🗓️ Lecture 10: Regression analysis
🎯 Content and goals
- You understand the logic behind multiple linear regression and how to interpret it.
- You understand the logic behind different models for interaction effects.
- You can choose the right functional form based on the visual analysis of the data.
- You know the steps of a regression analysis.
🖥️ Lecture Slides
The slides for this lecture will be made available here.
📚 Mandatory Reading
- Ismay et al. (2025: 5–6)
🏆 Further Readings
- James et al. (2021: 3)
✍️ Exercises and coursework
Take-home exercise:
- Conduct a regression analysis for the example data provided and present the results in a Quarto report.
If you have questions or problems, please post them in the Moodle forum.
References
Ismay, C., Kim, A. Y. and Valdivia, A. (2025) Statistical inference via data science: A ModernDive into R and the tidyverse, 2nd edition., CRC Press, available at https://moderndive.com/v2/index.html.
James, G., Witten, D., Hastie, T. and Tibshirani, R. (2021) An introduction to statistical learning: With applications in R, Second edition., New York, NY: Springer.