I use Python 3 and Jupyter Notebooks to generate plots and equations with linear regression on Kaggle data. I checked the correlations and built a basic machine learning model with this dataset.

Comparing regression coefficients between models when one model is nested within another is of great practical interest when two explanations of a given phenomenon are specified as linear models. The ...

For a regression model, d is usually equal to the number of estimated coefficients. Thus, AIC includes a penalty, which is an increasing function of the number of estimated parameters.

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

In the analysis of censored failure time observations, the standard Cox proportional hazards model assumes that the regression coefficients are time invariant. Often, these parameters vary over time, ...