This package contains data sets and some utility functions to support Foundations and Applications of Statistics: An Introduction Using R by Randall Pruim.
The package can be installed from CRAN via
install.packages("fastR")or from github
devtools::install_github("rpruim/fastR")In addtion to data sets, fastR contains a snippet() function that loads and executes code found in the text. Here is an example:
require(fastR)
require(multcomp)
snippet("bugs")
#>
#>
#> snippet(bugs)
#> ------- ~~~~
#>
#> > model <- aov(sqrt(NumTrap)~Color,bugs)
#>
#> > TukeyHSD(model)
#> Tukey multiple comparisons of means
#> 95% family-wise confidence level
#>
#> Fit: aov(formula = sqrt(NumTrap) ~ Color, data = bugs)
#>
#> $Color
#> diff lwr upr p adj
#> G-B 1.750330 0.6458303 2.8548288 0.0013396
#> W-B 0.146892 -0.9576072 1.2513913 0.9818933
#> Y-B 3.060201 1.9557018 4.1647003 0.0000011
#> W-G -1.603438 -2.7079368 -0.4989383 0.0031308
#> Y-G 1.309872 0.2053723 2.4143708 0.0165743
#> Y-W 2.913309 1.8088098 4.0178083 0.0000022
#>
#>
#> > model <- lm(sqrt(NumTrap)~Color,bugs)
#>
#> > summary(glht(model,mcp(Color="Tukey")))
#>
#> Simultaneous Tests for General Linear Hypotheses
#>
#> Multiple Comparisons of Means: Tukey Contrasts
#>
#>
#> Fit: lm(formula = sqrt(NumTrap) ~ Color, data = bugs)
#>
#> Linear Hypotheses:
#> Estimate Std. Error t value Pr(>|t|)
#> G - B == 0 1.7503 0.3946 4.436 0.00136 **
#> W - B == 0 0.1469 0.3946 0.372 0.98189
#> Y - B == 0 3.0602 0.3946 7.755 < 0.001 ***
#> W - G == 0 -1.6034 0.3946 -4.063 0.00305 **
#> Y - G == 0 1.3099 0.3946 3.319 0.01656 *
#> Y - W == 0 2.9133 0.3946 7.383 < 0.001 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> (Adjusted p values reported -- single-step method)