Statistical Models
Lecture Slides
Welcome
These are the Slides of the module Statistical Models 551305 for T2 2024/25 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. Links to the slides and lecture titles are below.
| Slides | Title |
|---|---|
| Lecture 1 | An introduction to Statistics |
| Lecture 2 | Random samples |
| Lecture 3 | The t-test and an introduction to R |
| Lecture 4 | The variance ratio and two-sample t-test |
| Lecture 5 | Two-sample F-test and goodness-of-fit test |
| Lecture 6 | The chi-squared test and non-parametric tests |
| Lecture 7 | The maths of regression |
| Lecture 8 | General linear regression |
| Lecture 9 | Practical regression |
| Lecture 10 | Violation of regression assumptions |
| Lecture 11 | ANOVA |
| Appendix A | Probability revision |
| Appendix B | More on R |
Statistical tables
- Download here
R Codes
| Lecture | Codes |
|---|---|
| Lecture 3 | One-Sample t-test |
| Lecture 4 | Variance ratio test Two-Sample t-test |
| Lecture 5 | F-test F-test First Principles |
| Lecture 6 | Goodness-of-fit Goodness-of-fit First Principles Monte Carlo \(\pi\) Monte Carlo p-value Goodness-of-fit Contingency Independence Test |
| Lecture 7 | Least-squares Solution 1 Least-squares Solution 2 |
| Lecture 8 | Multiple Regression R2 multiple regression |
| Lecture 9 | Simple Regression Longley regression Longley selection Galileo Divorces |
| Lecture 10 | Residual graphs Autocorrelation graphic tests Multicollinearity Stepwise regression: Longley Stepwise regression: Divorces |
| Lecture 11 | Anova models |
| Appendix B | 2008 Crisis |
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.