Chi-Squared Challenging using SPSS
A Chi-Square Challenge (or Test) procedure organizes your data pond variables into groups and computes a chi-square statistic. Here is the specific definition:
“The chi-square (chi, the Greek letter pronounced “kye”) statistic is a statistical technique used to determine if a “distribution of observed frequencies” differs from the “theoretical expected frequencies”…
Okay, this is a pretty clever explanation, however it really just means “does what I see match what I had thought I’d see”.
For example, the chi-square test could be used to determine whether a box of crayons contains equal quantities of blue, brown, green, orange, red, and yellow.
Using IBM SPSS you can obtain your chi-test by selecting from the menus:
Analyze > Nonparametric Tests > Legacy Dialogs > Chi-Square…
From there, you can select one or more test variables. Each variable will produce a separate test.
Using a previous blog as an example, I might want to evaluate the results of a poll conducted on marriage, gender and an individual’s overall satisfaction with their life. Using SPSS I can determine (for an example) that there are 132 total “observations” -121 male and 12 female. Does my expected ratio of male v. female align to the actual? Does my assumption that married females are significantly more satisfied with their life than males are? And so on…
Once again, SPSS makes statistical analysis easy.
