Chi square is a nonparametric statistical test appropriate when the data are in the form of frequency counts or percentages and proportions that can be converted into frequencies. These frequency counts can be placed into two or more categories. Thus, chi square is appropriate when the data are a nominal scale (e.g., male or female, Democrat or Republican). A chi square test compares the proportions actually observed in a study to the proportions expected, to see if they are significantly different. Expected proportions are usually the frequencies that would be expected if the groups were equal, although occasionally they also may be based on past data. The chi square value increases as the difference between observed and expected frequencies increases. To determine whether chi square is significant, you must consult a chi square table.
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