On apsects of statistical modelling
Preliminary material
Introduction
In order to get the most out of the AUEB MSc short course “On aspects of statistical modelling”, students should have, at the start of the module, a sound knowledge of the principles of statistical inference and the theory of linear and generalised linear models. Students should also have some experience of statistical modelling in R.
The following reading and activities are recommended to all students to (re)-familiarise themselves with those topics.
Linear and generalised linear models: A student who has covered Davison (2003, Chapter 8 and 10.1-10.4) will be more than adequately prepared for the short course. For students without access to this book, the main theory is repeated in the current set of preliminary notes. The inference methodology described is largely based on classical statistical theory. Although prior experience of Bayesian statistical modelling would be helpful, it will not be assumed.
Preliminary material exercises: Nine exercises are included in the current preliminary material.
R practicals: Some practical exercises are also provided at the end of these notes to enable students to familiarise themselves with statistical modelling in R.
Typos and issues
You can report and suggest fixes to typos and issues by email to ioannis.kosmidis@warwick.ac.uk.