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."
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 …
regression - What does it mean to regress a variable against …
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.
regression - Trying to understand the fitted vs residual plot?
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 …
regression - how to interpret the interaction term in lm formula in …
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 …
regression - Interaction term vs subgroup analysis - Cross Validated
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 …
regression - Why do we say the outcome variable "is regressed …
Apr 15, 2016 · In its core, linear regression amounts to orthogonal projection of y y on (onto) X X, where y y is the n n -dimensional vector of observations of the dependent variable and X X is …
regression - Understanding Propensity Score Matching - Cross …
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 …
regression - Combining vs. Separating Predictors: What’s Better for ...
Apr 30, 2025 · I'm using two independent predictors, A and B (Pearson correlation = 0), both standardized to the same scale, to predict a binary disease outcome using logistic regression. …
regression - Building a linear model for a ratio vs. percentage ...
What kind of regression models are used for positive, non-count data?) Is it better generally to predict (say) the percentage instead of the ratio, and if so, why?