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2010/1 Module Catalogue
 Module Code: MAT2013 Module Title: MATHEMATICAL STATISTICS
Module Provider: Mathematics Short Name: MS237
Level: HE2 Module Co-ordinator: YOUNG KD Dr (Maths)
Number of credits: 15 Number of ECTS credits: 7.5
 
Module Availability
Semester 2
Assessment Pattern

Unit(s) of Assessment

 

Weighting Towards Module Mark( %)

 

2 hour unseen examination

 

75

 

Test

 

10

 

Coursework

 

15

 

Qualifying Condition(s) 

 

A weighted aggregate mark of 40% is required to pass the module.

 

 

Module Overview
The module gives a presentation of some fundamental mathematical theory underlying statistics.
Prerequisites/Co-requisites
The probability component of MAT1025 is a pre-requisite.
Module Aims
This module provides theoretical background for many of the topics introduced in the probability component of MS1025 and for some of the topics that will appear in subsequent statistics modules.
Learning Outcomes
At the end of the module, a student should: 
(1) be familiar with the main results of intermediate distribution theory; 
(2) be able to apply this knowledge to suitable problems in statistics.
Module Content

Review of probability and basic univariate distributions.

 

 

 

Bivariate and multivariate distributions.

 

 

 

Transformations.

 

 

 

Moments, generating functions and inequalities.

 

 

 

Further discrete and continuous distributions: negative binomial, hypergeometric, multinomial, gamma, beta.

 

 

 

Univariate, bivariate and multivariate normal distributions.

 

 

 

Proof of the central limit theorem.

 

 

 

Distributions associated with the normal distribution: Chi-square, t and F.

 

 

 

Application to normal linear models.

 

 

 

Theory of minimum variance unbiased estimation.
Methods of Teaching/Learning
Teaching is by lectures and example classes. Learning takes place through lectures, exercises (example sheets) and background reading.
Selected Texts/Journals

Recommended

 

J.E. Freund, Mathematical Statistics with Applications, Pearson, (2004).

 

R.V. Hogg and E.A. Tanis, Probability and Statistical Inference, Prentice-Hall, (1997).

 

 

 

Further Reading

 

A.M. Mood, F.G. Graybill and D.C. Boes, Introduction to the Theory of Statistics, McGraw-Hill, (1974).
Last Updated
September 10