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 …
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 - 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 - When is R squared negative? - Cross Validated
Also, for OLS regression, R^2 is the squared correlation between the predicted and the observed values. Hence, it must be non-negative. For simple OLS regression with one predictor, this is …
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 - 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 …
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 - Difference between confidence intervals and …
Regression results are typically estimated based upon parametric Student's t distribution parameters and typically regression, especially from poorly matched to the data regression …
regression - Explain model adjustment, in plain English - Cross …
An alternative way of adjusting/controlling for variables that is particularly useful when there are many of them is provided by regression analysis with multiple dependent variables, sometimes …
regression - How to Perform Cross-Validation for LASSO in …
Apr 2, 2025 · I am working with a Generalized Additive Model for Location, Scale, and Shape (GAMLSS) and trying to determine the optimal $\lambda$ values for LASSO-penalized …