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."

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 …

Dec 4, 2014 · 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.

4 days ago · However, in lots of papers of all kind of statistical models, not only regression (factor analysis, SEM, ARIMA, etc), I noticed that p-values are used to assess the significance of …

What is the limit to the number of independent variables one may enter in a multiple regression equation? I have 10 predictors that I would like to examine in terms of their relative …

Would you like to specifically know how R creates the design matrix for this formula, or are you more broadly interested in how to interpret such a multiplicative ("interaction") term in terms of …

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?

Suppose I want to build a model to predict some kind of ratio or percentage. For example, let's say I want to predict the number of boys vs. girls who will attend a party, and features of the …

Nov 27, 2021 · I am trying to better understand the motivations and the applications behind Propensity Score Matching. I read the following that explains the motivations behind …

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 …