Regression is problematic for classical statistical tests that assume independently distributed errors.
Regression is a statistical technique that relates a dependent variable to one or more independent (explanatory) variables. A regression model can indicate whether an observed change in the dependent variable is associated with changes in one or more of the explanatory variables.
Regression comes from "regress", which comes from the Latin word "regresses" – (to return to something). In this sense, regression is a technique that allows us to move from chaotic and difficult-to-interpret data to a clearer and more meaningful model.
Regression analysis predicts a continuous dependent variable from a set of variables. Used when the independent variable. If your dependent variable is dichotomous, you should use logistic regression.
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