Linear Regression using Python

This video is on linear regression using Python and the statsmodels package. In it, I demonstrate how to create data, and how to summarize and visualize the data for a simulated research project. I state the research question and the null hypothesis and alternative hypothesis.

There is a thorough explanation of a linear model in one variable in order to build intuition about the results of linear regression. I explain what all the important results are and show how they are calculated. These include the parameters estimates (coefficients), the standard error, test statistics, p value, and the confidence intervals.

I also explain the errors in the model such the sum of squared errors due to the regression and the residuals, the degrees of freedom in the model, the F statistic and its p value, as well as the coefficient of determination.