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."
regression - What does it mean to regress a variable against another ...
Dec 21, 2016 · Those words connote causality, but regression can work the other way round too (use Y to predict X). The independent/dependent variable language merely specifies how one thing depends …
Why is the intercept negative, and what does my regression show?
It is expected that if a model is perfect, the unexplained variation in y should be 0 and thereby the intercept should be zero. In a regression model where the intercept is negative implies that the model …
Multivariable vs multivariate regression - Cross Validated
Feb 2, 2020 · Multivariable regression is any regression model where there is more than one explanatory variable. For this reason it is often simply known as "multiple regression". In the simple …
What's the difference between correlation and simple linear regression ...
Aug 1, 2013 · Note that one perspective on the relationship between regression & correlation can be discerned from my answer here: What is the difference between doing linear regression on y with x …
regression - When should I use lasso vs ridge? - Cross Validated
Ridge regression is useful as a general shrinking of all coefficients together. It is shrinking to reduce the variance and over fitting. It relates to the prior believe that coefficient values shouldn't be too large …
regression - Difference between forecast and prediction ... - Cross ...
I was wondering what difference and relation are between forecast and prediction? Especially in time series and regression? For example, am I correct that: In time series, forecasting seems to mea...
regression - Trying to understand the fitted vs residual plot? - Cross ...
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 reasonable. The …
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 equivalent to …
When conducting multiple regression, when should you center your ...
Jun 5, 2012 · In some literature, I have read that a regression with multiple explanatory variables, if in different units, needed to be standardized. (Standardizing consists in subtracting the mean and dividin...