SAS For Dummies by Stephen McDaniel

Author:Stephen McDaniel
Language: eng
Format: epub
Publisher: Wiley
Published: 2010-03-08T16:00:00+00:00

Analyzing Counts and Frequencies

In customer demographic and health care research, collecting responses for one or more categorical variables is common. Examples of categorical variables include a favorite car type, ethnic background, gender, disease progression status, a grade received in a course, marital status, home ownership status, citizenship status, credit grade, and employment status. Some categorical variables have inherent order, and others are just categories with no implicit order. Gender is a good example of a nominal variable, a variable with no explicit order to the values male and female. There is no reason to place female before male except for the alphabetic order of the name of the category. Disease progression status is a good example of an ordinal variable because Stage I of a disease occurs before Stage II, and so on. Ordinal variables simply have an order of the categories. They have no exact ratio of difference among the categories: That is, Stage I is not necessarily half as advanced as Stage II.

An example of a two-way contingency table is shown in Figure 8-2. This is a table of chocolate preference by gender generated with the Table Analysis task (available by choosing Describe⇒Table Analysis). This type of table is also referred to as a contingency table or a cross-tabular summary. The Table Analysis task can produce contingency tables based on many variables, but practical experience shows that no more than three or four variables can be examined easily. The Table Analysis task adds more value than the Summary Tables task (covered in Chapter 6) because of the availability of many statistical methods to determine whether the differences among the various categories are statistically significant.

Figure 8-2: A two-way contingency table of gender by chocolate type preference.

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