Theory of Statistical Inference (U01889)

? Credit Points : 10 ? SCQF Level : 10 ? Acronym : MAT-4-TSI

Course for final year students in Honours programmes in Statistics.

Parametric families and likelihood. Sufficiency, Neyman factorisation, minimal sufficiency, joint sufficiency, Bayesian sufficiency. Estimation, minimum variance unbiased estimators, Cramr-Rao lower bound, Bayes estimators. Hypothesis testing, pure significance tests, optimal tests, power, Neyman-Pearson lemma, uniformly most powerful tests. Confidence intervals, relationship to hypothesis testing, Bayesian credible intervals. Bayesian inference, conjugate prior distributions, predictive distributions.

Entry Requirements

? Pre-requisites : Passes at C or better in (MAT-2-)FoC, SVC, LiA, MAM, Prb, SMe, StM

Variants

? This course has variants for part year visiting students, as follows

Theory of Statistical Inference (VS1) (Semester 1 (Blocks 1-2))

Subject Areas

Home subject area

Specialist Statistics (Year 4), (School of Mathematics, Schedule P)

Delivery Information

? Normal year taken : 4th year

? Delivery Period : Semester 1 (Blocks 1-2)

? Contact Teaching Time : 2 hour(s) per week for 11 weeks

All of the following classes

Type	Day	Start	End	Area
Lecture	Tuesday	14:00	14:50	KB
Lecture	Friday	14:00	14:50	KB

Summary of Intended Learning Outcomes

1. Knowledge of the theory of statistical inference.
2. Ability to prove and apply results concerning Frequentist and Bayesian inference.
3. Ability to develop theoretical arguments.
4. Familiarity with dealing with multiparameter problems.