# Chapter 3 Descriptive Syntax in R.

# We begin by reading the comma-separated rat pup data file (rat_pup.dat) into R.

ratpup <- read.table("http://www.rohan.sdsu.edu/~babailey/stat700/rat_pup.dat", h = T)
ratpup

# In order to simplify reference and manipulation of the data, we will execute attach(ratpup) so that objects in the 
# dataset ratpup can be accessed by simply giving their names (e.g. sex rather than ratpup$sex).   

attach(ratpup)

# We use boxplots to compare the distributions of birth weights for each treatment by sex combination graphically. We 
# first sort the data by TREAT and SEX, so that the boxplots will be displayed in the proper order. Levels of TREAT form 
# blocks in the boxplot output—each level of SEX is displayed within a block of TREAT. The block label position is set to # be at the bottom of the graph.

library(lattice)  # trellis graphics
library(grid)

bwplot(weight ~ sex|treatment, data=ratpup,aspect = 2, ylab="Birth Weights", 
    xlab="SEX",main = "Boxplots of birth weights for levels of treatment by sex")
 
# We use boxplots to illustrate the relationship between birth weight and litter size. Each panel shows the distributions # of birth weights for all litters ranked by size, within a given level of treatment and sex. We first create a new 
# variable, RANKLIT, to order the litters by size. The smallest litter has a size of 2 pups (RANKLIT = 1) and the largest # litter has a size of 18 pups (RANKLIT = 27).

ranklit <- litsize+0.01*litter
sort(ranklit)
ranklit
ranklit <- factor(ranklit)

levels(ranklit) <- c( "1","2", "3","4","5","6","7","8","9","10", "11","12", "13","14","15","16","17","18","19","20", "21","22", "23","24","25","26","27")

ranklit

bwplot(weight ~ranklit | treatment*sex, data=ratpup,aspect = 2, ylab="Birth Weights", xlab="" )

#Additional summary plots
RatPupWeight <- ratpup[,2:6]
summary(RatPupWeight)
plot(RatPupWeight)             ## default dot plot
plot.design(RatPupWeight[,-1]) ## shows spreads of each factor variable

par(pty="s")
dotplot(litter ~ weight,group=interaction(treatment,sex), data =RatPupWeight,
         autoKey=T )

with(RatPupWeight, interaction.plot( treatment,sex,weight))

with(RatPupWeight, tapply( weight, interaction(treatment,sex),summary))