Exploring Data with R

A data analyst can obtain a huge data set and extract visual patterns from it in a very short time. R software is especially good at generating high-level graphics. This chapter surveys some graphing possibilities in R, from basic to more advanced, and features many visualization tools that can be immediately applied directly to the data as needed. The most common way to obtain a basic plot in R is to use the plot() function. The chapter shows a generic example for plotting two variables against each other in two dimensions using vectors z and w, and then proceeds to produce additional scatterplots using the featured data sets. Stem-and-leaf plots have the advantage that one can see the actual data points in the plot rather than the data be invisibly binned as in the case of histograms. The chapter also discusses assessment of normality of distributions and box-and-whisker plots.