13.1. Learning Objectives

Conceptual

This week we have introduced regression analysis.

After this week, you should be able to:

• Know how regression relates to the methods of correlation and covariance.

• Understand the “Least Squares” concept.

• Distinguish a dependent from an independent variable.

• Understand the form and interpretation of the regression equation.

• Recognise and understand the equations for calculating regression coefficients.

These points will be covered in the lecture.

Python Skills

Starting this week, and for the rest of the course, we will be working with the statsmodels package in Python.

This week, you will learn to:

• Run a simple regression model in Python.

• Understand the model outputs including the intercept and slope coefficients, and the sum of residuals.

• Identify potential outliers and exclude them from your analysis.

• Plot a regression line over a scatterplot.

We will also be re-capping some of the valuable skills you learned for handling real-world data (data cleaning and finding outliers), as well as other skills relevant to regression modelling, namely making scatter plots, and finding correlations.