Not currently offered

Credit points: 15

Subject outline

This subject builds on the knowledge of classical statistical inference developed in STM3SI (Statistical Inference). You will be introduced to proofs of some fundamental results in the advanced theory of statistical inference, including principles of data reduction, point estimation, hypothesis testing, interval estimation, asymptotic evaluations and the effect of model selection on confidence intervals. Some of these proofs are presented by the teacher in lectures and some of these proofs are derived independently by the you as parts of your assignments. In addition, the subject introduces you to some important practical applications of advanced theory of statistical inference. This is achieved both by the teacher describing these applications in lectures and you discovering these applications through carrying out your assignments.

SchoolEngineering and Mathematical Sciences

Credit points15

Subject Co-ordinatorPaul Kabaila

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 4 - UG/Hons/1st Yr PG

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules

Prerequisites STA3SI or STM3SI or STA4SI or admission into SMDS


Incompatible subjectsSTA5TS

Equivalent subjectsN/A

Quota Management StrategyN/A

Quota-conditions or rulesN/A

Special conditionsA sufficient background in probability and statistics is required to undertake this subject.

Minimum credit point requirementN/A

Assumed knowledgeN/A

Learning resources

Statistical Inference

Resource TypeBook

Resource RequirementRecommended

AuthorRecommended text: Casella, G. and Berger, R.L .


Edition/Volume2nd edition



Chapter/article titleN/A



Other descriptionN/A

Source locationN/A

Career Ready


Work-based learningNo

Self sourced or Uni sourcedN/A

Entire subject or partial subjectN/A

Total hours/days requiredN/A

Location of WBL activity (region)N/A

WBL addtional requirementsN/A

Graduate capabilities & intended learning outcomes

Graduate Capabilities

Intended Learning Outcomes

01. Justify the steps in the proofs of the results in the theory of statistical inference given in the lectures.
02. Derive mathematical calculations to investigate properties of data reduction by sufficiency, data reduction by ancillary, data reduction by invariance, the assessment of confidence intervals and the effect of model selection on confidence intervals.
03. Write clear, well structured and rigorous proofs of results in the theory of statistical inference that you have not seen in lectures.
04. Critically review the implications for statistical practice of the advanced theory of statistical inference.

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