SPSS: Expected frequencies, chi-squared test. In-depth ...

SPSS: Expected frequencies, chi-squared test. In-depth example: Age groups and radio choices.

Dealing with small frequencies. Quick Example: Handedness and Careers

Last time we tested whether one nominal variable was independent of another.

We did this by looking at the cross tabs and seeing how far the observed frequencies were from the frequencies we would expect if the two variables were independent.

For nominal variables that only had 2 possible responses each (yes/no, male/female, insane/sane), we could use the odds ratio.

When one or both of the variables has more than 2 responses odds ratio is no longer useful, so we use the chi-squared test instead.

The tradeoff: Odds ratio can be used for one-tailed tests, chisquared can't. Chi-squared can handle any number of rows and columns.

Get chi-squared is also heavy in math, so in the real world, SPSS and other software can handle most of it for us.

Most important things to know: - How to get the expected frequency from a particular cell.

- Chi-squared is a measure of how far the observed frequencies are from the expected frequencies.

- Large chi-squared values mean large deviations from the expected frequencies.

- The df for chi-squared is (rows ? 1) x (columns ? 1)

SPSS: Expected frequencies Start with a crosstab.

Analyze Descriptive Stats Crosstabs

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