Origin of 'regression' The term "regression" was coined by Francis Galton in the 19th century to describe a biological phenomenon. The phenomenon was that the heights of descendants of …

As an example, the data is X = 1,...,100. The value of Y is plotted on the Y axis. The red line is the linear regression surface. Personally, I don't find the independent/dependent variable …

Dec 23, 2016 · In this example, variances for the first quarter of the data, up to about a fitted value of 40 are smaller than variances for fitted values larger than 40. The middle portion of the fitted …

In regression we can get biased estimators of slopes by doing stepwise regression. A variable is more likely to be kept in a stepwise regression if the estimated slope is further from 0 and …

May 3, 2024 · I have performed a Theil-Sen slope regression on the size (hectares) of Beech trees coverage in a given Swedish forest from 1986 to 2020. The development is set to be an …

Jun 19, 2016 · A regression model is often used for extrapolation, i.e. predicting the response to an input which lies outside of the range of the values of the predictor variable used to fit the …

May 17, 2011 · Endogeneity is often described as having three sources: omitted variables, measurement error, and simultaneity. Though it is often helpful to mention these "sources" …

Oct 5, 2011 · A better alternative is often quantile regression. I wrote about this for NESUG recently. That paper is here. One exception to the above is when the categories are …

Sep 1, 2022 · I am looking for a beginner-friendly explanation of what Robbins' G-computation and G-estimation are for estimating causal effects. What problem(s) do they solve. Ideally I …

One of the observable ways it might differ from being equal is if it changes with the mean (estimated by fitted); another way is if it changes with some independent variable (though for …