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Linear regression is the most basic and commonly used predictive analysis. Regression estimates are used to describe data and to explain the relationship between one dependent variable and one or more independent variables.
When Dependent Variables Are Not Fit for Linear Models, Now What? When your dependent variable is not continuous, unbounded, and measured on an interval or ratio scale, your model will never meet the Assumptions of the General Linear Model (GLM). Today Iâm going to go into more detail about these 6 common types of dependent variables, and the tests that work instead.