When interpreting the results of a linear regression model, the first step is to look at the regression coefficients. Each term in the model has one. And each one describes the average difference in the value of Y for a one-unit difference in the value of the predictor variable, X, that makes up that term.
It’s the effect size statistic for that term in the model.
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