Credit points: 15

Subject outline

Statistical inference is used to describe procedures that draw conclusions from datasets arising from systems affected by random variation.This subject comprises components in estimation and testing hypotheses. Topics in the first component include method of moments and maximum likelihood, reduction by sufficiency and invariance, unbiasedness, consistency, efficiency and robustness. The second component examines size and power of tests, Neyman-Pearson lemma, optimality of tests, the likelihood ratio test and relationship to confidence interval estimation. This subject is co-taught with STA3SI. For STA4SI there is greater emphasis on research and inquiry with an expactation that students independently formulate proofs for extension questions related to the subject material.

FacultyFaculty of Science, Tech & Engineering

Credit points15

Subject Co-ordinatorAndriy Olenko

Available to Study Abroad StudentsYes

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

Exchange StudentsYes

Subject particulars

Subject rules

Prerequisites STA2MD


Incompatible subjects STA3SI

Equivalent subjectsN/A

Special conditionsN/A

Learning resources


Resource TypeTitleResource RequirementAuthor and YearPublisher
ReadingsIntroduction to Probability and Mathematical StatisticsRecommendedBain LJ, Engelhardt M 20002ND ED, DUXBURY.

Subject options

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Start date between: and    Key dates

Melbourne, 2014, Semester 1, Day


Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorAndriy Olenko

Class requirements

Practical Week: 10 - 22
One 1.0 hours practical per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.

Lecture Week: 10 - 22
Three 1.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.


Assessment elementComments%
10 Assignments (approx. 250-300 words each)30
3-hour short answer Final Examination70