Than the variance of the dependent variable) adjusted for the number ofĬoefficients in the model relative to the sample size in order to correct itįor bias (the same adjustment used in computing the standard error of the This is R-squared (the fraction by which the variance of the errors is less Typical in size and random-looking, or are they getting bigger or more biased? Relative to a random-walk-without-drift model. Scaled error statistic measures improvement in mean absolute error To these error measures? The mean absolute Improve on the best naive (random walk or random trend) model, according
Statistics are not routinely reported by most regression software, however.Īre working with time series data, you should also ask: does the current regression model Also, it is sometimes appropriate to compare MAPE between modelsįitted to different samples of data, because it is a relative rather than Sensitive to extreme errors, if the occasional big mistake is not a seriousĬoncern. Measures are easier for non-specialists to understand and they are less Series forecasting, it is common to look not only at root-mean-squared errorīut also the mean absolute error (MAE) and, for positive data, the mean absolute percentage error (MAPE) in evaluating and comparing Independent variables that are not included in all models. Models fitted to the same dependent variable, in order to make such comparisonsĮasy, although sample sizes may vary if there are missing values in any Shows side-by-side comparisons of error measures and coefficient estimates for RegressIt provides a Model Summary Report that Same) sample of the same dependent variable. If their units are the same and they are fitted to the same (or almost the Standard error will be only slightly larger than the standard error of theĭirectly compare the standard error of the regression between models only Large and the values of the independent variables are not extreme, the forecast Of the values of the independent variables for which the forecast is being In general theįorecast standard error will be a little larger because it also takes intoĪccount the errors in estimating the coefficients and the relative extremeness
Which is the estimated standard deviation of the unexplainable variations inĪpproximately the standard deviation of the errors, apart from theĭegrees-of-freedom adjustment.) This what your software is trying to minimize when estimatingĬoefficients, and it is a sufficient statistic for describing properties of theĮrrors if the model’s assumptions are all correct.Ī lower bound on the standard error of any forecast generated from the model. Smaller errors, on average, than the best model previously fitted, and is theīest single error statistic to look at is the standard error of the regression, Of freedom): Does the current regression model yield
Standard error of the regression (root-mean-squared error adjusted for degrees Topics discussed here, see the “Regression
This page for a discussion: What's wrong with Excel's Analysis Toolpak for regressionįor a sample of output that illustrates the various It's a toy (a clumsy one at that), not a tool for serious work. You to run linear and logistic regression models in R without writing any codeīeen using Excel's own Data Analysis add-in for regression (Analysis Toolpak),Ĭhanged since it was first introduced in 1993, and it was a poor design even Highly interactive tables and charts that runs on PC's. Support systematic grading and auditing of student work on a large scale. It includes extensive built-inĭocumentation and pop-up teaching notes as well as some novel features to Videos of examples of regression modeling. Interactive presentations, online teaching of regression, and development of Substitute for whatever regression software you are currently using,Įxcel-based or otherwise. Has a richer and easier-to-use interface and much better designed output than The linear regression version runs on both PC's and Macs and
Latest release of RegressIt, a free Excel add-in for linear and logistic
What's the bottom line? How to compare modelsĮxcel in your work or in your teaching to any extent, you should check out the