Perhaps the most fundamental type of R analysis is linear regression. Linear regression can be used for two closely related, but slightly different purposes. You can use linear regression to predict ...

xkcd #2048 is exceptionally relevant to this. Doing linear regression well with a big dataset is difficult! I do this all the time at work and honestly I often show a scatter plot without any ...

Learn how to graph linear regression in Excel. ... In contrast to the R 2 value, a smaller p-value is favorable as it indicates a correlation between the dependent and independent variables.

The major outputs you need to be concerned about for simple linear regression are the R-squared, the intercept (constant) and the GDP's beta (b) coefficient. The R-squared number in this example ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of linear regression with two-way interactions between predictor variables. Compared to standard linear ...

The next time you cover this topic, consider teaching students how to perform a simple linear regression analysis in Excel. Below is an example screenshot illustrating 12 months of cost data for a ...

Specialization: Statistical Modeling for Data Science Applications Instructor: Brian Zaharatos, Director, Professional Master’s Degree in Applied Mathematics Prior knowledge needed: Basic calculus ...

This post will show how to estimate and interpret linear regression models with survey data using R. We’ll use data taken from a Pew Research Center 2016 post-election survey, and you can download the ...

A regression equation with a zillion dummy variables in it is hard to read and has little generalizable business value. For example, instead of having a factor “city” with many different levels/values ...