In this project we hope to examine generalised linear regression models and see how they can be applied to data from the English Premier League. \
We will first look at logistic regression models, to see how match result is affected by a few different effects. Logistic regression can be used to model Bernoulli processes with variable probability dependent on different factors, making it a useful tool for predicting outcome in sports. \
Afterwards we will look at proportional hazards models and see how they can be used for analysis of first-goal times. Proportional hazards models that we hope to focus on are parametric models of exponential or Weibull type, and the Cox proportional-hazards model. \

#heading([Notes], outlined: false, numbering: none)
// No numbering - Don't want this to show up in contents or change numbering of later sections.
Word count excluding bibliography, appendices is approx 11.7k.\

This document was typeset using Typst. The code used for generating page headers was written by <NAME>, and used under the terms of the Apache open source license. Their original work and the associated license can be found at the following link.
#link("https://github.com/zagoli/simple-typst-thesis")\

All code pertaining to statistics was written in R, though some helper scripts were written in Python. All relevant code will be in the appendices, and some time after the Turnitin check all source files will be uploaded to my Github: #link("https://github.com/ralphmb")


This project received ethics approval from Coventry University, the certificate can be found at the end of the appendices.


Thank you to Prof. <NAME> for his practical support and guidance, and thank you to Deimantė Bogužaitė for her moral support and cooking. \
