9.1.3 Model quality and statistical significance. We will come back to the question of whether the linear model is valid (whether it satisfies the assumptions of the technique). First we want to ...

One key assumption is that the errors are independent of each other. However, with time series data, the ordinary regression residuals usually are correlated over time. It is not desirable to use ...

Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...

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 ...

In this article, you'll learn the basics of simple linear regression, sometimes called 'ordinary least squares' or OLS regression—a tool commonly used in forecasting and financial analysis. We ...