Using R for Introductory Statistics : John Verzani

Using R for introductory statistics 274for comparison, as comparing slopes isn’t applicable for multivariate models. The Cook’sdistance is computed by the extractor function cooks. distance ().One of the diagnostic plots produced by plot () will show the Cook’s distance for thedata points plotted using spikes. Another way to display this information graphically is tomake the size of the points in the scatterplot depend on this distance using the cex=argument. This type of plot is referred to as a bubble plot and is illustrated using theemissions (UsingR) data set in Figure 10.4. The graphic is made with the followingcommands:> res = lm(C02 ~ perCapita, emissions)> plot(C02 ~ perCapita, emissions,+ cex = 10*sqrt(cooks.distance(res)),+ main = expression( # make subscript on C02in title+ paste("bubble plot of ",CO[2],+ ” emissions by per capita GDP")+ ))The square root of the distances is used, so the area of the points is proportional to theCook’s distance rather than to the radius. (The argument to main= illustrates how to usemathematical notation in the title of a graphic. See the help page ?plotmath for details.)For the maximum-heart-rate data, the four diagnostic plots produced by R with thecommand plot (res. mhr) are in Figure 10.5. The par (mf row=c (2,2)) command was usedto make the four graphs appear in one figure. This command sets the number of rows andcolumns in a multi-graphic figure.