## Supplement to Lec1.r code.  Example for Project 1 Q#4
## Ex. Kenton Food Company
##   Read in the data; name the variables
kenton <- read.table("Datasets/CH16TA01.txt",
                     col.names=c("Y","package","id"))
kenton$package <- as.factor(kenton$package)
## Summary statistics:  For Q#4 you need to add "$x" to end of each line
cellmeans <- aggregate(kenton$Y, by=list(package=kenton$package), FUN=mean)$x
cellsds <- aggregate(kenton$Y, by=list(package=kenton$package), FUN=sd)$x
cellsizes <- aggregate(kenton$Y, by=list(package=kenton$package), FUN=length)$x
cellmeans; cellsds; cellsizes
## Fit the one-way ANOVA model
fit <- aov(Y ~ package, data=kenton)
## Sample code for Project 1 Q#4
##   Get individual CIs for the means superimposed on the aligned dotplots
##   First gather the ingredients for the CIs
df.res <- fit$df.residual
mse <- sum((fit$residuals)^2)/df.res
se.of.mean <- sqrt(mse)/sqrt(cellsizes)
cc <- qt(.975, df=df.res) # for 95% confidence level
allow <- se.of.mean*cc
##
## The code snippet below is taken from Dalgaard's book on R
stripchart(Y ~ package, method="jitter",
           jitter=0.05,pch=16,vert=TRUE,
           ylim=c(8,35), data=kenton)
arrows(1:4,cellmeans+allow,1:4,cellmeans-allow,angle=90,
     code=3,length=.1)
lines(1:4,cellmeans,pch=4,type="p",cex=2)
title(main="Individual confidence intervals for the means",
      sub="Package Design")
###