Modern Regression and Bayesian Methods

Content

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Description

Module Overview:  Modern Regression and Bayesian Methods

• Random effects models
• Modern regression (generalised additive models, etc)
• Bayesian methods
• Markov chain Monte Carlo methods
• Case studies

Assessment

This module is assessed in two assignments. Each is a short project after each block of five lectures. The deadline for the first assignment is Tuesday 20th February 2024, and for the second assignment - Monday 8th April 2024. 

Prerequisites

Basic concepts in

• probability (elementary probability distributions)
• statistics (ideas of estimation, confidence intervals, hypothesis tests)
• calculus
• linear algebra

In addition, we assume the first semester module 'Regression and Simulation Methods', or its equivalent.