Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

A framework is developed for the interpretation of regression plots, including plots of the response against selected covariates, residual plots, added-variable plots, and detrended added-variable ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Exploratory data analysis plays a central role in applied statistics and econometrics. In the popular regression-discontinuity (RD) design, the use of graphical analysis has been strongly advocated ...

If you want to advance your data science skill set, Python can be a valuable tool for SEOs to generate deep data insights to help your brand. The programming language of Python is gaining popularity ...

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

Businesspeople need to demand more from machine learning so they can connect data scientists’ work to relevant action. This requires basic machine learning literacy — what kinds of problems can ...