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

Multiple linear regression should be used when multiple independent variables determine the outcome of a single dependent variable. This is often the case when forecasting more complex relationships.

Learn the difference between linear regression and multiple regression and how investors can use these types of statistical analysis.

When multiple variables are associated with a response, the interpretation of a prediction equation is seldom simple.

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.

This paper provides an alternative approach to penalized regression for model selection in the context of high-dimensional linear regressions where the number of covariates is large, often much larger ...

This is where regression comes in. By using the regression function `svyglm ()` in R, we can conduct a regression analysis that includes party differences in the same model as race. Using `svyglm ()` ...