Regression and Simulation Methods
Content
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Description
Overview
Within the Probability & Statistics theme, there are two free-standing and independently-assessed modules on statistics. (You can take either one, neither, or both.) One aim is to introduce some key topics which lie at the heart of research in statistical methods and form a basis for more advanced and sophisticated ideas. Another is to develop good computational skills using R, the statistical computing package which is in widespread use for statistical work in academia and industry.
Regression & Simulation Methods (first semester - this module)
- Introduction to R
- Linear models
- Likelihood methods and optimisation
- Generalised linear models
- Simulation and bootstrapping
- Case study
Assessment
This module is assessed through a single assignment, based on the 5 lectures on GLMs and simulation.
Prerequisites
Basic concepts in:
- probability (elementary probability distributions)
- statistics (ideas of estimation, confidence intervals, hypothesis testing)
- calculus
- linear algebra
The level required in these areas would usually be provided in a first undergraduate course.
Important: The first five sessions of Regression and Simulation methods cover material which is a standard part of many undergraduate curricula, although it is recognised that the material may be new to some. A flexible form of delivery allows participants to study different parts of this material at a speed and depth which is appropriate to their previous experience. So, the first five sessions of this module will be delivered through audio and PDF files supplied on the SMSTC website. There will be no videoconference lectures until session 6.
However, during weeks 1-5, the video conference link will be used to host workshop/Q&A sessions, where students can ask about the static course material, as they work through the scripts and exercises. These sessions will largely focus on the exercises, but there should also be an opportunity to discuss the lecture material if that would be useful.
Prof. Bowman has now retired, so please address any questions regarding the first 5 weeks to lawrence.bull@glasgow.ac.uk or come along to the Zoom meeting open Q+As.