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STATISTICAL INFERENCE (R)

Module code: MT862S
Credits: 5
Semester: 2
Department: MATHEMATICS AND STATISTICS
International:

	Overview
	Module Objective: To introduce students to Statistical Inference. Point estimation: method of moments and maximum likelihood. Consistency, bias and mean squared error. Information and the Cramer-Rao lower bound. Asymptotic distribution of MLEs. Confidence intervals. Testing hypotheses: power, Neymann Pearson, Likelihood ratio tests, large sample approximations. Bayesian estimation: prior and posterior distributions, loss functions, Bayes rule. Lectures and tutorials as for MT462S.

Overview

Module Objective: To introduce students to Statistical Inference. Point estimation: method of moments and maximum likelihood. Consistency, bias and mean squared error. Information and the Cramer-Rao lower bound. Asymptotic distribution of MLEs. Confidence intervals. Testing hypotheses: power, Neymann Pearson, Likelihood ratio tests, large sample approximations. Bayesian estimation: prior and posterior distributions, loss functions, Bayes rule.

Lectures and tutorials as for MT462S.

Teaching & Learning methods

Assessment

	Repeat options
	NA

	Pre-Requisites
	Registered Research student. Permission is required from the Head of the Mathematics & Statistics Department.

	Timetable
	This timetable is not currently available, please contact the Mathematics And Statistics Department.

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Courses / Module

STATISTICAL INFERENCE (R)