regression - When is R squared negative? - Cross Validated
With linear regression with no constraints, R2 R 2 must be positive (or zero) and equals the square of the correlation coefficient, r r. A negative R2 R 2 is only possible with linear …
regression - Trying to understand the fitted vs residual plot?
Dec 23, 2016 · A good residual vs fitted plot has three characteristics: The residuals "bounce randomly" around the 0 line. This suggests that the assumption that the relationship is linear is …
regression - What does it mean to regress a variable against …
Dec 21, 2016 · Those words connote causality, but regression can work the other way round too (use Y to predict X). The independent/dependent variable language merely specifies how one …
regression - Linear model with both additive and multiplicative …
Sep 23, 2020 · In a log-level regression, the independent variables have an additive effect on the log-transformed response and a multiplicative effect on the original untransformed response:
regression - What intuitively is "bias"? - Cross Validated
Feb 1, 2019 · I'm struggling to grasp the concept of bias in the context of linear regression analysis. What is the mathematical definition of bias? What exactly is biased and why/how? …
correlation - What is the difference between linear regression on y ...
The Pearson correlation coefficient of x and y is the same, whether you compute pearson(x, y) or pearson(y, x). This suggests that doing a linear regression of y given x or x given y should be …
regression - What is the "root MSE" in Stata? - Cross Validated
I have a question that has been confusing me ever since I took econometrics last year. What does the "root MSE" mean in Stata output when you regress a OLS model? I know that it translates …
regression - Mean centering interaction terms - Cross Validated
Jul 11, 2019 · I want to mean center my interaction terms in a regression model (i.e., make the mean zero for each variable). I understand that I am supposed to mean center my variables …
regression - How to use weights in function lm in R? - Cross …
Could anyone offer some pointers on how to use the weights argument in R's lm function? Say, for instance you were trying to fit a model on traffic data, and you had several hundred rows, …
In linear regression, when is it appropriate to use the log of an ...
Aug 24, 2021 · This is because any regression coefficients involving the original variable - whether it is the dependent or the independent variable - will have a percentage point change …