In some literature, I have read that a regression with multiple explanatory variables, if in different units, needed to be standardized. (Standardizing consists in subtracting the mean and dividin...
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 interpretation.
In linear regression, when is it appropriate to use the log of an ...
Is it possible to have a (multiple) regression equation with two or more dependent variables? Sure, you could run two separate regression equations, one for each DV, but that doesn't seem like it ...
The regression slope measures the "steepness" of the linear relationship between two variables and can take any value from $-\infty$ to $+\infty$. Slopes near zero mean that the response (Y) variable changes slowly as the predictor (X) variable changes.
ANOVA and linear regression are equivalent when the two models test against the same hypotheses and use an identical encoding. The models differ in their basic aim: ANOVA is mostly concerned to present differences between categories' means in the data while linear regression is mostly concern to estimate a sample mean response and an associated $\sigma^2$. Somewhat aphoristically one can ...
If I want to examine sex differences in three variables, lets say academic attainment, study motivation, and a variable that is categorical. How should can I fit these variables with OLS regression?
It appears that isotonic regression is a popular method to calibrate models. I understand that isotonic guarantees a monotonically increasing or decreasing fit. However, if you can get a smoother f...