Efron and Tibshirani discuss the scor (bootstrap) test score data on 88 students who took examinations in five subjects
Posted: Mon May 09, 2022 12:01 pm
Efron and Tibshirani discuss the scor (bootstrap) test score
data
on 88 students who took examinations in five subjects $[91, Table
7.1]$,
$[194, Table 1.2.1]$. The first two tests (mechanics, vectors) were
closed
book and the last three tests (algebra, analysis, statistics) were
open
book. Each row of the data frame is a set of scores $(xi1, . . . ,
xi5)$ for
the $ith$ student. Use a panel display to display the scatter plots
for
each pair of test scores. Compare the plot with the sample
correlation
matrix. Obtain bootstrap estimates of the standard errors for each
of the
following estimates: $ρˆ12 = ˆρ(mec, vec), ρˆ34 = ˆρ(alg,
ana)$,
$ρˆ35 = ˆρ(alg,sta), ρˆ45 = ˆρ(ana, sta)$.
data
on 88 students who took examinations in five subjects $[91, Table
7.1]$,
$[194, Table 1.2.1]$. The first two tests (mechanics, vectors) were
closed
book and the last three tests (algebra, analysis, statistics) were
open
book. Each row of the data frame is a set of scores $(xi1, . . . ,
xi5)$ for
the $ith$ student. Use a panel display to display the scatter plots
for
each pair of test scores. Compare the plot with the sample
correlation
matrix. Obtain bootstrap estimates of the standard errors for each
of the
following estimates: $ρˆ12 = ˆρ(mec, vec), ρˆ34 = ˆρ(alg,
ana)$,
$ρˆ35 = ˆρ(alg,sta), ρˆ45 = ˆρ(ana, sta)$.