ST903: Statistical Methods

Lecturer(s)

Dr Larbi Alili

Commitment: 3 hours per week for 10 weeks. This module runs in Term 1.

Summary: The module content will include a thorough grounding in classical methods of statistical inference with an introduction to selected more recent developments in statistical methodology. Since MSc students have different background knowledge in statistics we start afresh. At the end of the course you will have a solid background in basic statistics and knowledge at an advanced level in some areas.

Content:

    1. Data
    2. Probability
    3. Random Variables
    4. Special univariate distributions
    5. Joint and Conditional distributions
    6. Distributions of functions of random variables
    7. Methods of inference
    8. Inference using simulation
    9. Maximum Likelihood Estimation
    10. Elements of Bayesian Inference
    11. General linear model (including ANOVA)
    12. Generalised linear model

Books: Casella, G. and Berger, R. L., Statistical Inference, 2nd Ed, Duxbury.

Wasserman L.,All of Statistics: A Concise Course in Statistical Inference, Springer

Lecture notes will cover everything that is done in the course.

Assessment: 90% Exam in Week 1 of Term 2, 10% Course Work

 

Resources for Current Students