How can we interpret R^2 ?
R^2 indicates how much of the variation in the dependent variable can be explained by the independent variables in the model (Goodness of Fit of the Model)
Value from 0 to 1 - the higher the better the model
How can we intrepret the Standard errors of regression ?
S.E of the regression measures the average size of the residuals around the fitted regression line
Value - the lower the better
A low value means that predictions are closer to actual observations
How can we interpret the value for the F-statistic ? And the p-value ?
The F-statistic tests the H0 that all estimators (Beta) are 0, so that they have no explanatory power.
The larger the value, the higher the possibility that we can reject H0 and the Betas are together significant
The p-value next to it shows the probability of observing such an F-statistic if the H0 were true.. small value = higher statistical significance
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