Dec 21, 2016 · When we say, to regress $Y$ against $X$, do we mean that $X$ is the independent variable and Y the dependent variable? i.e. $Y =aX + b$.

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

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."

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 …

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 interpretation.

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 regression? The t-test …

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 dependent and …

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 for the given …

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 misleading in this …

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...