regression - What does it mean to regress a variable against …
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 …
regression - Interpreting the residuals vs. fitted values plot for ...
Consider the following figure from Faraway's Linear Models with R (2005, p. 59). The first plot seems to indicate that the residuals and the fitted values are uncorrelated, as they should be in a
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."
What's the difference between correlation and simple linear …
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 …
In linear regression, when is it appropriate to use the log of an ...
Aug 24, 2021 · This is because any regression coefficients involving the original variable - whether it is the dependent or the independent variable - will have a percentage point change …
Minimum number of observations for multiple linear regression
Jun 1, 2012 · I am doing multiple linear regression. I have 21 observations and 5 variables. My aim is just finding the relation between variables Is my data set enough to do multiple …
Deciding between a linear regression model or non-linear …
There are four principal assumptions which justify the use of linear regression models for purposes of inference or prediction: (i) linearity and additivity of the relationship between …
How does linear regression use the normal distribution?
Apr 29, 2015 · How does linear regression use this assumption? As any regression, the linear model (=regression with normal error) searches for the parameters that optimize the likelihood …
Extract standard errors of coefficient linear regression R
May 2, 2012 · I would like to note that the question concerned the standard errors of the regression coefficients and not the values of the coefficients themselves. The above answer is …
Inclusion of lagged dependent variable in regression
I'm very confused about if it's legitimate to include a lagged dependent variable into a regression model. Basically I think if this model focuses on the relationship between the change in Y and ot...