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Plotting commands for homework 5

 `####``# using "unclass" to assign multiple colors``# in plotting``#``# We reuse Hinton's data on a teacher's ratings``# of how well some girls and boys paid attention in class``hinton.attention = data.frame(child = c("susan", "linda", "john", "mary", "peter", "ian", "trevor", "andrew", "helen", "christine"), rating = c(67, 55, 26, 70, 36, 57, 32, 65, 59, 24))``# adding in gender as a factor``hinton.attention\$gender = as.factor(c("g", "g", "b", "g", "b", "b", "b", "b", "g", "g"))``# plotting the teacher's ratings in pink and blue``plot(hinton.attention\$rating, col = c("lightblue", "pink")[unclass(hinton.attention\$gender)])``####``# using boxplots to inspect principal components``# coming out of principal component analysis``#``# we again use the PCA analysis of affixes in different texts``# that we have used before``library(languageR)``affixes.pr = prcomp(affixProductivity[,1:(ncol(affixProductivity)-3)])``# where does the first principal component tend to put books``# from different registers?``boxplot(affixes.pr\$x[,1] ~ affixProductivity\$Registers)``####``# does the first principal component capture something``# about the degree to which 'ly' is used productively?``plot(affixProductivity\$ly, affixes.pr\$x[,1], type = "p",``     xlab = "productivity for '-ly'", ylab = "value on PC1")``# adding a smoother to the impressively straight line``lines(lowess(affixProductivity\$ly, affixes.pr\$x[,1]))`