Where β∗ β ∗ are the estimators from the regression run on the standardized variables and β^ β ^ is the same estimator converted back to the original scale, Sy S y is the sample standard …

Dec 4, 2014 · When we say, to regress Y Y against X X, do we mean that X X is the independent variable and Y the dependent variable? i.e. Y = aX + b Y = a X + b.

Mar 21, 2014 · In linear regression, we often get multiple R and R squared. What are the differences between them?

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 …

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 …

A quick question: Is "residual standard error" the same as "residual standard deviation"? Gelman and Hill (p.41, 2007) seem to use them interchangeably.

Jan 10, 2015 · I would have expected the correlation coefficient to be the same as a regression slope (beta), however having just compared the two, they are different. How do they differ - …

Jan 6, 2021 · Three linear machine learning algorithms: Linear Regression, Logistic Regression and Linear Discriminant Analysis. Five nonlinear algorithms: Classification and Regression …

What statistical tests or rules of thumb can be used as a basis for excluding outliers in linear regression analysis? Are there any special considerations for multilinear regression?

Sep 23, 2020 · In a log-level regression, the independent variables have an additive effect on the log-transformed response and a multiplicative effect on the original untransformed response: