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."

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 …

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.

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 …

Jun 3, 2025 · I’m working with a dataset that includes 6 continuous predictor variables and 6 continuous response variables across 3 different years. I plan to run a total of 18 linear mixed …

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 …

Mar 21, 2024 · I have a question regarding the choice between interaction term and subgroup analysis. Suppose that I want to study the association between education and income by sex. I …

Nov 4, 2016 · Can somebody explain how the properties of logs make it so you can do log linear regressions where the coefficients are interpreted as percentage changes?

In ANOVA/regression design, "covariate" just refers to factors/independent variables? I may have completely misunderstood this. Can anyone give a simple example of the term "covariate" …

Reading about methods and results of statistical analysis, especially in epidemiology, I very often hear about adjustment or controlling of the models. How would you explain, to a non …