STATISTICAL INFERENCE

STA3SI

2014

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.

Faculty: Faculty of Science, Tech & Engineering

Credit points: 15

Subject Co-ordinator: Andriy Olenko

Available to Study Abroad Students: Yes

Subject year level: Year Level 3 - UG

Exchange Students: Yes

Subject particulars

Subject rules

Prerequisites: STA2MD

Co-requisites: N/A

Incompatible subjects: N/A

Equivalent subjects: N/A

Special conditions: N/A

Learning resources

Readings

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

Melbourne, 2014, Semester 1, Day

Overview

Online enrolment: Yes

Maximum enrolment size: N/A

Enrolment information:

Subject Instance Co-ordinator: Andriy Olenko

Class requirements

LectureWeek: 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.

PracticalWeek: 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.

Assessments

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