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Are the relationships between my variables linear?
This may seem like a tricky question to answer, but it is actually very simple! You can use the Scatterplot Matrix to evaluate all of the relationships between the variables in your data. Linear relationships would look like diagonal lines in the scatterplot matrix. Non-linear relationships could look more like curved lines, or take some other shape.[ATTACH]947[/ATTACH]
If you see that the variable you are trying to model (your dependent variable) has a non-linear relationship with one of your explanatory variables then you have some work to do! OLS is a linear regression model that assumes that the relationships between your variables are linear. If they aren�??t linear, you can try to transform your variables so that the relationships become linear. Common transformations include Log and Exponential transformations.
Another useful output of the scatterplot matrix is the histogram that is created for each of the variables. You can use these histograms to figure out if your data is normally distributed, or if it is skewed or has outliers. Skewness and outliers can cause problems in many types of statistics, including regression. You can use the same power transformations that I just mentioned to help you mitigate the impact of outliers and skewness. This image shows the way that different types of transformations can help you get your data into its most useful form.
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ESRI | Redlands, CA