The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

Here's how to run both simple and multiple linear regression in Google Sheets using the built-in LINEST function. No add-ons or coding required.

Beside the model, the other input into a regression analysis is some relevant sample data, consisting of the observed values of the dependent and explanatory variables for a sample of members of the ...

For example, suppose that you would like to model a person's aerobic fitness as measured by the ability to consume oxygen. The data set analyzed in this example is named Fitness, and it contains ...

For example, if X and Y are highly correlated, they could be replaced in a linear regression by X+Y and X-Y without changing the fit of the model or statistics for other regressors.

Examination of the (sample) residuals resulting from the regression analysis can indicate failures of assumptions 1, 3, and 4. Such failures are not necessarily a bad thing: They can point the way to ...

Predicting the Future The most common use of regression in business is to predict events that have yet to occur. Demand analysis, for example, predicts how many units consumers will purchase.

Goodness-of-fit statistics for general multiple-linear-regression equations are reviewed for the case of replicated responses. A modification of the coefficient of determination is recommended. This ...

Hilary Finucane, Brendan Bulik-Sullivan, Benjamin Neale, Alkes Price and colleagues introduce a new method, called stratified LD score regression, for partitioning heritability by functional ...