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 thing depends …

I'm trying to fit a multiple linear regression model to my data with couple of input parameters, say 3.

Oct 19, 2011 · LASSO regression is a type of regression analysis in which both variable selection and regulization occurs simultaneously. This method uses a penalty which affects they value of …

Also, for OLS regression, R^2 is the squared correlation between the predicted and the observed values. Hence, it must be non-negative. For simple OLS regression with one predictor, this is equivalent to …

Nov 14, 2010 · 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 …

What statistical tests or rules of thumb can be used as a basis for excluding outliers in linear regression analysis? Are there any special considerations for multilinear regression?

Oct 3, 2021 · Can I merge multiple linear regressions into one regression? Ask Question Asked 4 years, 4 months ago Modified 3 years, 4 months ago

Jun 5, 2012 · 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...

Oct 25, 2022 · Why do we need so many dummy variables in a regression with categorical predictor? Why not use binary encoding instead of one-hot encoding? Ask Question Asked 3 years, 3 months …

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