Yeah funny enough I came across this awhile ago and was confused until I realized it was the root square mean error (rmse). So average distance observations are away from the predicted value.
Im currently working on a dissertation. After running an OLS regression I have a statistic called the standard error of the regression. I have analysed the standard error of the coefficients but I do not know what the difference between the standard error of regression and coefficient are.
Please help!!
Yeah funny enough I came across this awhile ago and was confused until I realized it was the root square mean error (rmse). So average distance observations are away from the predicted value.
Stop cowardice, ban guns!
hl: The RMSE is the average of the squared deviations of actual values of Y from the predicted values of Y. In short, the standard error of a regression model is not an unbiased average of the error terms.
You can think of it as the estimate for the standard deviation of the error term. If you multiply it by 2, you can use the empirical rule to make a statement that about 95% of the actual y values will fall within 2*s of their respective predicted values using the particular model (within 2*s implies above and below the average, hence the approximate interval). It gives you a bit of an idea about accuracy, if only in-sample. If you find that 2*s is too large, you may want to find a way to improve the model.
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