scor {bootstrap} | R Documentation |

## Open/Closed Book Examination Data

### Description

This is data form mardia, Kent and Bibby on 88 students who took
examinations in 5 subjects. Some where with open book and other with
closed book.

### Usage

data(scor)

### Format

A data frame with 88 observations on the following 5 variables.

- mec
mechanics, closed book note

- vec
vectors, closed book note

- alg
algebra, open book note

- ana
analysis, open book note

- sta
statistics, open book note

### Details

The book uses this for bootstrap in principal component analysis.

### Source

Efron, B. and Tibshirani, R. (1993) An Introduction to the Bootstrap.
Chapman and Hall, New York, London.

### Examples

str(scor)
if(interactive())par(ask=TRUE)
plot(scor)
# The parameter of interest (theta) is the fraction of variance explained
# by the first principal component.
# For principal components analysis svd is better numerically than
# eigen-decomposistion, but for bootstrapping the latter is _much_ faster.
theta <- function(ind) {
vals <- eigen(var(scor[ind,]), symmetric=TRUE, only.values=TRUE)$values
vals[1] / sum(vals) }
scor.boot <- bootstrap(1:88, 500, theta)
sd(scor.boot$thetastar) # bootstrap standard error
hist(scor.boot$thetastar)
abline(v=theta(1:88), col="red2")
abline(v=mean(scor.boot$thetastar), col="blue")

[Package

*bootstrap* version 2019.6

Index]