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- Why are regression problems called regression problems?
I was just wondering why regression problems are called "regression" problems What is the story behind the name? One definition for regression: "Relapse to a less perfect or developed state "
- Why is the intercept negative, and what does my regression show?
It is expected that if a model is perfect, the unexplained variation in y should be 0 and thereby the intercept should be zero In a regression model where the intercept is negative implies that the model is overestimating on an average the y values thereby a negative correction in the predicted values is needed
- regression - Converting standardized betas back to original variables . . .
I have a problem where I need to standardize the variables run the (ridge regression) to calculate the ridge estimates of the betas I then need to convert these back to the original variables scale
- regression - Interpretation of log transformed predictor and or . . .
I'm wondering if it makes a difference in interpretation whether only the dependent, both the dependent and independent, or only the independent variables are log transformed Consider the case of
- regression - What does it mean to regress a variable against another . . .
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 on the other Generally speaking it makes more sense to use correlation rather than regression if there is no causal relationship
- Whats the difference between correlation and simple linear regression . . .
Note that one perspective on the relationship between regression correlation can be discerned from my answer here: What is the difference between doing linear regression on y with x versus x with y?
- Multivariable vs multivariate regression - Cross Validated
Multivariable regression is any regression model where there is more than one explanatory variable For this reason it is often simply known as "multiple regression" In the simple case of just one explanatory variable, this is sometimes called univariable regression Unfortunately multivariable regression is often mistakenly called multivariate regression, or vice versa Multivariate
- When conducting multiple regression, when should you center your . . .
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
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