Using R for Introductory Statistics : John Verzani

Multivariate data 131+ subset=(wt != 999 & gestation != 999),+ panel=panel.regression) # a new panel functionFigure 4.8 contains the graphic. We might ask, “Are the slopes similar?” and, “Whatwould it mean if they aren’t?”Figure 4.8 Gestation versus weightfor levels of smoke4.4.1 Problems4.22 The kid. weights (UsingR) data set contains measurements for several children.There is a clear relationship between height and weight. Break the data down by the ageof the child. As age is numeric, it helps to turn it into a factor: cut (age/12, 3*(0:4)). Doyou see the same trend for all the age groups?4.23 For the kid.weights (UsingR) data set, explore the relationship of weight andgender for the age ranges 0–3, 3–6, 6–9, and 9–12. Is the relationship always the same?4.24 The female. inc (UsingR) data set contains income and race data for females inthe United States for the year 2001. Make a boxplot of the income variable broken up bythe race variable. Do there appear to be any major differences among the races? Inaddition, compute the summary statistics for each racial group in the data.4.25 The data set ToothGrowth contains measurements of tooth growth for differentdosages of a supplement. Use the function bwplot() to make boxplots of len for each levelof dose broken up by the levels of supp. You need to make dose a factor first. Also,repeat the graphic after reversing the role of the two factors.4.26 The car safety (UsingR) data set contains data on accident fatalities per millionvehicles for several types of cars. Make boxplots of Driver. deaths broken down by type.