regression - Why do we say the outcome variable is regressed on the . . . 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 and y So, this sentence "y is regressed on x" is the short format of: Every predicted y shall "be dependent on" a value of x through a regression technique
Multivariable vs multivariate regression - Cross Validated 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 case of just one explanatory variable, this is sometimes called univariable regression Unfortunately multivariable regression is often mistakenly called multivariate regression, or vice versa Multivariate
How does the correlation coefficient differ from regression slope? The regression slope measures the "steepness" of the linear relationship between two variables and can take any value from $-\infty$ to $+\infty$ Slopes near zero mean that the response (Y) variable changes slowly as the predictor (X) variable changes
What is the lasso in regression analysis? - Cross Validated LASSO regression is a type of regression analysis in which both variable selection and regulization occurs simultaneously This method uses a penalty which affects they value of coefficients of regression
Regression with multiple dependent variables? - Cross Validated Is it possible to have a (multiple) regression equation with two or more dependent variables? Sure, you could run two separate regression equations, one for each DV, but that doesn't seem like it
Linear regression when independent variable are count data The Ys, on the other hand, are continuous and can assume any numerical value, either positive or negative Initially, my approach was to apply linear regression to model this relationship However, given the specific nature of the Xs as count variables, I've grown uncertain about the appropriateness of using linear regression