![]() Analyzeįrom the data table, click on the toolbar, and choose Chi-square (and Fisher's exact) test. Prism offers another analysis for that purpose. ![]() If you want to compare an observe distribution of values with a distribution expected by theory, do not use a contingency table. If your experimental design matched patients and controls, you should not analyze your data with contingency tables. For this reason, Prism won't let you enter a decimal point when entering values into a contingency table. You must enter the actual number of subjects, objects, events. Your results will be completely meaningless if you enter averages, percentages or rates. In each cell, enter the number of subjects actually observed. The categories defining the rows and columns must be mutually exclusive, with each subject (or experimental unit) contributing to one cell only. Use the sample data to see how the data should be organized.īe sure to enter data as a contingency table. But it does matter for calculations of relative risk, odds ratio, etc. ![]() ![]() Prism cannot cross-tabulate raw data to create a contingency table.įor calculation of P values, the order of rows and columns does not matter. You must enter data in the form of a contingency table. Most contingency tables have two rows (two groups) and two columns (two possible outcomes), but Prism lets you enter tables with any number of rows and columns. If you are not ready to enter your own data, choose one of the sample data sets. ![]() From the Welcome or New table dialog, choose the contingency tab. ![]()
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