I would start with a correlation analysis, and a scatterplot matrix of the 3 variables. Principal Components is another tool that would work here.
Regression is only appropriate if you have one or more dependent variables (also called "response" variables) and one or more independent variables (also called "predictor" variables). It's not clear to me that any of your variables is a dependent variable.
I would start with a correlation analysis, and a scatterplot matrix of the 3 variables. Principal Components is another tool that would work here.
Regression is only appropriate if you have one or more dependent variables (also called "response" variables) and one or more independent variables (also called "predictor" variables). It's not clear to me that any of your variables is a dependent variable.
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ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.
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