Statistical Models
Lecture Slides
Welcome
These are the Slides of the module Statistical Models 551305 for T2 2025/26 at the University of Hull. If you have any question or find any typo, please email me at
Up to date information about the module will be published on the University of Hull Canvas Webpage
and on the Course Webpage hosted on my website
Slides
There are 11 lectures in this module and 3 optional appendices. Links to the slides and lecture titles are below.
| Slides | Title |
|---|---|
| Lecture 1 | An introduction to Statistics |
| Lecture 2 | Random samples & The t-test |
| Lecture 3 | Introduction to R & The variance ratio test |
| Lecture 4 | Two-sample t-test & More on R |
| Lecture 5 | Two-sample F-test & Goodness-of-fit test |
| Lecture 6 | Chi-squared test & Least Squares |
| Lecture 7 | The maths of Regression |
| Lecture 8 | Practical regression |
| Lecture 9 | |
| Lecture 10 | Model Selection & Regression Assumptions |
| Lecture 11 | Stepwise Regression & ANOVA |
| Appendix A | Probability revision |
| Appendix B | R Style Guide |
| Appendix C | Simulation & Bootstrap |
Statistical tables
- Download here
R Codes
| Lecture | Codes |
|---|---|
| Lecture 3 | One-Sample t-test Variance ratio test |
| Lecture 4 | Two-Sample t-test |
| Lecture 5 | F-test F-test First Principles Goodness-of-fit Goodness-of-fit First Principles Goodness-of-fit Contingency |
| Lecture 6 | Independence Test 2008 Crisis Least-squares Solution 1 Least-squares Solution 2 |
| Lecture 7 | Multiple Regression R2 multiple regression |
| Lecture 8 | Simple Regression Longley regression |
| Lecture 9 | |
| Lecture 10 | Longley selection Galileo Divorces Heteroscedasticity Autocorrelation |
| Lecture 11 | Multicollinearity Stepwise regression: Longley Stepwise regression: Divorces Anova Ancova |
| Appendix C | Monte Carlo \(\pi\) Bootstrap CI Bootstrap t-test Bootstrap F-test |
Datsets
Readings
Main textbooks: These slides are self-contained and largely based on the books
Secondary References: In addition we reccomend the following
References
[1]
Bingham, Nicholas H., Fry, John M., Regression, linear models in statistics, Springer, 2010.
[2]
Fry, John M., Burke, Matt, Quantitative methods in finance using R, Open University Press, 2022.
[3]
Casella, George, Berger, Roger L., Statistical inference, second edition, Brooks/Cole, 2002.
[4]
DeGroot, Morris H., Schervish, Mark J., Probability and statistics, Fourth Edition, Addison-Wesley, 2012.
[5]
Dalgaard, Peter, Introductory statistics with R, Second Edition, Springer, 2008.
[6]
Davies, Tilman M., The book of R, No Starch Press, 2016.