# put Howell's data into more convenient form for the homework

# read the data
# assumes you've downloaded the data files into current dir
phonedat <-read.delim2("Ex11-32.dat")
gluclat <-read.delim2("Ex12-22.dat")
trials2learn <-read.delim2("Ex12-1.dat")

# First do the driving data
# change from the data-in-separate columns format into the 
# the standard each-row-is-an-observation format; omit the 
# unecessary id column
phonedat <- stack(phonedat, select = -id)
# first column is now the measured values (steering errors)
# and second col. is the condition (alcohol., cell phone, or control)

# work on the rat learning data
# these data come with a "Group" column with the numbers 1 through 5 indicating 
# treatment groups - we'll create a new column that is a "factor" (for the anova) and
# that has more descriptive names
mylevels = c('control1', 'control2', 'nofood', 'nowater', 'nofoodorwater')
# make these labels into an official "factor"
myfactor <- factor(trials2learn$Group, labels=mylevels)
# add factor to the data frame
trials2learn$GroupName <- myfactor

# now do the latency vs. glucose data
# make vector containing doses - these are from memory, so might be wrong
myvals = c(0, 1, 10, 100, 250, 500)
# make a vector with 6 of each
myvals <- rep(myvals, each=6)
# and put into a new "doses" column of our data frame
gluclat$doses <- myvals

# save into an easily-loadable R workspace file
save(gluclat, phonedat, trials2learn, file = "myHWdata.Rdata")

#say "woohoo"
print('woo hoo')