A Tutrial on Correlation, Regression Analysis and Analysis of Variance

Crosstabulation is a simple, straightforward tool for examining relationships between variables, but it has two important disadvantages. First, quantitative variables with many values must be recoded to a smaller number of categories before they can be crosstabbed with other variables. This necessarily loses information about the covariation of the variables. Second, crosstabulation limits severely the number of variables whose relationships can be examined simultaneously. While we may be able to control for one variable while evaluating the association between two others, our theories or prior research findings often require that we take into account the simultaneous influences of a number of variables. Unless we have an exceptionally large number of cases, a traditional crosstabular control strategy will result in many subtables, most of which are likely to have very few cases.