2.2 Graphing qualitative variables

When Apple Computer introduced the iMac computer in August 1998, the company wanted to learn whether the iMac was expandingApple?s market share. Was the iMac just attracting previous Macintosh owners? Or was it purchased by newcomers to thecomputer market, and by previous Windows users who were switching over? To find out, 500 iMac customers wereinterviewed. Each customer was categorized as a previous Macintosh owners, a previous Windows owner, or a new computerpurchaser. This section examines graphical methods for displaying the results of the interviews. We'll learn somegeneral lessons about how to graph data that fall into a small number of categories. A later section will consider how to graphnumerical data in which each observation is represented by a number in some range. The key point about the qualitative datathat occupy us in the present section is that they do not come with a pre-established ordering (the way numbers areordered). For example, there is no natural sense in which the category of previous Windows users comes before or after thecategory of previous iMac users. This situation may be contrasted with quantitative data, such as a person?sweight. People of one weight are naturally ordered with respect to people of a different weight.

Frequency tables

All of the graphical methods shown in this section are derived from frequency tables. shows a frequency table for the results of the iMac study; it showsthe frequencies of the various response categories. It also shows the relative frequencies, which are the proportion ofresponses in each category. For example, the relative frequency for "none" of $0.17=85/500$ .

Pie charts

The pie chart in shows the results of the iMac study. In a pie chart, each category is representedby a slice of the pie. The area of the slice is proportional to the percentage of responses in the category. This is simplythe relative frequency multiplied by 100. Although most iMac purchasers were Macintosh owners, Apple was encouraged by the12% of purchasers who were former Windows users, and by the 17% of purchasers who were buying a computer for the firsttime.

"The only worse design than a pie chart is several of them"

Here is another important point about pie charts. If they are based on a small number of observations, itcan be misleading to label the pie slices with percentages. For example, if just 5 people had been interviewed by AppleComputers, and 3 were former Windows users, it would be misleading to display a pie chart with the Windows slice showing60%. With so few people interviewed, such a large percentage of Windows users might easily have accord since chance can causelarge errors with small samples. In this case, it is better to alert the user of the pie chart to the actual numbersinvolved. The slices should therefore be labeled with the actual frequencies observed ( e.g. , 3) instead of with percentages.