Lecture 1

Regression modelling is a collection of statistical techniques that have the common goal of finding a relationship between a target response and various explanatory, predictors or covariates. The goal is to explain variation in or predict the target variable given the values of the predictor. Equally important is to understand the effect of the predictors on the response in a regression model. This course is designed to provide an introduction to regression modelling.

In this course we will introduce and discuss statistical methods to answer questions such as:

• How does the price of a car depend on its age?
• Is there a linear relationship between a mother’s height and her daughter’s height?
• Is there a linear relationship between blood pressure measurements in the left and right arms of humans?
• How does air temperature depend on CO\(_{2}\)?
• Can the number of hospital admissions from respiratory illness be predicted by levels of air pollution?

We will discuss a series of examples to introduce and motivate the main ideas of regression models.