Quiz and summary
Contents
2.4. Quiz and summary¶
2.4.1. Quiz 2¶
Complete Quiz 2 to check your understanding of this topic. You are advised to score at least 50% to proceed to the next topic.
2.4.2. Summary¶
In this chapter, we learnt about one of the core machine learning techniques, Linear Regression. We started with simple linear regression, learning how we fit a line to data by minimising the residual sum of squares (RSS) between observed and predicted response values. Then, we moved on to multiple linear regression, accounting for multiple variables in the same model. We then discussed the assumptions of linear regression and how to check them before finally discussing the limitations of the method when it comes to nonlinear data.
In this topic, you learnt how to:
Use simple linear regression to fit a line to data.
Perform multiple linear regression to account for multiple variables in the same model.
The assumptions and limitations of using linear regression.
2.4.3. References and further reading¶
This material is based on the following resources:
The Textbook: James G, Witten D, Hastie T, Tibshirani R., An Introduction to Statistical Learning, Second Edition, Springer, 2021. PDF [James et al., 2021]