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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 "
- regression - What does it mean to regress a variable against another . . .
When we say, to regress Y Y against X X, do we mean that X X is the independent variable and Y the dependent variable? i e Y = aX + b Y = a X + b
- How should outliers be dealt with in linear regression analysis?
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?
- 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 the
- 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
- regression - Trying to understand the fitted vs residual plot? - Cross . . .
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 reasonable The res
- Regression with multiple dependent variables? - Cross Validated
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
- regression - How exactly does one “control for other variables . . .
Here is the article that motivated this question: Does impatience make us fat? I liked this article, and it nicely demonstrates the concept of “controlling for other variables” (IQ, career, income
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