Why are regression problems called "regression" problems?
Origin of 'regression' The term "regression" was coined by Francis Galton in the 19th century to describe a biological phenomenon. The phenomenon was that the heights of descendants of …
correlation - What is the difference between linear regression on y ...
The insight that since Pearson's correlation is the same whether we do a regression of x against y, or y against x is a good one, we should get the same linear regression is a good one. It is …
regression - What does it mean to regress a variable against …
As an example, the data is X = 1,...,100. The value of Y is plotted on the Y axis. The red line is the linear regression surface. Personally, I don't find the independent/dependent variable …
regression - Trying to understand the fitted vs residual plot?
Dec 23, 2016 · In this example, variances for the first quarter of the data, up to about a fitted value of 40 are smaller than variances for fitted values larger than 40. The middle portion of the fitted …
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 - Is it optimal to run 18 LMMs with Bonferroni …
Jun 3, 2025 · One example, and probably the most straightforward, is to construct a system of simultaneously estimated regression paths using maximum likelihood, in what we would …
regression - Why do we say the outcome variable "is regressed …
Apr 15, 2016 · The word "regressed" is used instead of "dependent" because we want to emphasise that we are using a regression technique to represent this dependency between x …
regression - Understanding Propensity Score Matching - Cross …
Nov 27, 2021 · 1) Run a Logistic Regression model to estimate the probability of a patient receiving the treatment vs not receiving the treatment. 2) Based on these Propensity Score …
regression - how to interpret the interaction term in lm formula in …
It is easiest to think about interactions in terms of discrete variables. Perhaps you might have studied two-way ANOVAs, where we have two grouping variables (e.g. gender and age …
regression - Building a linear model for a ratio vs. percentage ...
Echoing the first answer. Don't bother to convert - just model the counts and covariates directly. If you do that and fit a Binomial (or equivalently logistic) regression model to the boy girl counts …