Package 'Sleuth2'

Description

Data sets from Ramsey and Schafer's "Statistical Sleuth (2nd ed)"

Details

This package contains a variety of datasets. For a complete list, use library(help="Sleuth2") or Sleuth2Manual().

Author(s)

Original by F.L. Ramsey and D.W. Schafer

Modifications by Daniel W Schafer, Jeannie Sifneos and Berwin A Turlach

Maintainer: Berwin A Turlach [email protected]

Description

Data from an experiment concerning the effects of intrinsic and extrinsic motivation on creativity. Subjects with considerable experience in creative writing were randomly assigned to one of two treatment groups.

Usage

case0101

Format

A data frame with 47 observations on the following 2 variables.

Score

creativity score

Treatment

factor denoting the treatment group

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Amabile, T. (1985). Motivation and Creativity: Effects of Motivational Orientation on Creative Writers, Journal of Personality and Social Psychology 48(2): 393–399.

Examples

str(case0101)
boxplot(Score~Treatment, case0101)

Description

The data are the beginning salaries for all 32 male and all 61 female skilled, entry–level clerical employees hired by a bank between 1969 and 1977.

Usage

case0102

Format

A data frame with 93 observations on the following 2 variables.

Salary

starting salaries (in US$\$$)

Sex

sex of the clerical employee

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Roberts, H.V. (1979). Harris Trust and Savings Bank: An Analysis of Employee Compensation, Report 7946, Center for Mathematical Studies in Business and Economics, University of Chicago Graduate School of Business.

See Also

case1202

Examples

str(case0102)
boxplot(Salary~Sex, case0102)

Description

As evidence in support of natural selection, Bumpus presented measurements on house sparrows brought to the Anatomical Laboratory of Brown University after an uncommonly severe winter storm. Some of these birds had survived and some had perished. Bumpus asked whether those that perished did so because they lacked physical characteristics enabling them to withstand the intensity of that particular instance of selective elimination. The data are on the humerus (arm bone) lengths for the 24 adult male sparrows that perished and for the 35 adult males that survived.

Usage

case0201

Format

A data frame with 59 observations on the following 2 variables.

Humerus

Humerus length of adult male sparrows (in inches)

Status

factor variable indicating whether the sparrow perished or survived in a winter storm

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

See Also

ex0221, ex2016

Examples

str(case0201)
with(subset(case0201, Status=="Perished"), stem(Humerus, scale=10))
with(subset(case0201, Status=="Survived"), stem(Humerus))

Description

Are any physiological indicators associated with schizophrenia? In a 1990 article, researchers reported the results of a study that controlled for genetic and socioeconomic differences by examining 15 pairs of monozygotic twins, where one of the twins was schizophrenic and the other was not. The researchers used magnetic resonance imaging to measure the volumes (in cm$^3$) of several regions and subregions of the twins' brains.

Usage

case0202

Format

A data frame with 15 observations on the following 2 variables.

Unaffect

volume of left hippocampus of unaffected twin (in cm$^3$)

Affected

volume of left hippocampus of affected twin (in cm$^3$)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Suddath, R.L., Christison, G.W., Torrey, E.F., Casanova, M.F. and Weinberger, D.R. (1990). Anatomical Abnormalities in the Brains of Monozygotic Twins Discordant for Schizophrenia, New England Journal of Medicine 322(12): 789–794.

Examples

str(case0202)
with(case0202, stem(Unaffect-Affected, scale=2))

Description

Does dropping silver iodide onto clouds increase the amount of rainfall they produce? In a randomized experiment, researchers measured the volume of rainfall in a target area (in acre-feet) on 26 suitable days in which the clouds were seeded and on 26 suitble days in which the clouds were not seeded.

Usage

case0301

Format

A data frame with 52 observations on the following 2 variables.

Rainfall

the volume of rainfall in the target area (in acre-feet)

Treatment

a factor with levels "Unseeded" and "Seeded" indicating whether the clouds were unseeded or seeded.

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Simpson, J., Olsen, A., and Eden, J. (1975). A Bayesian Analysis of a Multiplicative Treatment Effect in Weather Modification. Technometrics 17: 161–166.

Examples

str(case0301)
boxplot(Rainfall ~ Treatment, case0301)
boxplot(log(Rainfall) ~ Treatment, case0301)
library(lattice)
bwplot(Treatment ~ log(Rainfall), case0301)
bwplot(log(Rainfall) ~ Treatment, case0301)

Description

In 1987, researchers measured the TCDD concentration in blood samples from 646 U.S. veterans of the Vietnam War and from 97 U.S. veterans who did not serve in Vietnam. TCDD is a carcinogenic dioxin in the herbicide called Agent Orange, which was used to clear jungle hiding areas by the U.S. military in the Vietnam War between 1962 and 1970.

Usage

data(case0302)

Format

A data frame with 743 observations on the following 2 variables.

Dioxin

the concentration of TCDD, in parts per trillion

Veteran

factor variable with two levels, "Vietnam" and "Other", to indicate the type of veteran

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Centers for Disease Control Veterans Health Studies: Serum 2,3,7,8-Tetraclorodibenzo-p-dioxin Levels in U.S. Army Vietnam-era Veterans. Journal of the American Medical Association 260: 1249–1254.

Examples

str(case0302)
boxplot(Dioxin ~ Veteran, case0302)
t.test(Dioxin ~ Veteran, case0302)
## To examine results with largest dioxin omitted
t.test(Dioxin ~ Veteran, case0302, subset=(Dioxin < 40))

Description

The number of space shuttle O-ring incidents for 4 space shuttle launches when the air temperatures was below 65 degrees F and for 20 space shuttle launches when the air temperature was above 65 degrees F.

Usage

case0401

Format

A data frame with 24 observations on the following 2 variables.

Incidents

the number of O-ring incidents

Launch

factor variable with two levels—"Cool" and "Warm"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Feynman, R.P. (1988). What do You Care What Other People Think? W. W. Norton.

See Also

ex2011, ex2223

Examples

str(case0401)
stem(subset(case0401, Launch=="Cool", Incidents, drop=TRUE))
stem(subset(case0401, Launch=="Warm", Incidents, drop=TRUE))

Description

Educational researchers randomly assigned 28 ninth-year students in Australia to receive coordinate geometry training in one of two ways: a conventional way and a modified way. After the training, the students were asked to solve a coordinate geometry problem. The time to complete the problem was recorded, but five students in the “conventional” group did not complete the solution in the five minute alloted time.

Usage

case0402

Format

A data frame with 28 observations on the following 3 variables.

Time

the time (in seconds) that the student worked on the problem

Treatmt

factor variable with two levels—"Modified" and "Conventional"

Censor

1 if the individual did not complete the problem in 5 minutes, 0 if they did

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Sweller, J., Chandler, P., Tierney, P. and Cooper, M. (1990). Cognitive Load as a Factor in the Structuring of Technical Material, Journal of Experimental Psychology General 119(2): 176–192.

Examples

str(case0402)
stem(subset(case0402, Treatmt=="Conventional", Time, drop=TRUE))
stem(subset(case0402, Treatmt=="Modified", Time, drop=TRUE))
wilcox.test(Time ~ Treatmt, case0402)

Description

Female mice were randomly assigned to six treatment groups to investigate whether restricting dietary intake increases life expectancy. Diet treatments were:

1. "NP"—mice ate unlimited amount of nonpurified, standard diet

2. "N/N85"—mice fed normally before and after weaning. After weaning, ration was controlled at 85 kcal/wk

3. "N/R50"—normal diet before weaning and reduced calorie diet (50 kcal/wk) after weaning

4. "R/R50"—reduced calorie diet of 50 kcal/wk both before and after weaning

5. "N/R50 lopro"—normal diet before weaning, restricted diet (50 kcal/wk) after weaning and dietary protein content decreased with advancing age

6. "N/R40"—normal diet before weaning and reduced diet (40 Kcal/wk) after weaning.

Usage

case0501

Format

A data frame with 349 observations on the following 2 variables.

Lifetime

the lifetime of the mice (in months)

Diet

factor variable with six levels—"NP", "N/N85", "lopro", "N/R50", "R/R50" and "N/R40"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Weindruch, R., Walford, R.L., Fligiel, S. and Guthrie D. (1986). The Retardation of Aging in Mice by Dietary Restriction: Longevity, Cancer, Immunity and Lifetime Energy Intake, Journal of Nutrition 116(4):641–54.

Examples

str(case0501)
boxplot(Lifetime~Diet, width=c(rep(.8,6)), data=case0501,
        xlab="Diet", ylab="Lifetime in months")
summary(subset(case0501, Diet=="NP", Lifetime))

Description

In 1968, Dr. Benjamin Spock was tried in Boston on charges of conspiring to violate the Selective Service Act by encouraging young men to resist being drafted into military service for Vietnam. The defence in the case challenged the method of jury selection claiming that women were underrepresented. Boston juries are selected in three stages. First 300 names are selected at random from the City Directory, then a venire of 30 or more jurors is selected from the initial list of 300 and finally, an actual jury is selected from the venire in a nonrandom process allowing each side to exclude certain jurors. There was one woman on the venire and no women on the final list. The defence argued that the judge in the trial had a history of venires in which women were systematically underrepresented and compared the judge's recent venires with the venires of six other Boston area district judges.

Usage

case0502

Format

A data frame with 46 observations on the following 2 variables.

Percent

is the percent of women on the venire's of the Spock trial judge and 6 other Boston area judges

Judge

a factor with levels "Spock's", "A", "B", "C", "D", "E" and "F"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Zeisel, H. and Kalven, H. Jr. (1972). Parking Tickets and Missing Women: Statistics and the Law in Tanur, J.M. et al. (eds.) Statistics: A Guide to the Unknown, Holden-Day.

Examples

str(case0502)
boxplot(Percent~Judge, data=case0502,
        xlab="Judge",ylab="Percentage of Women")
percent.spocks <- subset(case0502, Judge == "Spock's", Percent)
percent.others <- subset(case0502, Judge != "Spock's", Percent)
t.test( percent.spocks,percent.others)
summary(aov(Percent~Judge, case0502, subset = Judge != "Spock's"))

#as in Display 5.10
summary(aov(Percent~Judge, case0502))

Description

Study explores how physical handicaps affect people's perception of employment qualifications. Researchers prepared 5 videotaped job interviews using actors with a script designed to reflect an interview with an applicant of average qualifications. The 5 tapes differed only in that the applicant appeared with a different handicap in each one. Seventy undergraduate students were randomly assigned to view the tapes and rate the qualification of the applicant on a 0-10 point scale.

Usage

case0601

Format

A data frame with 70 observations on the following 2 variables.

Score

is the score each student gave to the applicant

Handicap

is a factor variable with 5 levels—"None", "Amputee", "Crutches", "Hearing" and "Wheelchair"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Cesare, S.J., Tannenbaum, R.J. and Dalessio, A. (1990). Interviewers' Decisions Related to Applicant Handicap Type and Rater Empathy, Human Performance 3(3): 157–171.

Examples

str(case0601)
boxplot(Score~Handicap, data=case0601, ylab="Score")
aov.handicap <- aov(Score ~ Handicap, case0601)
summary(aov.handicap)
TukeyHSD(aov.handicap)

#Calculate confidence interval for linear combination
#(wheelchair+crutches)/2 - (amputee+hearing)/2 as in Display 6.4
mean.handicaps <- with(case0601, tapply(Score, Handicap, mean))
var.handicaps <- with(case0601, tapply(Score, Handicap, var))

n <- 14
s.pooled <- sqrt(sum((n-1)*var.handicaps)/sum((n-1)*5))

## either
cr.wh <- mean.handicaps["Wheelchair"] + mean.handicaps["Crutches"]
am.he <- mean.handicaps["Amputee"] + mean.handicaps["Hearing"]
g <- cr.wh/2 - am.he/2
## or
contr <- c(0, -1, 1, -1, 1)/2
g <- sum(contr * mean.handicaps)

se.g <- s.pooled * sqrt(sum(contr^2)/n)
t.65 <- qt(.975, 65)
## ci
g + c(-1,1) * t.65 * se.g

Description

Do female Platyfish prefer male Platyfish with yellow swordtails? A.L. Basolo proposed and tested a selection model in which females have a pre-existing bias for a male trait even before the males possess it. Six pairs of males were surgically given artificial, plastic swordtails—one pair received a bright yellow sword, the other a transparent sword. Females were given the opportunity to engage in courtship activity with either of the males. Of the total time spent by each female engaged in courtship during a 20 minute observation period, the percentages of time spent with the yellow-sword male were recorded.

Usage

case0602

Format

A data frame with 84 observations on the following 3 variables.

Proportion

The proportion of courtship time spent by 84 females with the yellow-sword males

Pair

Factor variable with 6 levels—"Pair 1", "Pair 2", "Pair 3", "Pair 4", "Pair 5" and "Pair 6"

Length

Body size of the males

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Basolo, A.L. (1990). Female Preference Predates the Evolution of the Sword in Swordtail Fish, Science 250: 808–810.

Examples

str(case0602)
boxplot(Proportion~Pair, case0602, ylab="Proportion")

#as in Display 6.5 
summary(aov(Proportion~Pair, case0602))

n.fish  <- with(case0602, tapply(Proportion, Pair, length))
av.fish <- with(case0602, tapply(Proportion, Pair, mean))
sd.fish <- with(case0602, tapply(Proportion, Pair, sd))
male.body.size <- with(case0602, tapply(Length, Pair, unique))
mean.body <- mean(male.body.size)
table.fish <- data.frame(n.fish, round(av.fish*100,2),
                         round(sd.fish*100,2), male.body.size,
                         2*(male.body.size-mean.body))
names(table.fish) <- c("n", "average", "sd", "male.body.size", "coefficient")
s.pooled <- with(table.fish, round(sqrt(sum(sd^2*(n-1))/sum(n-1)),2))
g <- with(table.fish, sum(average*coefficient))
se.g <- with(table.fish, round(s.pooled*sqrt(sum(coefficient^2/n)),2))
g/se.g

Description

Hubble's initial data on 24 nebulae outside the Milky Way.

Usage

case0701

Format

A data frame with 24 observations on the following 2 variables.

Velocity

recession velocity (in kilometres per second)

Distance

distance from earth (in magaparsec)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Hubble, E. (1929). A Relation Between Distance and Radial Velocity Among Extragalactic Nebulae, Proceedings of the National Academy of Science 15: 168–173.

See Also

ex0727

Examples

str(case0701)
plot(case0701)

Description

A certain kind of meat processing may begin once the pH in postmortem muscle of a steer carcass has decreased sufficiently. To estimate the timepoint at which pH has dropped sufficiently, 10 steer carcasses were assigned to be measured for pH at one of five times after slaughter.

Usage

case0702

Format

A data frame with 10 observations on the following 2 variables.

Time

time after slaughter (hours)

pH

pH level in postmortem muscle

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Schwenke, J.R. and Milliken, G.A. (1991). On the Calibration Problem Extended to Nonlinear Models, Biometrics 47(2): 563–574.

See Also

ex0816

Examples

str(case0702)
plot(case0702)

Description

The data are the numbers of reptile and amphibian species and the island areas for seven islands in the West Indies.

Usage

case0801

Format

A data frame with 7 observations on the following 2 variables.

Area

area of island (in square miles)

Species

number of reptile and amphibian species on island

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

Examples

str(case0801)
plot(case0801)

Description

In an industrial laboratory, under uniform conditions, batches of electrical insulating fluid were subjected to constant voltages until the insulating property of the fluids broke down. Seven different voltage levels were studied and the measured reponses were the times until breakdown.

Usage

case0802

Format

A data frame with 76 observations on the following 3 variables.

Time

times until breakdown (in minutes)

Voltage

voltage applied (in kV)

Group

factor variable (group number)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

Examples

str(case0802)
plot(log(Time)~Voltage, case0802)

Description

Meadowfoam is a small plant found growing in moist meadows of the US Pacific Northwest. Researchers reported the results from one study in a series designed to find out how to elevate meadowfoam production to a profitable crop. In a controlled growth chamber, they focused on the effects of two light–related factors: light intensity and the timeing of the onset of the ligth treatment.

Usage

case0901

Format

A data frame with 24 observations on the following 3 variables.

Flowers

average number of flowers per meadowfoam plant

Time

time light intensity regiments started

Intens

light intensity (in $\mu$mol/m$^2$/sec)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

Examples

str(case0901)
plot(Flowers~Intens, case0901, pch= ifelse(Time=="Early", 19, 21))

Description

The data are the average values of brain weight, body weight, gestation lengths (length of pregnancy) and litter size for 96 species of mammals.

Usage

case0902

Format

A data frame with 96 observations on the following 5 variables.

Species

species

Brain

average brain weight (in grams)

Body

average body weight (in kilograms)

Gestation

gestation period (in days)

Litter

average litter size

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

See Also

case0902

Examples

str(case0902)
pairs(log(Brain)~log(Body)+log(Litter)+Gestation, case0902)

Description

In 1609 Galileo proved mathematically that the trajectory of a body falling with a horizontal velocity component is a parabola. His search for an experimental setting in which horizontal motion was not affected appreciably (to study inertia) let him to construct a certain apparatus. The data comes from one of his experiments.

Usage

case1001

Format

A data frame with 7 observations on the following 2 variables.

Distance

horizontal distances (in punti)

Height

initial height (in punti)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

Examples

str(case1001)
plot(Distance ~ Height, case1001)

Description

The data are on in–flight energy expenditure and body mass from 20 energy studies on three types of flying vertebrates: echolocating bats, non–echolocating bats and non–echolocating birds.

Usage

case1002

Format

A data frame with 20 observations on the following 4 variables.

Species

species

Mass

mass (in grams)

Type

a factor with 3 levels indicating the type of flying vertebrate

Energy

in–flight energy expenditure (in W)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Speakman, J.R. and Racey, P.A. (1991). No cost of Echolocation for Bats in Flight, Nature 350: 421–423.

Examples

str(case1002)

plot(log(Energy)~log(Mass), case1002,
     pch = ifelse(Type=="echolocating bats", 19,
                  ifelse(Type=="non-echolocating birds", 21, 24)))

plot(Energy~Mass, case1002, log="xy",
     xlab = "Body Mass (g) (log scale)",
     ylab = "Energy Expenditure (W) (log scale)", 
     pch = ifelse(Type=="echolocating bats", 19,
                  ifelse(Type=="non-echolocating birds", 21, 24)))
legend(7, 50, pch=c(24, 21, 19),
     c("Non-echolocating bats", "Non-echolocating birds","Echolocating bats"))

library(lattice)
yticks <- c(1,2,5,10,20,50)
xticks <- c(10,20,50,100,200,500)
xyplot(Energy ~ Mass, case1002, groups=Type, 
       scales = list(log=TRUE, y=list(at=yticks), x=list(at=xticks)),
       ylab = "Energy Expenditure (W) (log scale)",
       xlab = "Body Mass (g) (log scale)", 
       auto.key = list(x = 0.2, y = 0.9, corner = c(0, 1), border = TRUE))

Description

These data were collected on 18 women and 14 men to investigate a certain theory on why women exhibit a lower tolerance for alcohol and develop alcohol–related liver disease more readily than men.

Usage

case1101

Format

A data frame with 32 observations on the following 5 variables.

Subject

subject number in the study

Metabol

first–pass metabolism of alcohol in the stomach (in mmol/liter-hour)

Gastric

gastric alcohol dehydrogenase activity in the stomach (in $\mu$mol/min/g of tissue)

Sex

sex of the subject

Alcohol

whether the subject is alcoholic or not

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

Examples

str(case1101)

plot(Metabol~Gastric, case1101,
     pch=ifelse(Sex=="Female", 19, 21),
     col=ifelse(Alcohol=="Alcoholic", "red", "green"))
legend(1,12, pch=c(19,21,19,21), col=c("green","green", "red", "red"),
             c("Non-alcoholic Females", "Non-alcoholic Males",
               "Alcoholic Females", "Alcoholic Males"))

library(lattice)
xyplot(Metabol~Gastric|Sex*Alcohol, case1101)
xyplot(Metabol~Gastric, case1101, groups=Sex:Alcohol,
        auto.key=list(x=0.2, y=0.8, corner=c(0,0), border=TRUE))

Description

The human brain is protected from bacteria and toxins, which course through the blood–stream, by a single layer of cells called the blood–brain barrier. These data come from an experiment (on rats, which possess a similar barrier) to study a method of disrupting the barrier by infusing a solution of concentrated sugars.

Usage

case1102

Format

A data frame with 34 observations on the following 9 variables.

Brain

Brain tumor count (per gm)

Liver

Liver count (per gm)

Time

Sacrifice time (in hours)

Treat

Treatment received

Days

Days post inoculation

Sex

Sex of the rat

Weight

Initial weight (in grams)

Loss

Weight loss (in grams)

Tumor

Tumor weight (in 10$^{-4}$ grams)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

Examples

str(case1102)

plot(Brain/Liver ~ Time, case1102, log="xy", pch=ifelse(Treat=="BD", 19,21))
legend(10,0.1, pch=c(19,21), c("Saline control", "Barrier disruption"))

Description

Data on the average SAT scores for US states in 1982 and possible associated factors.

Usage

case1201

Format

A data frame with 50 observations on the following 8 variables.

State

US state

SAT

state averages of the total SAT (verbal + quantitative) scores

Takers

the percentage of the total eligible students (high school seniors) in the state who took the exam

Income

the median income of families of test–takers (in hundreds of dollars)

Years

the average number of years that the test–takers had formal studies in social sciences, natural sciences and humanities

Public

the percentage of the test–takers who attended public secondary schools

Expend

the total state expenditure on secondary schools (in hundreds of dollars per student)

Rank

the median percentile ranking of the test–takers within their secondary school classes

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

Examples

str(case1201)
pairs(SAT~Rank+Years+Income+Public+Expend, case1201)

Description

Data on employees from one job category (skilled, entry–level clerical) of a bank that was sued for sex discrimination. The data are on 32 male and 61 female employees, hired between 1965 and 1975.

Usage

case1202

Format

A data frame with 93 observations on the following 7 variables.

Bsal

Annual salary at time of hire

Sal77

Salary as of March 1975

Sex

Sex of employee

Senior

Seniority (months since first hired)

Age

Age of employee (in months)

Educ

Education (in years)

Exper

Work experience prior to employment with the bank (months)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Roberts, H.V. (1979). Harris Trust and Savings Bank: An Analysis of Employee Compensation, Report 7946, Center for Mathematical Studies in Business and Economics, University of Chicago Graduate School of Business.

See Also

case0102

Examples

str(case1202)
pairs(Sal77~Bsal+Senior+Age+Exper, case1202)

Description

To study the influence of ocean grazers on regeneration rates of seaweed in the intertidal zone, a researcher scraped rock plots free of seaweed and observed the degree of regeneration when certain types of seaweed-grazing animals were denied access. The grazers were limpets (L), small fishes (f) and large fishes (F). Each plot received one of six treatments named by which grazers were allowed access. In addition, the researcher applied the treatments in eight blocks of 12 plots each. Within each block she randomly assigned treatments to plots. The blocks covered a wide range of tidal conditions.

Usage

case1301

Format

A data frame with 96 observations on the following 3 variables.

Cover

percent of regenerated seaweed cover

Block

a factor with levels "B1", "B2", "B3", "B4", "B5", "B6", "B7" and "B8"

Treat

a factor indicating treatment, with levels "C", "f", "fF", "L", "Lf" and "LfF"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Olson, A. (1993). Evolutionary and Ecological Interactions Affecting Seaweeds, Ph.D. Thesis. Oregon State University.

Examples

str(case1301)

# full two-way model with interactions
fitfull <- aov(Cover ~ Treat*Block, case1301)
# Residual plot indicates a transformation might help
plot(fitfull)  

# Log of seaweed "regeneration ratio" 
y <- with(case1301, log(Cover/(100-Cover)))
# Full two-way model with interactions
fitfull <- aov(y~Treat*Block, case1301)
# No problems indicated by residual plot
plot(fitfull)
# Note that interactions are not statistically significant
anova(fitfull) 
# Additive model (no interactions)
fitadditive <- aov(y ~ Treat + Block, case1301) 

# Make indicator variables for presence of limpets, small fish, and large fish 
lmp <- with(case1301, ifelse(Treat %in% c("L", "Lf", "LfF"), 1, 0))
sml <- with(case1301, ifelse(Treat %in% c("f", "fF", "Lf", "LfF"), 1, 0))
big <- with(case1301, ifelse(Treat %in% c("fF", "LfF"), 1, 0))

fitsimple <- lm(y ~ Block + lmp + sml + big, case1301)
# Model with main effects of 3 "presence" factors seems ok.
anova(fitsimple, fitadditive)  
summary(fitsimple, cor=FALSE)

Description

One company of soldiers in each of 10 platoons was assigned to a Pygmalion treatment group, with remaining companies in the platoon assigned to a control group. Leaders of the Pygmalion platoons were told their soldiers had done particularly well on a battery of tests which were, in fact, non-existent. In this randomised block experiment, platoons are experimental units, companies are blocks, and average Practical Specialty test score for soldiers in a platoon is the response. The researchers wished to see if the platoon response was affected by the artificially-induced expectations of the platoon leader.

Usage

case1302

Format

A data frame with 29 observations on the following 3 variables.

Company

a factor indicating company identification, with levels "C1", "C2", ..., "C10"

Treat

a factor indicating treatment with two levels, "Pygmalion" and "Control"

Score

average score on practical specialty test of all soldiers in the platoon

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Eden, D. (1990). Pygmalion Without Interpersonal Contrast Effects: Whole Groups Gain from Raising Manager Expectations, Journal of Applied Psychology 75(4): 395–398.

Examples

str(case1302)

# two-way model with interactions
fitfull <- aov(Score ~ Company*Treat, case1302)
# No problems are indicated by residual plot
plot(fitfull)
# Interaction terms are not statistically significant
anova(fitfull)  
# Additive model, with "treatment contrast" for treatment:
fitadditive <- aov(Score ~ Company + Treat, case1302)
# Interpret treatment effect as coefficient of Treat
anova(fitadditive)

Description

Researchers taught each of 4 chimps to learn 10 words in American sign language and recorded the learning time for each word for each chimp. They wished to describe chimp differences and word differences.

Usage

case1401

Format

A data frame with 40 observations on the following 3 variables.

Minutes

learning time in minutes

Chimp

a factor indicating chimp, with four levels "Booee", "Cindy", "Bruno" and "Thelma"

Sign

a factor indicating word taught, with 10 levels

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Fouts, R.S. (1973). Acquisition and Testing of Gestural Signs in Four Young Chimpanzees, Science 180: 978-980.

Examples

str(case1401)

fitadditive <- aov(Minutes ~ Chimp + Sign, case1401)
# Residual plot indicates a transformation may help
plot(fitadditive) 

fitadditive <- aov(log(Minutes) ~ Chimp + Sign, case1401)
# No problems are indicated by residual plot
plot(fitadditive) 
anova(fitadditive)

# Tukey multiple comparisons of sign differences
mcSign <- TukeyHSD(fitadditive,"Sign")  
mcSign
plot(mcSign)
mcChimp <- TukeyHSD(fitadditive,"Chimp")
mcChimp
par(cex=.7)
plot(mcChimp)

Description

In a completely randomized design with a 2x3x5 factorial treatment structure, researchers randomly assigned one of 30 treatment combinations to open-topped growing chambers, in which two soybean cultivars were planted. The responses for each chamber were the yields of the two types of soybean.

Usage

case1402

Format

A data frame with 30 observations on the following 5 variables.

Stress

a factor indicating treatment, with two levels "Well-watered" and "Stressed"

SO2

a quantitative treatment with three levels 0, 0.02 and 0.06

O3

a quantitative treatment with five levels 0.02, 0.05, 0.07, 0.08 and 0.10

Forrest

the yield of the Forrest cultivar of soybean (in kg/ha)

William

the yield of the Williams cultivar of soybean (in kg/ha)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Heggestad, H.E. and Lesser, V.M. (1990). Effects of Chronic Doses of Sulfur Dioxide, Ozone, and Drought on Yields and Growth of Soybeans Under Field Conditions, Journal of Environmental Quality 19: 488–495.

Examples

str(case1402)

plot(Forrest ~ O3,  case1402, log="y", pch=ifelse(Stress=="Stressed",19,21))
plot(Forrest ~ SO2, case1402, log="y", pch=ifelse(Stress=="Stressed",19,21))

fitbig <- lm(log(Forrest) ~  O3*SO2*Stress, case1402)
# Residual plot does not indicate any problem.
plot(fitbig) 
# The 3-factor interaction is not statistically significant.
anova(fitbig)  
# Drop the three-factor interaction
fit2 <- update(fitbig, ~ . - O3:SO2:Stress) 
anova(fit2)

fitadditive <- lm(log(Forrest) ~ O3 + SO2 + Stress, case1402)
summary(fitadditive)

Description

Data from an observational study of nitrate levels measured at three week intervals for five years in two watersheds. One of the watersheds was undisturbed and the other had been logged with a patchwork pattern.

Usage

case1501

Format

A data frame with 88 observations on the following 3 variables.

Week

week after the start of the study

Patch

residual nitrate level in the logged watershed (ppm) (see Display 15.3 of Statistical Sleuth)

Nocut

residual nitrate level in the undisturbed watershed (ppm)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Harr, R.D., Friderksen, R.L., and Rothacher, J. (1979). Changes in Streamflow Following Timber Harvests in Southwestern Oregon, USDA/USFS Research Paper PNW-249, Pacific NW Forest and Range Experiment Station, Portland, Oregon.

Examples

str(case1501)

par(mfrow=c(2,1)) # Make 2 plots on one page
plot(Nocut ~ Week, case1501)
plot(Patch ~ Week, case1501)
par(mfrow=c(1,1))
lag.plot(case1501$Nocut,do.lines=FALSE) 
lag.plot(case1501$Patch,do.lines=FALSE)

# Compute pooled estimate of first autocorrelation coefficient
# First auto covariance, Nocut
ac1nocut <- acf(case1501$Nocut,lag.max=1,type="covariance",plot=FALSE)$acf[2] 
n <- length(case1501$Nocut)
# Zeroth autocovariance for Nocut
ac0nocut <- var(case1501$Nocut[2:n])*(n-2)/(n-1)
# First auto covariance, Patch
ac1patch <- acf(case1501$Patch,lag.max=1,type="covariance",plot=FALSE)$acf[2]
# Zeroth autocovariance for PATCH
ac0patch <- var(case1501$Patch [2:n])*(n-2)/(n-1)

ac1pool <- (ac1nocut + ac1patch)/2
ac0pool <- (ac0nocut + ac0patch)/2

acorr1 <- ac1pool/ac0pool
acorr1  # Pooled estimate of first lag serial coefficient

Description

The data are the temperatures (in degrees Celsius) averaged for the northern hemisphere over a full year, for years 1880 to 1987. The 108-year average temperature has been subtracted, so each observation is the temperature difference from the series average.

Usage

case1502

Format

A data frame with 108 observations on the following 2 variables.

Year

year in which yearly average temperature was computed, from 1880 to 1987

Temp

northern hemisphere temperature minus the 108-year average (degrees Celsius)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Jones, P.D. (1988). Hemispheric Surface Air Temperature Variations—Recent Trends Plus an Update to 1987, Journal of Climatology 1: 654–660.

Examples

str(case1502)

# Residuals from regression fit, ignoring autocorrelation
resids <- lm(Temp ~ Year, case1502)$res
# PACF plot shows evidence of 1st order auto correlation
acf(resids,type="partial")
# 1st autocorrelation coef.
acorr1 <- acf(resids,type="correlation",plot=FALSE)$acf[2] 

# Fit regression with filtered response and explanatory variables:
n <- length(case1502$Temp)
y <- with(case1502, Temp [2:n] - acorr1* Temp [1:(n-1)])
x <- with(case1502, Year [2:n] - acorr1* Year [1:(n-1)])
fit <- lm(y ~ x)
summary(fit)  # Interpret coefficient of x as coefficient of Year

Description

Researchers taught 18 monkeys to distinguish each of 100 pairs of objects, 20 pairs each at 16, 12, 8, 4, and 2 weeks prior to a treatment. After this training, they blocked access to the hippocampal formation in 11 of the monkeys. All monkeys were then tested on their ability to distinguish the objects. The five-dimensional response for each monkey is the number of correct objects distinguished among those taught at 16, 12, 8, 4, and 2 weeks prior to treatment.

Usage

case1601

Format

A data frame with 18 observations on the following 7 variables.

Monkey

Monkey name

Treatment

a treatment factor with levels "Control" and "Treated"

Week2

percentage of 20 objects taught 2 weeks prior to treatment that were correctly distinguished in the test

Week4

percentage of 20 objects taught 4 weeks prior to treatment that were correctly distinguished in the test

Week8

percentage of 20 objects taught 8 weeks prior to treatment that were correctly distinguished in the test

Week12

percentage of 20 objects taught 12 weeks prior to treatment that were correctly distinguished in the test

Week16

percentage of 20 objects taught 16 weeks prior to treatment that were correctly distinguished in the test

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Sola-Morgan, S. M. and Squire, L. R. (1990). The Primate Hippocampal Formation: Evidence for a Time-limited Role in Memory Storage, Science 250: 288–290.

Examples

str(case1601)

# short-term response
short <- with(case1601, (Week2 + Week4)/2)
# long-term response
long <- with(case1601, (Week8 + Week12 + Week16)/3)
# Multivariate analysis of variance
mfit <- manova(cbind(short,long) ~ Treatment, case1601) 
summary(mfit)

Description

In a randomized, double-blind, crossover experiment, researchers randomly assigned 20 volunteer hospital employees to either a low-fiber or low-fiber treatment group. The subjects followed the diets for six weeks. After two weeks on their normal diet, all patients crossed over to the other treatment group for another six weeks. The total serum cholesterol (in mg/dl) was measured on each patient before the first treatment, at the end of the first six week treatment, and at the end of the second six week treatment.

Usage

case1602

Format

A data frame with 20 observations on the following 4 variables.

Baseline

total serum cholesterol before treatment

Hifiber

total serum cholesterol after the high fiber diet

Lofiber

total serum cholesterol after the low fiber diet

Order

factor to identify order of treatment, with two levels "HL" and "LH"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Swain, J.F., Rouse, I.L., Curley, C.B., and Sacks, F.M. (1990). Comparison of the Effects of Oat Bran and Low-fiber Wheat on Serum Lipoprotein Levels and Blood Pressure, New England Journal of Medicine 320: 1746–1747.

Examples

str(case1602)

subjects <- 1:20
ordersubjects <- order(case1602$Baseline)
plot(1:20, case1602$Baseline[ordersubjects], pch=24,
     xlab="Subjects (Ordered According to Baseline Cholesterol)",
     ylab="Total Serum Cholesterol (mg/dl)")
points(1:20, case1602$Lofiber[ordersubjects], pch=19, col=5)
points(1:20, case1602$Hifiber[ordersubjects], pch=21, col=3)
legend(1,245,legend=c("Baseline","After Low Fiber Diet","After High Fiber Diet"),
  pch=c(24,19,21),col=c(1,5,3))

diff <- with(case1602, Hifiber-Lofiber)
plot(subjects, diff, pch=ifelse(case1602$Order=="HL",19,21))
abline(h=0)
t.test(diff ~ Order, case1602) # Test for order of treatment effect
t.test(diff) # Test for treatment effect

Description

Engineers manipulated three factors (with 3, 2, and 4 levels each) in the construction and operation of printer rods, to see if they influenced the magnetic force around the rod.

Usage

case1701

Format

A data frame with 44 observations on the following 14 variables.

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

Examples

str(case1701)

pca <- princomp(case1701[,1:11])
summary(pca)
# The first 3 principal components account for 99.7% of the variation
screeplot(pca)
# The loadings suggest the following meaningful summaries...
loadings(pca)

overallaverage <- with(case1701, (L1 + L2 + L3 + L4 + L5 + L6 + L7 + L8 + L9 + L10 + L11)/11)
rightleftdiff <- with(case1701, (L9 + L10 + L11)/3 - (L1 + L2 + L3)/3)
middleleftdiff <- with(case1701, L6 - (L1 + L2)/2)

# Note 4 clusters and 1 outlier
pairs(cbind(overallaverage, rightleftdiff, middleleftdiff)) 

fit1 <- lm(overallaverage ~ Current*Configur*Material, case1701)
anova(fit1)

Description

Thirty couples participated in a study of love and marriage. Wives and husbands responded separately to four questions:

1. What is the level of passionate love you feel for your spouse?

2. What is the level of passionate love your spouse feels for you?

3. What is the level of compassionate love you feel for your spouse?

4. What is the level of compassionate love your spouse feels for you?

Each response was recorded on a five-point scale: 1=None, 2=Very Little, 3=Some, 4=A Great Deal and 5=A Tremendous Amount.

Usage

case1702

Format

A data frame with 30 observations on the following 9 variables.

Couple

couple identification number

Hps

level of passionate love husband feels for spouse

Wps

level of passionate love wife feels for spouse

Hcs

level of compassionate love husband feels for spouse

Wcs

level of compassionate love wife feels for spouse

Hpy

level of passionate love husband perceives spouse to have for him

Wpy

level of passionate love wife perceives spouse to have for her

Hcy

level of compassionate love husband perceives spouse to have for him

Wcy

level of compassionate love husband perceives spouse to have for her

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Johnson, R.A. and Wichern, D.W. (1988). Applied Multivariate Statistical Analysis (2nd ed), Prentice-Hall.

Examples

str(case1702)

# feelings about spouse
tospouse <- with(case1702, cbind(Hps, Wps, Hcs, Wcs))
# perceived feelings from spouse
fromspouse <- with(case1702, cbind(Hpy, Wpy, Hcy, Wcy))
cca <- cancor(tospouse,fromspouse)
# Examine loadings of first canonical variables:
par(mfrow=c(2,1))
barplot(cca$xcoef[,1], ylab="first 'to spouse' loadings", 
     names=c("Hps","Wps","Hcs","Wcs")) 
barplot(cca$ycoef[,1], ylab="first 'from spouse' loadings", 
     names=c("Hpy","Wpy","Hcy","Wcy")) 

# The first canonical variable for 'to spouse" is mostly Hcs
# The first canonical variable for 'fom spouse' is mostly Hcy

can.to <- tospouse 
can.from <- fromspouse 
can.to.1 <- can.to[,1] # first canonical variable
can.from.1 <- can.from[,1] # first canonical variable
pairs(cbind(can.to.1, case1702$Hcs, can.from.1, case1702$Hcy),
	labels=c("1st cv 'to'","husband's compassionate","1st cv
        'from'","husband's perceived compassionate"))

Description

Lawyers collected data on convicted black murderers in the state of Georgia to see whether convicted black murderers whose victim was white were more likely to receive the death penalty than those whose victim was black, after accounting for aggravation level of the murder. They categorized murders into 6 progressively more serious types. Category 1 comprises barroom brawls, liquor-induced arguments lovers' quarrels, and similar crimes. Category 6 includes the most vicious, cruel, cold=blooded, unprovoked crimes.

Usage

case1902

Format

A data frame with 12 observations on the following 4 variables.

Aggravation

the aggravation level of the crime, a factor with levels "1", "2", "3", "4", "5" and "6"

Victim

a factor indicating race of murder victim, with levels "White" and "Black"

Death

number in the aggravation and victim category who received the death penalty

Nodeath

number in the aggravation and victim category who did not receive the death penalty

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Woodworth, G.C. (1989). Statistics and the Death Penalty, Stats 2: 9–12.

Examples

str(case1902)

# Add smidgeon to denominator because of zeros
empiricalodds <- with(case1902, Death/(Nodeath + .5))
plot(empiricalodds ~ as.numeric(Aggravation), case1902, log="y",
  pch=ifelse(Victim=="White", 21, 19),
  xlab="Aggravation Level of the Murder", ylab="Odds of Death Penalty")
legend(3.8,.02,legend=c("White Victim Murderers","Black Victim Murderers"),pch=c(21,19))

fitbig <- glm(cbind(Death,Nodeath) ~ Aggravation*Victim, case1902, family=binomial)
# No evidence of overdispersion; no statistically significant evidence
# of interactive effect 
anova(fitbig, test="Chisq") 
fitlinear <- glm(cbind(Death,Nodeath) ~ Aggravation + Victim, case1902, family=binomial)
summary(fitlinear)

# Mantel Haenszel Test, as an alternative
table1902   <- with(case1902, rbind(Death,Nodeath))
dim(table1902) <- c(2,2,6)
mantelhaen.test(table1902)

Description

This data frame contains the ages and sexes of the adult (over 15 years) survivors and nonsurvivors of the Donner party.

Usage

case2001

Format

A data frame with 45 observations on the following 3 variables.

Age

Age of person

Sex

Sex of person

Status

Whether the person survived or died

Details

In 1846 the Donner and Reed families left Springfield, Illinois, for California by covered wagon. In July, the Donner Party, as it became known, reached Fort Bridger, Wyoming. There its leaders decided to attempt a new and untested rote to the Sacramento Valley. Having reached its full size of 87 people and 20 wagons, the party was delayed by a difficult crossing of the Wasatch Range and again in the crossing of the desert west of the Great Salt Lake. The group became stranded in the eastern Sierra Nevada mountains when the region was hit by heavy snows in late October. By the time the last survivor was rescued on April 21, 1847, 40 of the 87 members had died from famine and exposure to extreme cold.

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Grayson, D.K. (1990). Donner Party Deaths: A Demographic Assessment, Journal of Anthropological Research 46: 223–242.

See Also

ex1918

Examples

str(case2001)

Description

A 1972–1981 health survey in The Hague, Netherlands, discovered an association between keeping pet birds and increased risk of lung cancer. To investigate birdkeeping as a risk factor, researchers conducted a case–control study of patients in 1985 at four hospitals in The Hague (population 450,000). They identified 49 cases of lung cancer among the patients who were registered with a general practice, who were age 65 or younger and who had resided in the city since 1965. They also selected 98 controls from a population of residents having the same general age structure.

Usage

case2002

Format

A data frame with 147 observations on the following 7 variables.

LC

Whether subject has lung cancer

FM

Sex of subject

SS

Socioeconomic status, determined by occupation of the household's principal wage earner

BK

Indicator for birdkeeping (caged birds in the home for more that 6 consecutive months from 5 to 14 years before diagnosis (cases) or examination (control))

AG

Age of subject (in years)

YR

Years of smoking prior to diagnosis or examination

CD

Average rate of smoking (in cigarettes per day)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Holst, P.A., Kromhout, D. and Brand, R. (1988). For Debate: Pet Birds as an Independent Risk Factor for Lung Cancer, British Medical Journal 297: 13–21.

Examples

str(case2002)

Description

In a study of the Krunnit Islands archipelago, researchers presented results of extensive bird surveys taken over four decades. They visited each island several times, cataloguing species. If a species was found on a specific island in 1949, it was considered to be at risk of extinction for the next survey of the island in 1959. If it was not found in 1959, it was counted as an “extinction”, even though it might reappear later. This data frame contains data on island size, number of species at risk to become extinct and number of extinctions.

Usage

case2101

Format

A data frame with 18 observations on the following 4 variables.

Island

Name of Island

Area

Area of Island

Atrisk

Number of species at risk

Extinct

Number of extinctions

Details

Scientists agree that preserving certain habitats in their natural states is necessary to slow the accelerating rate of species extinctions. But they are divided on how to construct such reserves. Given a finite amount of available land, is it better to have many small reserves or a few large one? Central to the debate on this question are observational studies of what has happened in island archipelagos, where nearly the same fauna tries to survive on islands of different sizes.

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

V\"ais\"anen, R.A. and J\"arvinen, O. (1977). Dynamics of Protected Bird Communities in a Finnish Archipelago, Journal of Animal Ecology 46: 891–908.

Examples

str(case2101)
logit <- function(p) log(p/(1-p))
plot(logit(Extinct/Atrisk) ~ log(Area), case2101)

Description

This data was collected by J.A. Bishop. Bishop selected seven locations progressively farther from Liverpool. At each location, Bishop chose eight trees at random. Equal number of dead (frozen) light (Typicals) and dark (Carbonaria) moths were glued to the trunks in lifelike positions. After 24 hours, a count was taken of the numbers of each morph that had been removed—presumably by predators.

Usage

case2102

Format

A data frame with 14 observations on the following 4 variables.

Morph

Morph, a factor with levels "light" and "dark"

Distance

Distance from Liverpool (in km)

Placed

Number of moths placed

Removed

Number of moths removed

Details

Population geneticists consider clines particularly favourable situations for investigating evolutionary phenomena. A cline is a region where two colour morphs of one species arrange themselves at opposite ends of an environmental gradient, with increasing mixtures occurring between. Such a cline exists near Liverpool, England, where a dark morph of a local moth has flourished in response to the blackening of tree trunks by air pollution from the mills. The moths are nocturnal, resting during the day on tree trunks, where their coloration acts as camouflage against predatory birds. In Liverpool, where tree trunks are blackened by smoke, a high percentage of the moths are of the dark morph. One encounters a higher percentage of the typical (pepper–and–salt) morph as one travels from the city into the Welsh countryside, where tree trunks are lighter. J.A. Bishop used this cline to study the intensity of natural selection.

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Bishop, J.A. (1972). An Experimental Study of the Cline of Industrial Melanism in Biston betularia [Lepidoptera] Between Urban Liverpool and Rural North Wales, Journal of Animal Ecology 41: 209–243.

Examples

str(case2102)

Description

Although male elephants are capable of reproducing by 14 to 17 years of age, your adult males are usually unsuccessful in competing with their larger elders for the attention of receptive females. Since male elephants continue to grow throughout their lifetimes, and since larger males tend to be more successful at mating, the males most likely to pass their genes to future generations are those whose characteristics enable them to live long lives. Joyce Poole studied a population of African elephants in Amboseli National Park, Kenya, for 8 years. This data frame contains the number of successful matings and ages (at the study's beginning) of 41 male elephants.

Usage

case2201

Format

A data frame with 41 observations on the following 2 variables.

Age

Age of elephant at beginning of study

Matings

Number of successful matings

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Poole, J.H. (1989). Mate Guarding, Reproductive Success and Female Choice in African Elephants, Animal Behavior 37: 842–849.

Examples

str(case2201)
plot(case2201)

Description

The Del Norte Salamander (plethodon elongates) is a small (5–7 cm) salamander found among rock rubble, rock outcrops and moss-covered talus in a narrow range of northwest California. To study the habitat characteristics of the species and particularly the tendency of these salamanders to reside in dwindling old-growth forests, researchers selected 47 sites from plausible salamander habitat in national forest and parkland. Randomly chosen grid points were searched for the presence of a site with suitable rocky habitat. At each suitable site, a 7 metre by 7 metre search are was examined for the number of salamanders it contained. This data frame contains the counts of salamanders at the sites, along with the percentage of forest canopy and age of the forest in years.

Usage

case2202

Format

A data frame with 47 observations on the following 4 variables.

Site

Investigated site

Salaman

Number of salamanders found in 49 m$^2$ area

PctCover

Percentage of canopy cover

Forestage

Forest age

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Welsh, H.H. and Lind, A.J. (1995). Journal of Herpetology 29(2): 198–210.

Examples

str(case2202)

Description

Researchers used 7 red and 7 black playing cards to randomly assign 14 volunteer males with high blood pressure to one of two diets for four weeks: a fish oil diet and a standard oil diet. These data are the reductions in diastolic blood pressure.

Usage

ex0112

Format

A data frame with 14 observations on the following 2 variables.

BP

reduction in diastolic blood pressure (in mm of mercury)

Diet

factor variable indicating the diet that the subject followed

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Knapp, H.R. and FitzGerald, G.A. (1989). The Antihypertensive Effects of Fish Oil, New England Journal of Medicine 320: 1037–1043.

Examples

str(ex0112)

Description

The data are the distances from the sun (scaled so that earth=10) and the order from the sun for the 9 planets in our solar system plus the asteroid belt (treated here as the fifth body from the sun).

Usage

ex0116

Format

A data frame with 10 observations on the following 3 variables.

Planet

name of body (planet or asteroid belt)

Order

order from sun

Distance

distance from sun (scaled so that earth's distance is 10)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

Examples

str(ex0116)

Description

The data are survival times (in days) of guinea pigs that were randomly assigned either to a control group or to a treatment group that received a dose of tubercle bacilli.

Usage

ex0211

Format

A data frame with 122 observations on the following 2 variables.

Lifetime

survival time of guinea pig (in days)

Group

a factor with levels "bacilli" and "control", indicating the group to which the guinea pig was assigned

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Doksum, K. (1974). Empirical Probability Plots and Statistical Inference for Nonlinear Models in the Two–sample Case, Annals of Statistics 2: 267–277.

Examples

str(ex0211)

Description

As evidence in support of natural selection, Bumpus presented measurements on house sparrows brought to the Anatomical Laboratory of Brown University after an uncommonly severe winter storm. Some of these birds had survived and some had perished. Bumpus asked whether those that perished did so because they lacked physical characteristics enabling them to withstand the intensity of that particular instance of selective elimination. The data are on the the weights, in grams, for the 24 adult male sparrows that perished and for the 35 adult males that survived.

Usage

ex0221

Format

A data frame with 59 observations on the following 2 variables.

Weight

weight of adult male sparrows (in grams)

Status

factor variable indicating whether the sparrow perished or survived in a winter storm

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

See Also

case0201, ex2016

Examples

str(ex0221)

Description

This data comes from an observational study to contrast cholesterol levels in rural and urban Guatemalan Indians

Usage

ex0222

Format

A data frame with 94 observations on the following 2 variables.

Cholesterol

Serum total cholesterol of individual (in mg/l)

Group

a factor with levels "Rural" and "Urban" indicating to which group the individual belongs

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Tejada, C., Charm, S., Guzman, M., Mendez, J. and Kurland, G. (1964). The Blood Viscosity of Various Socioeconomic Groups in Guatemala, American Journal of Clinical Nutrition: 303–308.

Examples

str(ex0222)

Description

The National Highway System Designation Act was signed into law in the United States on November 28, 1995. Among other things, the act abolished the federal mandate of 55 mile per hour maximum speed limits on roads in the United States and permitted states to establish their own limits. Of the 50 states (plus the District of Columbia), 32 increased their speed limits at the beginning of 1996 or sometime during 1996. These data are the percentage changes in interstate highway traffic fatalities from 1995 to 1996.

Usage

ex0223

Format

A data frame with 51 observations on the following 3 variables.

State

US state

Increase

a factor with levels "No" "Yes", indicating whether the state increased its speed limit

FatalitiesChange

percentage change in interstate traffic fatalities between 1995 and 1996

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Report to Congress: The Effect of Increased Speed Limits in the Post-NMSL Era, National Highway Traffic Safety Administration, February, 1998; available in the reports library at https://www-fars.nhtsa.dot.gov/.

Examples

str(ex0223)

Description

Researchers collected historical and current data on umpires to investigate their life expectancies following the collapse and death of a U.S. major league baseball umpire. They were investigating speculation that stress associated with the job posed a health risk. Data were found on 227 umpires who had died or had retired and were still living. The data set includes the dates of birth and death.

Usage

ex0321

Format

A data frame with 227 observations on the following 3 variables.

Lifelength

observed lifetime for those umpires who had died by the time of the study or current age of those still living

Censored

0 for those who had died by the time of the study or 1 for those who were still living

Expected

length from actuarial life tables for individuals who were alive at the time the person first became an umpire

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Cohen, R.S., Kamps, C.A., Kokoska, S., Segal E.M. and Tucker, J.B.(2000). Life Expectancy of Major League Baseball Umpires, The Physician and Sportsmedicine 28(5): 83–89.

Examples

str(ex0321)

Description

Data contains yearly skin cancer rates (per 100,000 people) in Connecticut from 1938 to 1972 with a code indicating those years that came two years after higher than average sunspot activity and those years that came two years after lower than average sunspot activity.

Usage

ex0323

Format

A data frame with 35 observations on the following 3 variables.

Year

year

Rate

skin cancer rate per 100,000 people

Sunspot

a factor with levels "High" and "Low"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Andrews, D.F. and Herzberg, A.M. (1985). Data: A Collection of Problems from many Fields for the Student and Research Worker, Springer-Verlag.

Examples

str(ex0323)

Description

Life expectancy and per capita income for 20 industrialized countries and 9 petroleum exporting countries. Note that there is a missing value for South Africa.

Usage

ex0327

Format

A data frame with 29 observations on the following 4 variables.

Country

a character vector indicating the country

Life

life expectancy (years)

Income

income in 1974 (U.S. dollars)

Type

factor variable with levels "Industrialized" and "Petroleum"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Leinhardt, S. and Wasserman, S.S. (1979). Teaching Regression: An Exploratory Approach, The American Statistician 33(4): 196–203.

Examples

str(ex0327)

Description

As part of a study to investigate reproductive strategies in plants, biologists recorded the time spent at sources of pollen and the proportions of pollen removed by bumblebee queens and honeybee workers pollinating a species of lily.

Usage

ex0328

Format

A data frame with 47 observations on the following 3 variables.

Removed

proportion of pollen removed

Duration

duration of visit (in seconds)

Bee

factor variable with levels "Queen" and "Worker"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Harder, L.D. and Thompson, J.D. (1989). Evolutionary Options for Maximizing Pollen Dispersal of Animal-pollinated Plants, American Naturalist 133: 323–344.

Examples

str(ex0328)

Description

A randomized experiment was performed on mice to determine whether two forms of iron are retained differently. If one type is retained especially well it may be more useful as a dietary supplement for humans.

Usage

ex0331

Format

A data frame with 36 observations on the following 2 variables.

Iron

percentage of iron retained in each mouse

Supplement

factor variable with levels "Fe3" and "Fe4"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Rice, J. (1987). Mathematical Statistics and Data Analysis, Wadsworth.

Examples

str(ex0331)

Description

Tuition in dollars of 20 private and 20 public U.S. colleges and universities for 1993–1994.

Usage

ex0332

Format

A data frame with 20 observations on the following 3 variables.

Private

tuition in dollars of 20 private schools

PubIn

tuition in dollars of 20 public schools (in-state tuition)

PubOut

tuition in dollars of 20 public schools (out-of-state tuition)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

1995 U.S. News and World Report's Guide to America's Best Colleges.

Examples

str(ex0332)

Description

Relative brain weights for 51 species of mammal whose average litter size is less than 2 and for 45 species of mammal whose average litter size is greater than or equal to 2.

Usage

ex0333

Format

A data frame with 96 observations on the following 2 variables.

Brainsize

relative brain sizes (1000 * Brain weight/Body weight) for 96 species of mammals

Littersize

factor variable with levels "Small" and "Large"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Sacher, G.A. and Staffeldt, E.F. (1974). Relation of Gestation Time to Brain Weight for Placental Mammals: Implications for the Theory of Vertebrate Growth, American Naturalist 108: 593–613.

See Also

case0902

Examples

str(ex0333)

Description

Plant heights (inches) for 15 pairs of plants of the same age, one of which was grown from a seed from a cross-fertilized flower and the other of which was grown from a seed from a self-fertilized flower.

Usage

ex0428

Format

A data frame with 15 observations on the following 2 variables.

Cross

height (inches) of cross-fertilized plant

Self

height (inches) of self-fertilized plant

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Andrews, D.F. and Herzberg, A.M. (1985). Data: A Collection of Problems from many Fields for the Student and Research Worker, Springer-Verlag.

Examples

str(ex0428)

Description

Can active exercise shorten the time it takes an infant to walk alone? Twelve, one week old, male infants from white, middle-class families were randomly allocated to one of two treatment groups. Those in the active-exercise group received stimulation of the walking reflexes during four 3 minute sessions each day from the beginning of the second through the end of the eighth week. Those in the other group received no stimulation.

Usage

ex0429

Format

A data frame with 12 observations on the following 2 variables.

Age

age (months) at which infants first walked alone

Exercise

a factor with levels "Active" and "None"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Zelazo, P.R. (1972). Walking in the Newborn, Science 176: 314–315.

Examples

str(ex0429)

Description

Tolerance to sunlight (in minutes) for 13 patients prior to and after treatment with a sunscreen.

Usage

ex0430

Format

A data frame with 13 observations on the following 2 variables.

Control

tolerance to sunlight (minutes) prior to sunscreen application

Sunscreen

tolerance to sunlight (minutes) after sunscreen application

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Fusaro, R.M. and Johnson, J.A. (1974). Sunlight Protection for Erythropoietic Protoporphyria Patients, Journal of the American Medical Association 229(11): 1420.

Examples

str(ex0430)

Description

Researchers randomly assigned metastatic breast cancer patients to either a control group or a group that received weekly 90 minute sessions of group therapy and self-hypnosis, to see whether the latter treatment improved the patients' quality of life.

Usage

ex0431

Format

A data frame with 58 observations on the following 3 variables.

Survival

months of survival after beginning of study

Group

a factor with levels "Control" and "Therapy"

Censor

0 if entire lifetime observed, 1 if patient known to have lived at least 122 months

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Spiegel, D., Bloom, J.R., Kraemer, H.C. and Gottheil, E. (1989). Effect of Psychosocial Treatment on Survival of Patients with Metastatic Breast Cancer, Lancet 334(8668): 888–891.

Examples

str(ex0431)

Description

To investigate the capacity of marijuana to reduce the side effects of cancer chemotherapy, researchers performed a double-blind, randomized, crossover trial. Fifteen cancer patients on chemotherapy were randomly assigned to receive either a marijuana treatment or a placebo treatment after their first three sessions of chemotherapy. They were then crossed over to the opposite treatment for their next 3 sessions.

Usage

ex0432

Format

A data frame with 15 observations on the following 3 variables.

Subject

subject number 1–15

Marijuana

total number of vomiting and retching episodes under marijuana treatment

Placebo

total number of vomiting and retching episodes under placebo treatment

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Chang, A.E., Shiling, D.J., Stillman, R.C., Goldberg, N.H., Seipp, C.A., Barofsky, I., Simon, R.M. and Rosenberg, S.A. (1979). Delta-9-Tetrahydrocannabinol as an Antiemetic in Cancer Patients Receiving High Dose Methotrexate, Annals of Internal Medicine 91(6): 819–824.

Examples

str(ex0432)

Description

A randomized experiment was performed to estimate the effect of a certain fatty acid CPFA on the level of a certain protein in rat livers.

Usage

ex0518

Format

A data frame with 30 observations on the following 4 variables.

Protein

levels of protein (x 10) found in rat livers

Treatment

a factor with levels "Control", "CPFA50", "CPFA150", "CPFA300", "CPFA450" and "CPFA600"

Day

a factor with levels "Day1", "Day2", "Day3", "Day4" and "Day5"

Group

a factor with levels "Group1", "Group2", ..., "Group10"; the observed levels of the Treatment and Day interaction

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

Examples

str(ex0518)

Description

Data frame with measurements of oxygen isotopic composition of vertebrate bone phosphate (per mil deviations from SMOW) in 12 bones of a singe Tyrannosaurus rex specimen

Usage

ex0523

Format

A data frame with 52 observations on the following 2 variables.

Oxygen

oxygen isotopic composition

Bonegrp

a factor with levels "Bone1", "Bone2", ..., "Bone12"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Barrick, R.E. and Showers, W.J. (1994). Thermophysiology of Tyrannosaurus rex: Evidence from Oxygen Isotopes, Science 265(5169): 222–224.

See Also

ex1120

Examples

str(ex0523)

Description

Previous studies suggest that vegetarians may not receive enough zinc in their diets and the zinc requirement is especially important during pregnancy. Twenty-three women were monitored: twelve vegetarians who were pregnant, six nonvegetarians who were pregnant, and five vegetarians who were not pregnant. Is there any evidence that pregnant vegetarians tend to have lower zinc levels than pregnant nonvegetarians?

Usage

ex0524

Format

A data frame with 23 observations on the following 2 variables.

Zinc

levels of Zinc ($\mu$g/g) in the hair of women

Group

a factor with levels "PregNonVeg", "PregVeg" and "NonPregVeg"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

King, J.C., Stein, T. and Doyle, M. (1981). Effect of Vegetarianism on the Zinc Status of Pregnant Women, American Journal of Clinical Nutrition 34(6): 1049–1055.

Examples

str(ex0524)

Description

Data consist of times to fatigue failure (in units of millions of cycles) for 10 high-speed turbine engine bearings made from five different compounds.

Usage

ex0621

Format

A data frame with 50 observations on the following 2 variables.

Time

failure times of bearings (millions of cycles)

Compound

a factor with levels "I", "II", "III", "IV" and "V"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

McCool, J.I. (1979). Analysis of Single Classification Experiments Based on Censored Samples from the Two-parameter Weibull Distribution, Journal of Statistical Planning and Inference 3(1): 39–68.

Examples

str(ex0621)

Description

Is there a physiological basis for sexual preference? Researchers measured the volumes of four cell groups in the interstitial nuclei of the anterior hypothalamus in postmortem tissue from 41 subjects at autopsy from seven metropolitan hospitals in New York and California.

Usage

ex0622

Format

A data frame with 41 observations on the following 2 variables.

Volume

volumes of INAH3 (1000 $\times$ mm$^3$) cell clusters from 41 humans

Group

a factor with levels

"Group1"	heterosexual male with AIDS death
"Group2"	heterosexual male with Non-AIDS death
"Group3"	homosexual male with AIDS death
"Group4"	heterosexual female with AIDS death
"Group5"	heterosexual female with Non-AIDS death

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

LeVay, S. (1991). A Difference in Hypothalamic Structure Between Heterosexual and Homosexual Men, Science 253(5023): 1034–1037.

Examples

str(ex0622)

Description

Old Faithful Geyser in Yellowstone National Park, Wyoming, derives its name and its considerable fame from the regularity (and beauty) of its eruptions. As they do with most geysers in the park, rangers post the predicted tiems of eruptions on signs nearby and people gather beforehand to witness the show. R.A. Hutchinson, a park geologist, collected measurements of the eruption durations (X, in minutes) and the subsequent intervals before the next eruption (Y, in minutes) over an 8–day period.

Usage

ex0723

Format

A data frame with 107 observations on the following 3 variables.

Date

date of observation (August 1 to August 8, 1978)

Interval

length of interval before the next eruption (in minutes)

Duration

duration of eruption (in minutes)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Weisberg, S. (1985). Applied Linear Regression, John Wiley & Sons, New York, p. 231.

Examples

str(ex0723)

Description

As part of a study of the effects of predatory intertidal crab species on snail populations, researchers measured the mean closing forces and the propdus heights of the claws on several crabs of three species.

Usage

ex0724

Format

A data frame with 38 observations on the following 3 variables.

Force

closing strength of claw of the crab

Height

propodus height of claw of the crab

Species

species to which the crab belongs

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Yamada, S.B. and Boulding, E.G. (1992). Shell–breaking Efficiency of Predatory Crabs Influences the Distribution of an Intertidal Snail, Technical Report, Zoology Department, Oregon State University.

Examples

str(ex0724)

Description

The data are on the proportion of male birts in Denmark, The Netherlands, Canada and the United States for a number of yeras. Notice that the proportions for Canada and the United States are only provided for the years 1970 to 1990, while Denmark and The Netherlands have data listed for 1950 to 1994.

Usage

ex0726

Format

A data frame with 45 observations on the following 5 variables.

Year

year of observation

Denmark

male birth rate of Denmark for given year

Netherlands

male birth rate of The Netherlands for given year

Canada

male birth rate of Canada for given year

Usa

male birth rate of the United States for given year

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Davis, D.L., Gottlieb, M.B. and Stampnitzky, J.R. (1998). Reduced ratio of male to female births in several industrial countries, Journal of the American Medical Association 279(13): 1018–1023.

Examples

str(ex0726)

Description

These data are measured distances and recession velocities for 10 clusters of nebulae, much farther from earth than the nebulae reported in case0701.

Usage

ex0727

Format

A data frame with 10 observations on the following 2 variables.

Cluster

name of the cluster of nebulae

Distance

distance from earth (in million parsec)

Velocity

recession velocity (in kilometres per second)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Hubble, E. and Humason, M. (1931). The Velocity–Distance Relation Among Extra–calactic Nebulae, Astrophysics Journal 74: 43–50.

See Also

case0701

Examples

str(ex0727)

Description

The 1994 World Almanac reports heights and number of stories for notable tall buildings in North America. The data in this data frame are a random sample of size 60 of those for which dates of completion were available.

Usage

ex0728

Format

A data frame with 60 observations on the following 3 variables.

Year

year of completion

Height

height of building

Stories

number of stories of building

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

Examples

str(ex0728)

Description

Black wheatears are small birds in Spain and Morocco. Males of the species demonstrate an exaggerated sexual display by carrying many heavy stones to nesting cavities. This 35–gram bird transports, on average, 3.1 kg of stones per nesting season! Different males carry somewhat different sized stones, prompting a study on whether larger stones may be a signal of higher health status. Soler et al. calculated the average stone mass (g) carried by each of 21 male black wheatears, along with T-cell response measurements reflecting their immune systems' strengths.

Usage

ex0729

Format

A data frame with 21 observations on the following 2 variables.

Mass

average mass of stones carried by bird (in g)

Tcell

T-cell response measurement (in mm)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Soler, M., Martín-Vivaldi, M., Marín J. and Møller, A. (1999). Weight lifting and health status in the black wheatears, Behavioral Ecology 10(3): 281–286.

Examples

str(ex0729)

Description

Studies over the past two decades have shown that activity can effect the reorganisation of the human central nervous system. For example, it is known that the part of the brain associated with activity of a finger or limb is taken over for other purposes in individuals whose limb or finger has been lost. In one study, psychologists used magnetic source imaging (MSI) to measure neuronal activity in the brains of nine string players (six violinists, two cellists and one guitarist) and six controls who had never played a musical instrument, when the thumb and fifth finger of the left hand were exposed to mild stimulation. The researchers felt that stringed instrument players, who use the fingers of their left hand extensively, might show different behaviour—as a result of this extensive physical activity—than individuals who did not play stringed instruments.

Usage

ex0730

Format

A data frame with 15 observations on the following 2 variables.

Years

years that the individual has been playing

Activity

neuronal activity index

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Elbert, T., Pantev, C., Wienbruch, C., Rockstroh, B. and Taub E. (1995). Increased cortical representation of the fingers of the left hand in string players, Science 270(5234): 305–307.

Examples

str(ex0730)

Description

The data in case0702 are a subset of the complete data on postmortum pH in 12 steer carcasses.

Usage

ex0816

Format

A data frame with 12 observations on the following 2 variables.

Time

time after slaughter (hours)

pH

pH level in postmortem muscle

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Schwenke, J.R. and Milliken, G.A. (1991). On the Calibration Problem Extended to Nonlinear Models, Biometrics 47(2): 563–574.

See Also

case0702

Examples

str(ex0816)

Description

In a study of the effectiveness of biological control of the exotic weed tansy ragwort, researchers manipulated the exposure to the ragwort flea beetle on 15 plots that had been planted with a high density of ragwort. Harvesting the plots the next season, they measured the average dry mass of ragwort remaining (grams/plant) and the flea beetle load (beetles/gram of ragwort dry mass) to see if the ragwort plants in plots with high flea beetle loads were smaller as a result of herbivory by the beetles.

Usage

ex0817

Format

A data frame with 15 observations on the following 2 variables.

Load

flee beetle load (in beetles/gram of ragwort dry mass)

Mass

dry mass of ragwort weed

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

McEvoy, P. and Cox, C. (1991). Successful Biological Control of Ragwort, Senecio jacobaea, by introducing insects in Oregon, Ecological Applications 1(4): 430–442.

Examples

str(ex0817)

Description

One of the most dangerous contaminants deposited over European countries following the Chernobyl accident in April 1986 was radioactive cesium. To study cesium transfer from contaminated soil to plants, researchers collected soil samples and samples of mushroom mycelia from 17 wooded locations in Umbria, Central Italy, from August 1986 to November 1989. The data are measured concentrations (Bq/kg) of cesium in the soil and in the mushrooms.

Usage

ex0818

Format

A data frame with 17 observations on the following 2 variables.

Mushroom

Cesium concentrations in mushrooms (in Bq/kg)

Soil

Cesium concentrations in soil (in Bq/kg)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Borio, R., Chiocchini, S., Cicioni, R., Degli Esposti, P., Rongoni, A., Sabatini, P., Scampoli, P., Antonini, A. and Salvadori, P. (1991). Uptake of Radiocesium by Mushrooms, Science of the Total Environment 106(3): 183–190.

Examples

str(ex0818)

Description

The data are observations on the difference between Democratic and Republican vote counts, by (a) absentee ballot and (b) voting machine, for 21 elections in Philadelphia's senatorial districts over the last 10 years.

Usage

ex0820

Format

A data frame with 21 observations on the following 2 variables.

Absentee

Democratic minus Republican vote count by absentee ballot

Machines

Democratic minus Republican vote count by voting machine

Details

In a special election to fill a Pennsylvania State Senate seat in 1993, the Democrat, William Stinson, received 19,127 machine–counted votes and the Republican, Bruce Marks, received 19,691. In addition, there were 1,391 absentee ballots for Stinson and 366 absentee ballots for Marks, so that the total tally showed Stinson the winner by 461 votes. The large disparity between the machine–counted and absentee votes, and the resulting reversal of the outcome due to the absentee ballots caused some concern about possible illegal influence on the absentee votes. To see whether the discrepancy in absentee votes was larger than could be explained by chance, an econometrician considered the data given in this data frame (read from a graph in The New York Times, 11 April 1994).

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

See Also

ex1115

Examples

str(ex0820)

Description

Data are the number of butterfly species in 16 islands of forest of various sizes in otherwise cleared areas in Brazil.

Usage

ex0822

Format

A data frame with 16 observations on the following 2 variables.

Area

area (ha) of forest patch

Species

number of butterfly species

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Lovejoy, T.E., Rankin, J.M., Bierregaard, Jr., R.O., Brown, Jr., K.S., Emmons, L.H. and van der Voort, M. (1984). Ecosystem decay of Amazon forest remnants in Nitecki, M.H. (ed.) Extinctions, University of Chicago Press.

Examples

str(ex0822)

Description

The data are the average wine consumption rates (in liters per person per year) and number of ischemic heart disease deaths (per 1000 men aged 55 to 64 years) for 18 industrialized countries.

Usage

data(ex0823)

Format

A data frame with 18 observations on the following 3 variables.

Country

a character vector indicating the country

Wine

consumption of wine (liters per person per year)

Mortality

heart disease mortality rate (deaths per 1,000)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

St. Leger A.S., Cochrane, A.L. and Moore, F. (1979). Factors Associated with Cardiac Mortality in Developed Countries with Particular Reference to the Consumption of Wine, Lancet: 1017–1020.

Examples

str(ex0823)

Description

A high respiratory rate is a potential diagnostic indicator of respiratory infection in children. To judge whether a respiratory rate is “high” however, a physician must have a clear picture of the distribution of normal rates. To this end, Italian researchers measured the respiratory rates of 618 children between the ages of 15 days and 3 years.

Usage

ex0824

Format

A data frame with 618 observations on the following 2 variables.

Age

age in months of child

Rate

respiratory rate (breaths per minute)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Rusconi, F., Castagneto, M., Porta, N., Gagliardi, L., Leo, G., Pellegatta, A., Razon, S. and Braga, M. (1994). Reference Values for Respiratory Rate in the First 3 Years of Life, Pediatrics 94(3): 350–355.

Examples

str(ex0824)

Description

Data set shows the number of votes for Buchanan and Bush in all 67 counties in Florida during the U.S. presidential election of November 7, 2000.

Usage

ex0825

Format

A data frame with 67 observations on the following 3 variables.

County

a character vector indicating the county

Buchanan2000

votes cast for P. Buchanan

Bush2000

votes cast for G.W. Bush

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

See Also

ex1222

Examples

str(ex0825)

Description

In four regions of the US (Northeast, Midwest, South and West), in three different sized metropolitan regions, researchers measured indicators of pace of life.

Usage

ex0914

Format

A data frame with 36 observations on the following 4 variables.

Bank

bank clerk speed

Walk

pedestrian walking speed

Talk

postal clerk talking speed

Heart

age adjusted death rate due to heart disease

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Levine, R.V. (1990). The Pace of Life, American Scientist 78: 450–459.

Examples

str(ex0914)

Description

Data on corn yield and rainfall in six U.S. corn–producing states (Iowa, Nebraska, Illinois, Indiana, Missouri and Ohio), recorded for each year from 1890 to 1927.

Usage

ex0915

Format

Year

year of observation (1890–1927)

Yield

average corn yield for the six states (in bu/acre)

Rainfall

average rainfall in the six states (in in/year)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Ezekiel, M. and Fox, K.A. (1959). Methods of Correlation and Regression Analysis, John Wiley & Sons, New York.

Examples

str(ex0915)

Description

Researchers studied the development of a fly (Drosophila subobscura) that had been accidentally introduced from the Old World into North America around 1980.

Usage

ex0918

Format

A data frame with 21 observations on the following 8 variables.

Continent

a factor with levels "NA" and "EU"

Latitude

latitude (degrees)

Females

average wing size (10$^3\times$log mm) of female flies on log scale

SE.F

standard error of wing size (10$^3\times$log mm) of female flies on log scale

Males

average wing size (10$^3\times$log mm) of male flies on log scale

SE.M

standard error of wing size (10$^3\times$log mm) of male flies on log scale

Ratio

average basal length to wing size ratios of female flies

SE.R

standard error of average basal length to wing size ratio of female flies

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Huey, R.B., Gilchrist, G.W., Carlson, M.L., Berrigan, D. and Serra, L. (2000). Rapid Evolution of a Geographic Cline in Size in an Introduced Fly, Science 287(5451): 308–309.

Examples

str(ex0918)

Description

Data set contains the year of the Kentucky Derby, the winning horse, the condition of the track and the average speed of the winner for years 1896–2000.

Usage

ex0920

Format

A data frame with 105 observations on the following 4 variables.

Year

year of Kentucky Derby

Winner

a character vector with the name of the winning horse

Condition

a factor with levels "fast", "good" and "slow"

Speed

average speed of the winner (feet per second)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

https://www.kentuckyderby.com/

Examples

str(ex0920)

Description

Researchers randomly allocated 25 beakers containing minnow larvae to receive one of 25 treatment combinations of 5 levels of zinc and 5 levels of copper.

Usage

ex1014

Format

A data frame with 25 observations on the following 3 variables.

Copper

amount of copper received (in ppm)

Zinc

amount of zinc received (in ppm)

Protein

protein in minnow larvae exposed to copper and zinc ($\mu$g/larva)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Ryan, D.A., Hubert, J.J., Carter, E.M., Sprague, J.B. and Parrott, J. (1992). A Reduced-Rank Multivariate Regression Approach to Aquatic Joint Toxicity Experiments, Biometrics 48(1): 155–162.

Examples

str(ex1014)

Description

Depletion of the ozone layer allows the most damaging ultraviolet radiation to reach the Earth's surface. To measure the relationship, researchers sampled the ocean column at various depths at 17 locations around Antarctica during the austral spring of 1990.

Usage

ex1026

Format

A data frame with 17 observations on the following 3 variables.

Inhibit

percent inhibition of primary phytoplankton production in water

UVB

UVB exposure

Surface

a factor with levels "Deep" and "Surface"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Smith, R.C., Prézelin, B.B., Baker, K.S., Bidigare, R.R., Boucher, N.P., Coley, T., Karentz, D., MacIntyre, S., Matlick, H.A., Menzies, D., Ondrusek, M., Wan, Z. and Waters, K.J. (1992). Ozone Depletion: Ultraviolet Radiation and Phytoplankton Biology in Antarctic Waters, Science 255(5047): 952–959.

Examples

str(ex1026)

Description

Data are measurements on breeding pairs of land-bird species collected from 16 islands around Britain over the course of several decades. For each species, the data set contains an average time of extinction on those islands where it appeared, the average number of nesting pairs, the size of the species and the migratory status of the species.

Usage

ex1027

Format

A data frame with 62 observations on the following 5 variables.

Species

a character vector indicating the species

Time

average extinction time in years

Pairs

average number of nesting pairs

Size

a factor with levels "L" and "S"

Status

a factor with levels "M" and "R"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Pimm, S.L., Jones, H.L., and Diamond, J. (1988). On the Risk of Extinction, American Naturalist 132(6): 757–785.

Examples

str(ex1027)

Description

Data set with the numbers of Atlantic Basin tropical storms and hurricanes for each year from 1950–1997. The variable storm index is an index of overall intensity of hurricane season. Also listed are whether the year was a cold, warm or neutral El Nino year and a variable indicating whether West Africa was wet or dry that year.

Usage

ex1028

Format

A data frame with 48 observations on the following 7 variables.

Year

year

ElNino

a factor with levels "cold", "neutral" and "warm"

Temperature

numeric variable with values -1 if ElNino is "cold", 0 if "neutral" and 1 if "warm"

WestAfrica

numeric variable indicating whether West Africa was wet (1) or dry (0)

Storms

number of storms

Hurricanes

number of hurricanes

StormIndex

index of overall intensity of hurricane season

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Data were gathered by William Gray of Colorado State University and reported on USA Today weather page: http://www.usatoday.com/weather/whurnum.htm

Examples

str(ex1028)

Description

Data set contains weekly wages in 1987 for a sample of 25,632 males between the age of 18 and 70 who worked full-time along with their years of education, years of experience, indicator variable for whether they were black, indicator variable for whether they worked in or near a city, and a code for the region in the US where they worked.

Usage

ex1029

Format

A data frame with 25631 observations on the following 6 variables.

Wage

weekly wage in dollars

Education

education in years

Experience

experience in years

Black

a factor with levels "Yes" and "No"; indicator for whether the person is black

SMSA

a factor with levels "Yes" and "No"; indicator for whether the person worked in or near a city

Region

a factor with levels "MW", "NE", "S" and "W"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Bierens, H.J. and Ginther, D.K. (2001). Integrated Conditional Moment Testing of Quantile Regression Models, Empirical Economics 26(1): 307–324

http://econ.la.psu.edu/~hbierens/QUANTILE.PDF

http://econ.la.psu.edu/~hbierens/MEDIAN.HTM

Examples

str(ex1029)

Description

The data are observations on the difference between Democratic and Republican vote counts, by (a) absentee ballot and (b) voting machine, for 22 elections in Philadelphia's senatorial districts over the last 10 years.

Usage

ex1115

Format

A data frame with 22 observations on the following 2 variables.

Absentee

Democratic minus Republican vote count by absentee ballot

Machines

Democratic minus Republican vote count by voting machine

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

See Also

ex0820

Examples

str(ex1115)

Description

Data are the isotopic composition of structural bone carbonate ($X$) and the isotopic composition of the coexisting calcite cements ($Y$) in 18 bone samples from a specimen of the dinosaur Tyrannosaurus rex. Evidence that the mean of $Y$ is positively associated with $X$ was used in an argument that the metabolic rate of this dinosaur resembled warm-blooded more than cold-blooded animals.

Usage

ex1120

Format

A data frame with 18 observations on the following 2 variables.

Carbonat

isotopic composition of bone carbonate

Calcite

isotopic composition of calcite cements

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Barrick, R.E. and Showers, W.J. (1994). Thermophysiology of Tyrannosaurus rex: Evidence from Oxygen Isotopes, Science 265(5169): 222–224.

See Also

ex0523

Examples

str(ex1120)

Description

It has been theorized that developing countries cut down their forests to pay off foreign debt. Data are debt, deforestation, and population from 11 Latin American nations.

Usage

ex1122

Format

A data frame with 11 observations on the following 4 variables.

Country

a character vector indicating the country

Debt

debt (millions of dollars)

Deforest

deforestation (thousands of ha)

Pop

population (thousands of people)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Gullison, R.R. and Losos, E.C. (1992). The Role of Foreign Debt in Deforestation in Latin America, Conservation Biology 7(1): 140–7.

Examples

str(ex1122)

Description

Does pollution kill people? Data in one early study designed to explore this issue from 5 Standard Metropolitan Statistical Areas in the U.S between 1959–1961.

Usage

ex1123

Format

A data frame with 60 observations on the following 7 variables.

City

a character vector indicating the city

Mort

total age-adjusted mortality from all causes

Precip

mean annual precipitation (inches)

Educ

median number of school years completed for persons 25 years or older

Nonwhite

percentage of population that is nonwhite

NOx

relative pollution potential of oxides of nitrogen

SO2

relative pollution potential of sulfur dioxide

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

McDonald, G.C. and Ayers, J.A. (1978). Some Applications of the “Chernoff Faces”: A Technique for Graphically Representing Multivariate Data in Wang, P.C.C. (ed.) Graphical Representation of Multivariate Data, Academic Press.

See Also

ex1217

Examples

str(ex1123)

Description

An assessment of the factors affecting dispersal distances is important for understanding population spread, recolonization and gene flow which are central issues for conservation of many vertebrate species. Researchers gathered data on body weight, diet type and maximum natal dispersal distance for various animals.

Usage

ex1124

Format

A data frame with 64 observations on the following 4 variables.

Species

a character vector indicating the species

Bodymass

bodymass (kg)

Maxdist

maximum dispersal distance (km)

Type

a factor with levels "Carnivore", "Herbivore" and "Omnivore"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Sutherland, G.D., Harestad, A.S., Price, K. and Lertzman, K.P. (2000). Scaling of Natal Dispersal Distances in Terrestrial Birds and Mammals, Conservation Ecology 4(1): 16.

Examples

str(ex1124)

Description

Complete data set for problem introduced in ex1123. Data from early study designed to explore the relationship between air pollution and mortality.

Usage

ex1217

Format

A data frame with 60 observations on the following 17 variables.

City

a character vector indicating the city

Mort

total age-adjusted mortality from all causes

Precip

mean annual precipitation (inches)

Humidity

percent relative humidity (annual average at 1:00pm)

Jantemp

mean January temperature (degrees F)

Julytemp

mean July temperature (degrees F)

Over65

percentage of the population aged 65 years or over

House

population per household

Educ

median number of school years completed for persons 25 years or older

Sound

percentage of the housing that is sound with all facilities

Density

population density (in persons per square mile of urbanized area)

Nonwhite

percentage of population that is nonwhite

Whitecol

percentage of employment in white collar occupations

Poor

percentage of households with annual income under $\$$3,000 in 1960

HC

relative pollution potential of hydrocarbons

NOx

relative pollution potential of oxides of nitrogen

SO2

relative pollution potential of sulfur dioxide

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

McDonald, G.C. and Ayers, J.A. (1978). Some Applications of the “Chernoff Faces”: A Technique for Graphically Representing Multivariate Data in Wang, P.C.C. (ed.) Graphical Representation of Multivariate Data, Academic Press.

See Also

ex1123

Examples

str(ex1217)

Description

The number of species on an island is known to be related to the island's area. Of interest is what other variables are also related to the number of species, after island area is accounted for, and whether the answer differs for native and non native species.

Usage

ex1220

Format

A data frame with 30 observations on the following 8 variables.

Island

a character vector indicating the island

Total

total number of observed species

Native

number of native species

Area

area (km$^2$)

Elev

elevation (m)

DistNear

distance from nearest island (km)

DistSC

distance from Santa Cruz (km)

AreaNear

area of nearest island (km$^2$)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Johnson, M.P. and Raven, P.H. (1973). Species Number and Endemism: The Galapagos Archipelago Revisited, Science 179(4076): 893–895.

Examples

str(ex1220)

Description

The rise in abundance of algae in coastal waters is thought to be due to increases in nutrients such as nitrate and other forms of nitrogen. Researchers gathered data to gauge the evidence that nitrates in the discharges of rivers around the world are associated with human population density.

Usage

ex1221

Format

A data frame with 42 observations on the following 11 variables.

River

a character vector indicating the river

Country

a factor variable with 26 levels

Discharge

the estimated annual average discharge of the river into an ocean (m$^3$ per second)

Runoff

estimated annual average runoff from the watershed (liters/(sec$\times$ km$^2$))

Area

watershed area (km$^2$)

Density

density of people (people/km$^2$)

NO3

nitrate concentration ($\mu$M/l)

Export

nitrate export (product of runoff times nitrate concentration)

Dep

deposition (proportional to product of nitratrate precipitation times precipitation)

NPrec

nitrate precipitation ($\mu$mol NO$_3$/(sec$\times$km$^2$))

Prec

precipitation (cm/year)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Cole, J.L., Peierls, B.L., Caraco, N.F. and Pace, M.L. (1993). Nitrogen Loading of Rivers as a Human-driven Process, in McDonnell, M.J. and Pickett, S.T.A. (eds.) Humans as Components of Ecosystems: The Ecology of Subtle Human Effects and Populated Areas, Springer-Verlag.

Examples

str(ex1221)

Description

This data set contains the vote counts by county in Florida for Buchanan and for four other presidential candidates in 2000, along with the total vote counts in 2000, the presidential vote counts for three presidential candidates in 1996, the vote count for Buchanan in his only other campaign in Florida—the 1996 Republican primary, the registration in Buchanan's Reform party and the total political party registration in the county.

Usage

ex1222

Format

A data frame with 67 observations on the following 13 variables.

County

a character vector indicating the county

Buchanan2000

votes cast for Buchanan in 2000 presidential election

Gore2000

votes cast for Gore in 2000 presidential election

Bush2000

votes cast for Bush in 2000 presidential election

Nader2000

votes cast for Nader in 2000 presidential election

Browne2000

votes cast for Browne in 2000 presidential election

Total2000

total vostes cast in 2000 presidential election

Clinton96

votes cast for Clinton in 1996 presidential election

Dole96

votes cast for Dole in 1996 presidential election

Perot96

votes cast for Perot in 1996 presidential election

Buchanan96p

votes cast for Buchanan in 1996 Republican primary

ReformReg

the registration in Buchanan's Reform party

TotalReg

the total political party registration

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

See Also

ex0825

Examples

str(ex1222)

Description

About 65 million years ago, the dinosaurs suffered a mass extinction virtually overnight (in geologic time). Among many clues, one that all scientists regard as crucial is a layer of iridium-rich dust that was deposited over much of the earth at that time. The theory is that an event like a volcanic eruption or meteor impact caused a massive dust cloud that blanketed the earth for years killing off animals and their food sources. Dataset has Iridium depths by type of deposit.

Usage

ex1317

Format

A data frame with 28 observations on the following 3 variables.

Iridium

Iridium in samples (ppt)

Strata

a factor with levels "Limestone" and "Shale"

Depth

a factor with six levels: "1", "2", ..., "6"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Alvarez, W. and Asaro, F. (1990). What Caused the Mass Extinction? An Extraterrestrial Impact, Scientific American 263(4): 76–84.

Courtillot, E. (1990). What Caused the Mass Extinction? A Volcanic Eruption. Scientific American 263(4): 85–92.

Examples

str(ex1317)

Description

A 1989 study investigated the effect of heredity and environment on intelligence. Data are the IQ scores for adopted children whose biological and adoptive parents were categorized either in the highest or the lowest socioeconomic status category.

Usage

ex1319

Format

A data frame with 38 observations on the following 3 variables.

IQ

IQ scores of adopted children

Adoptive

a factor with levels "High" and "Low"; the socioeconomic status of the adoptive parents

Biologic

a factor with levels "High" and "Low"; the socioeconomic status of the biological parents

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Capron, C. and Duyme, M. (1991). Children's IQ's and SES of Biological and Adoptive Parents in a Balanced Cross-fostering Study, European Bulletin of Cognitive Psychology 11(3): 323–348.

See Also

ex1605

Examples

str(ex1319)

Description

Data set on 861 ACT Assessment Mathematics Usage Test scores from 1987. The test was given to a sample of high school seniors who met one of three profiles of high school mathematics course work: (a) Algebra I only; (b) two Algebra courses and Geometry; and (c) two Algebra courses, Geometry, Trigonometry, Advanced Mathematics and Beginning Calculus.

These data were generated from summary statistics for one particular form of the test as reported by Doolittle (1989).

Usage

ex1320

Format

A data frame with 861 observations on the following 3 variables.

Sex

a factor with levels "female" and "male"

Background

a factor with levels "a", "b" and "c"

Score

ACT mathematics test score

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Doolittle, A.E. (1989). Gender Differences in Performance on Mathematics Achievement Items, Applied Measurement in Education 2(2): 161–177.

Examples

str(ex1320)

Description

Researchers designed an experiment to investigate how delivery of brain cancer antibody is influenced by tumor size, antibody molecular weight, blood-brain barrier disruption, and delivery route.

Usage

ex1414

Format

A data frame with 36 observations on the following 6 variables.

Agent

a factor with levels "AIB", "DEX7" and "MTX"

Treatment

a factor with levels "BD" and "NS"

Route

a factor with levels "IA" and "IV"

Days

days after inoculation

BAT

concentration of antibody in the part of the brain around the tumor

LH

concentration of antibody in the unaffected part of the brain

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Barnett, P.A., Roman-Goldstain, S., Ramsey, F., McCormick, C.I., Sexton, G., Szumowski, J. and Neuwelt, E.A. (1995). Differential Permeability and Quantitative MR Imaging of a Human Lung Carcinoma Brain Xenograft in the Nude Rat, American Journal of Pathology 146(2): 436–449.

See Also

ex1415

Examples

str(ex1414)

Description

Researchers designed an experiment to investigate how delivery of brain cancer antibody is influenced by tumor size, antibody molecular weight, blood-brain barrier disruption, and delivery route. The data for the first replicate of this study is in ex1414. This is the second replicate for the study.

Usage

ex1415

Format

A data frame with 36 observations on the following 6 variables.

Agent

a factor with levels "AIB", "DEX7" and "MTX"

Treatment

a factor with levels "BD" and "NS"

Route

a factor with levels "IA" and "IV"

Days

days after inoculation

BAT

concentration of antibody in the part of the brain around the tumor

LH

concentration of antibody in the unaffected part of the brain

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Barnett, P.A., Roman-Goldstain, S., Ramsey, F., McCormick, C.I., Sexton, G., Szumowski, J. and Neuwelt, E.A. (1995). Differential Permeability and Quantitative MR Imaging of a Human Lung Carcinoma Brain Xenograft in the Nude Rat, American Journal of Pathology 146(2): 436–449.

See Also

ex1414

Examples

str(ex1415)

Description

Corn yield trials were performed at four locations in Tennessee in 1999. Data shows the average yields for six hybrids at each of four locations.

Usage

ex1417

Format

A data frame with 30 observations on the following 3 variables.

Location

a factor with five levels: "Ames.irr", "Ames.un", "Crossvill", "Knoxville" and "Milan"

Hybrid

a factor with six levels: "AsgrowRX799", "Beck5912W", "Cargill7821", "FFR739W", "NorthrupKing" and "Pioneer"

Yield

average yield (bushels per acre)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

University of Tennessee Agricultural Experiment Station.

Examples

str(ex1417)

Description

Time series data set of annual counts of sunspots.

Usage

ex1509

Format

A data frame with 200 observations on the following 2 variables.

Year

year

Spots

number of sunspots

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Waldmeier, M. (1961). The Sunspot Activity in the Years 1610–1960, Federal Observatory, Zurich.

Examples

str(ex1509)

Description

Several factors suggest that the incidence of melanoma is related to solar radiation. Data has the age-adjusted melanoma incidence among males from Connecticut Tumor Registry, 1936–1972.

Usage

ex1512

Format

A data frame with 37 observations on the following 3 variables.

Year

year

Melanoma

male melanoma incidence in number of cases per 100,000 population

Sunspot

sunspot relative number

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Houghton, A., Munster, E.W. and Viola, M.V. (1978). Increased Incidence of Malignant Melanoma After Peaks of Sunspot Activity, Lancet: 759–760.

Examples

str(ex1512)

Description

Data on the annual numbers of lynx trapped in the Mackenzie River district of northwest Canada from 1821–1934.

Usage

ex1513

Format

A data frame with 114 observations on the following 3 variables.

Year

year

Lynx

number of lynx trapped

Spots

number of sunspots

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Elston, C. and Nicholson, M. (1942). The Ten Year Cycle in Numbers of the Lynx in Canada, Journal of Animal Ecology 11(2): 215–244.

Examples

str(ex1513)

Description

Data shows the number of deaths due to firearms and the number of deaths due to motor vehicle accidents in the United States between 1968 and 1993.

Usage

ex1514

Format

A data frame with 26 observations on the following 3 variables.

Year

year

FirearmDeaths

deaths due to firearms (in thousands per year)

MotorVehicleDeaths

deaths due to motor vehicles (in thousands per year)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Data read from a Centers for Disease Control and Prevention graph reported in The Oregonian, June 17, 1997.

Examples

str(ex1514)

Description

Data on the value of a $1 U.S. stock investment in 1871 at the end of each year, based on the Standard and Poor (S&P) 500 Composite stock index.

Usage

ex1515

Format

A data frame with 129 observations on the following 2 variables.

Year

year

SPReturn

S&P composite stock index ($)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

Examples

str(ex1515)

Description

Data are a subset from an observational, longitudinal, study on adopted children. Is child's intelligence related to intelligence of the biological mother and the intelligence of the adoptive mother?

Usage

ex1605

Format

A data frame with 62 observations on the following 6 variables.

AMED

adoptive mother's years of education

BMIQ

biological mother's score on IQ test

Age2IQ

IQ of child at age 2

Age4IQ

IQ of child at age 4

Age8IQ

IQ of child at age 8

Age13IQ

IQ of child at age 13

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Skodak, M. and Skeels, H.M. (1949). A Final Follow-up Study of One Hundred Adopted Children, Journal of Genetic Psychology 75: 85–125.

See Also

ex1319

Examples

str(ex1605)

Description

Adam Smith, in Wealth of Nations, observed that even religious monopolies become weak when they are not challenged by competition. Data to illustrate this point is from 21 countries in which the percentages of Catholics in the populations varied from a low 1.2% to a high 97.6%.

Usage

ex1611

Format

A data frame with 21 observations on the following 4 variables.

Country

a character vector indicating the country

PctCath

percent Catholics in the population

P2PRatio

priest to parishioner ratio

PctIndig

percent clergy indigenous

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Gill, A.J. (1994). Rendering unto Caesar? Religious Competition and Catholic Political Strategy in Latin America, 1962–79, American Journal of Political Science 38(2): 403–425.

Examples

str(ex1611)

Description

Samples of effluent were divided and sent to two laboratories for testing. Data are measurements of biochemical oxygen demand and suspended solid measurements obtained for 2 sample splits from the two laboratories.

Usage

ex1612

Format

A data frame with 11 observations on the following 4 variables.

ComBOD

biochemical oxygen demand measurements from commercial laboratory

ComSS

suspended solids measurements from commercial laboratory

StaBOD

biochemical oxygen demand measurements from state laboratory

StaSS

suspended solids measurements from state laboratory

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Johnson, R.A. and Wichern, D.W. (1988). Applied Multivariate Statistical Analysis, Prentice-Hall.

Examples

str(ex1612)

Description

Data are the measurements from two very similar species of flea beetle.

Usage

ex1613

Format

A data frame with 36 observations on the following 3 variables.

Jnt1

measurement of first joint in micrometers

Jnt2

measurement of second joint in micrometers

Species

a factor with levels "conc" and "heik"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Lubischew, A.A. (1962). On the Use of Discriminant Functions in Taxonomy, Biometrics 18: 455–477.

Examples

str(ex1613)

Description

Recent studies in the field of psychoimmunology suggest a link exists between behavioral events and the functioning of one's immune system. Data shows the results of a study on 12 subjects who were monitored during three distinct activities. The first activity consisted of neutral activity such as reporting tasks. During the second activity, subjects listened to audiotape exercises relating to images of heaviness, warmth in the body, relaxation, suggestions to remember happy events, etc. The third activity included a nonaudio tape follow up stimulus consisting of continued relaxation as in activity 2 and a verbal discussion of the positive aspects of the audiotape.

Usage

ex1614

Format

A data frame with 12 observations on the following 3 variables.

PhaseA

Interleukin-1 levels (counts per minute) from blood samples taken during activity A

PhaseB

Interleukin-1 levels (counts per minute) from blood samples taken during activity B

PhaseC

Interleukin-1 levels (counts per minute) from blood samples taken during activity C

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Keppel, W. (1993). Effects of Behavioral Stimuli on Plasma Interleukin-1 Activity in Humans at Rest, Journal of Clinical Psychology 49(6): 777–785.

Examples

str(ex1614)

Description

Data shows a partial listing of a data set with ratios of average math to average verbal SAT scores in the United States and the District of Columbia for 1989 and 1996–1999.

Usage

ex1615

Format

A data frame with 51 observations on the following 6 variables.

State

a character vector indicating the state

M/V:89

average MATH SAT scores divided by average VERBAL SAT score in 1989

M/V:96

average MATH SAT scores divided by average VERBAL SAT score in 1996

M/V:97

average MATH SAT scores divided by average VERBAL SAT score in 1997

M/V:98

average MATH SAT scores divided by average VERBAL SAT score in 1998

M/V:99

average MATH SAT scores divided by average VERBAL SAT score in 1999

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

Examples

str(ex1615)

Description

Actual pig fat and measurements of pig fat from magnetic resonance images at 13 locations for 12 pigs.

Usage

ex1708

Format

A data frame with 12 observations on the following 14 variables.

Fat

actual pig fat (in percent)

M1

magnetic resonance image at location 1

M2

magnetic resonance image at location 2

M3

magnetic resonance image at location 3

M4

magnetic resonance image at location 4

M5

magnetic resonance image at location 5

M6

magnetic resonance image at location 6

M7

magnetic resonance image at location 7

M8

magnetic resonance image at location 8

M9

magnetic resonance image at location 9

M10

magnetic resonance image at location 10

M11

magnetic resonance image at location 11

M12

magnetic resonance image at location 12

M13

magnetic resonance image at location 13

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Glasbey, C.A and Flowler, P.A. (1992). Regression Models Fitted Using Conditional Independence to Estimate Pig Fatness from Magnetic Resonance Images, The Statistician 41(2): 179–184.

Examples

str(ex1708)

Description

Data show measures that differ among denominations of American Protestant and Catholic churches.

Usage

ex1713

Format

A data frame with 18 observations on the following 6 variables.

Denomination

a character vector indicating the church denomination

Distinct

distinctiveness (strictness of discipline on a seven point scale)

Attend

average percentage of weeks that individuals attended a church meeting (% weekly)

NonChurch

average number of secular organisations to which members belong

StrongPct

average percentage of members that describe themselves as being strong church members (%)

AnnInc

average income of members (US$\$$)

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Iannaccone, L.R. (1994). Why Strict Churches Are Strong, American Journal of Sociology 99(5): 1180–1211.

Examples

str(ex1713)

Description

In the 1970's the U.S. Commission on Civil Rights investigated charges that insurance companies were attempting to redefine Chicago “neighborhoods” in order to cancel existing homeowner insurance policies or refuse to issue new ones. Dataset has data on homeowner and residential fire insurance policy issuances from 47 zip codes in the Chicago area.

Usage

ex1714

Format

A data frame with 47 observations on the following 8 variables.

Zip

last 2 digits of zip code

Fire

fires per 1000 housing units

Theft

thefts per 1000 population

Age

percentage of housing units built prior to 1940

Income

median family income

Race

percentage minority

Vol

number of new policies per 100 housing units

Invol

number of FAIR plan policies and renewals per 100 housing units

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Andrews, D.F. and Herzberg, A.M. (1985). Data: A Collection of Problems from many Fields for the Student and Research Worker, Springer-Verlag.

Examples

str(ex1714)

Description

Survival times for two groups of lymphoma patients.

Usage

ex1914

Format

A data frame with 34 observations on the following 4 variables.

Months

months after diagnosis

Group

a factor with levels "no" and "radiation"

Survived

number of patients known to survive beyond this month

Died

number of patients known to die after this many months

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Neuwelt, E.A., Goldman, D.L., Dahlborg, S.A., Crossen, J., Ramsey, F., Roman-Goldstein, S., Braziel, R. and Dana, B. (1991). Primary CNS Lymphoma Treated with Osmotic Blood-brain Barrier Disruption: Prolonged Survival and Preservation of Cognitive Function, Journal of Clinical Oncology 9(9): 1580–1590.

Examples

str(ex1914)

Description

Fictitious data set based on results of an experiment where subjects were randomly divided into two groups and given a placebo or vitamin c to take during the cold season. At the end of the cold season, the subjects were interviewed by a physician who determined whether they had or had not suffered a cold during the period. Skeptics interviewed the 800 subjects to determine who knew and who did not know to which group they had been assigned. Vitamin C has a bitter taste and those familiar with it could recognize whether their pills contained it.

Usage

ex1916

Format

A data frame with 4 observations on the following 4 variables.

Knew

a factor with levels "no" and "yes"

Treatment

a factor with levels "placebo" and "vitC"

Cold

number of people who got a cold

NoCold

number of people who did not get a cold

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

Examples

str(ex1916)

Description

Dataset from a study which investigated the added risk of breast cancer due to alcohol consumption. A sample of confirmed breast cancer patients were compared with a sample of cancer free women who were close in age and from the same neighborhood as the cases. Data was collected on the alcohol consumption and body mass of both sets of women.

Usage

ex1917

Format

A data frame with 6 observations on the following 4 variables.

Bodymass

a factor with levels "high", "low" and "medium"

Drinking

a factor with levels "high" and "low"

Cases

number of women with breast cancer

Controls

number of women without breast cancer

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Rosenberg, L., Palmer, J.R., Miller, D.R., Clarke, E.A. and Shapiro, S. (1990). A Case-Control Study of Alcoholic Beverage Consumption and Breast Cancer, American Journal of Epidemiology 131(1): 6–14.

Examples

str(ex1917)

Description

In 1846 the Donner party became stranded while crossing the Sierra Nevada Mountains near Lake Tahoe. The data frame has the counts for male and female survivors for six age groups.

Usage

ex1918

Format

A data frame with 12 observations on the following 4 variables.

Age

a factor with six levels: "15-19", "20-29", "30-39", "40-49", "50-59" and "60-69"

Sex

a factor with levels "female" and "male"

Lived

number that lived

Died

number that died

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Grayson, D.K. (1990). Donner Party Deaths: A Demographic Assessment, Journal of Anthropological Research 46: 223–242.

See Also

case2001

Examples

str(ex1918)

Description

Data shows the numbers of compact sports utility vehicles involved in fatal accidents in the U.S. between 1995 and 1999, categorized according to travel speed, make of car (Ford or other), and cause of accident (tire-related or other).

Usage

ex1919

Format

A data frame with 8 observations on the following 4 variables.

Speed

a factor with levels "0-40", "41-55", "56-65" and ">65"

Make

a factor with levels "Ford" and "Other"

Other

cause of accident was other than tire-related

Tire

cause of accident was tire-related

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

See Also

ex2018

Examples

str(ex1919)

Description

This data frame contains the launch temperatures (degrees Fahrenheit) and an indicator of O-ring failures for 24 space shuttle launches prior to the space shuttle Challenger disaster of January 28, 1986.

Usage

ex2011

Format

A data frame with 24 observations on the following 2 variables.

Temp

Launch temperature (in degrees Fahrenheit)

Failure

Indicator of O-ring failure

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

See Also

case0401, ex2223

Examples

str(ex2011)

Description

Duchenne Muscular Dystrophy (DMD) is a genetically transmitted disease, passed from a mother to her children. Boys with the disease usually die at a young age; but affected girls usually do not suffer symptoms, may unknowingly carry the disease and may pass it to their offspring. It is believed that about 1 in 3,300 women are DMD carriers. A woman might suspect she is a carrier when a related male child develops the disease. Doctors must rely on some kind of test to detect the presence of the disease. This data frame contains data on two enzymes in the blood, creatine kinase (CK) and hemopexin (H) for 38 known DMD carriers and 82 women who are not carriers. It is desired to use these data to obtain an equation for indicating whether a women is a likely carrier.

Usage

ex2012

Format

A data frame with 120 observations on the following 3 variables.

Group

Indicator whether the woman has DMD ("Case") or not ("Control")

CK

Creatine kinase reading

H

Hemopexin reading

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Andrews, D.F. and Herzberg, A.M. (1985). Data: A Collection of Problems From Many Fields For The Student And Research Worker, Springer-Verlag, New York.

Examples

str(ex2012)

Description

A study examined the association between nesting locations of the Northern Spotted Owl and availability of mature forests. Wildlife biologists identified 30 nest sites. The researchers selected 30 other sites at random coordinates in the same forest. On the basis of aerial photographs, the percentage of mature forest (older than 80 years) was measured in various rings around each of the 60 sites.

Usage

ex2015

Format

A data frame with 60 observations on the following 8 variables.

Site

Site, a factor with levels "Random" and "Nest"

PctRing1

Percentage of mature forest in ring with outer radius 0.91 km

PctRing2

Percentage of mature forest in ring with outer radius 1.18 km

PctRing3

Percentage of mature forest in ring with outer radius 1.40 km

PctRing4

Percentage of mature forest in ring with outer radius 1.60 km

PctRing5

Percentage of mature forest in ring with outer radius 1.77 km

PctRing6

Percentage of mature forest in ring with outer radius 2.41 km

PctRing7

Percentage of mature forest in ring with outer radius 3.38 km

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Ripple W.J., Johnson, D.H., Thershey, K.T. and Meslow E.C. (1991). Old–growth and Mature Forests Near Spotted Owl Nests in Western Oregon, Journal of Wildlife Management 55(2): 316–318.

Examples

str(ex2015)

Description

Hermon Bumpus analysed various characteristics of some house sparrows that were found on the ground after a severe winter storm in 1898. Some of the sparrows survived and some perished. This data set contains the survival status, age, the length from tip of beak to tip of tail (in mm), the alar extent (length from tip to tip of the extended wings, in mm), the weight in grams, the length of the head in mm, the length of the humerus (arm bone, in inches), the length of the femur (thigh bones, in inches), the length of the tibio–tarsus (leg bone, in inches), the breadth of the skull in inches and the length of the sternum in inches.

Usage

ex2016