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![]() ![]() This is why we dedicate a number of sections of our enhanced Spearman's correlation guide to help you get this right. ![]() Just remember that if you do not test these assumptions correctly, the results you get when running a Spearman's correlation might not be valid. In our enhanced guides, we show you how to: (a) create a scatterplot to check for a monotonic relationship when carrying out Spearman’s correlation using SPSS Statistics (b) interpret different scatterplot results and (c) consider possible solutions if your data fails this assumption. The relationship displayed in your scatterplot should be monotonic. Your scatterplot may look something like one of the following: Whilst there are a number of ways to check whether a monotonic relationship exists between your two variables, we suggest creating a scatterplot using SPSS Statistics, where you can plot one variable against the other, and then visually inspect the scatterplot to check for monotonicity. A monotonic relationship exists when either the variables increase in value together, or as one variable value increases, the other variable value decreases.
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