ABSTRACT
In this chapter you will:
Learn basic principles of good graphical design.
Learn how to create histograms, stem-and-leaf plots, and box plots.
In the previous chapter you learned basic statistics designed to describe the characteristics of central tendency (e.g., the mean) and variability (e.g., the variance and standard deviation). These statistics help define two important aspects of a distribution. Indeed, they form the foundation for the analysis of variance. Before applying inferential statistics, however, it is always important to know the subtleties inherent in any data set. The mean and standard deviation do not provide a comprehensive view of the data. The application of good graphical techniques allows you to determine the shape of your data distribution, discover outliers, and uncover subtle patterns in your data that may not be readily detectable when viewing only numerical values. As Edward Tufte summarized in the epilogue of his classic text, The Visual Display of Quantitative Information (1983, p. 191), “What is to be sought in designs for the display of information is the clear portrayal of complexity… the task of the designer is to give visual access to the subtle and the difficult—that is, the revelation of the complex.”