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The result will appear in the SPSS Output Viewer. Once you have specified the values that define each group, press the Continue button, and then click on OK in the main dialog box to run the Mann-Whitney U test. It’s also worth noting that if you had coded your grouping variable as a String type, then you’d need to match the string values that appear in the Data View precisely – for example, “No Dog” and “Owns Dog”. We’re using 0 and 1 to specify each group, because these values match the way the variable is coded (the Data View shows value labels, not the underlying numeric values). This indicates that you need to define the groups that make up the grouping variable. You’ll notice that the Grouping Variable, DogOwner, has two question marks in brackets after it. The dialog should now look something like this. You also need to select Mann-Whitney U under Test Type (by ticking the box). To move the variables over, you can either drag and drop, or use the blue arrows. To perform the Mann-Whitney U test, we’ve got to get our dependent variable (Frisbee Throwing Distance) into the Test Variable List box, and our grouping variable (Dog Owner) into the Grouping Variable box.
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This will bring up the Two-Independent-Samples Tests dialog box. To begin, click Analyze -> Nonparametric Tests -> Legacy Dialogs -> 2 Independent Samples. The obvious choice here is the Mann-Whitney U test. This means we’re better off using a non-parametric test to determine whether there is a relationship between our independent and dependent variables (though, actually, since we have a large number of observations, we’d probably get away with the t test). This is confirmed by the histogram, which has a long left tail. The trouble is if we test our data for normality, we get this result.īoth Kolmogorov-Smirnov and Shapiro-Wilk suggest that our dependent variable is not distributed normally. One assumption of this parametric test is that data is normally distributed. Given this setup, it would be usual to conduct an independent samples t test. Put simply, we want to know whether owning a dog (independent variable) has any effect on the ability to throw a frisbee (dependent variable). In our example, Frisbee Throwing Distance in Metres is the dependent variable, and Dog Owner is the grouping variable. The DataĪs per usual, we’re working on the assumption that you’ve opened SPSS, you’re looking at the Data View, and it looks something like this. The result will appear in the SPSS data viewer.įor this tutorial, we’re using data from a fake study that looks at the relationship between dog ownership and the ability to throw a frisbee.Press Continue, and then click on OK to run the test.Click on Define Groups, and input the values that define each of the groups that make up the grouping variable (i.e., the coded value for Group 1 and the coded value for Group 2).Drag and drop the dependent variable into the Test Variable(s) box, and the grouping variable into the Grouping Variable box.Click Analyze -> Nonparametric Tests -> Legacy Dialogs -> 2 Independent Samples.