THEORY OF STATISTICS

STA4TS

2014

Credit points: 15

Subject outline

This subject builds on the knowledge of classical statistical inference developed in either STA3SI (Statistical Inference) or STA4SI (Statistical Inference). It consists of a selection of material from the following chapters of Casella and Berger (2002): Chapter 6 (Principles of Data Reduction), Chapter 7 (Point Estimation), Chapter 8 (Hypothesis Testing), Chapter 9 (Interval Estimation) and Chapter 10 (Asymptotic Evaluations). This also includes an introduction to the effect of model selection on confidence intervals.

Faculty: Faculty of Science, Tech & Engineering

Credit points: 15

Subject Co-ordinator: Paul Kabaila

Available to Study Abroad Students: Yes

Subject year level: Year Level 4 - UG/Hons/1st Yr PG

Exchange Students: Yes

Subject particulars

Subject rules

Prerequisites: STA3SI or STA4SI

Co-requisites: N/A

Incompatible subjects: STA5TS

Equivalent subjects: N/A

Special conditions: Non-LTU students (i.e. RMIT or Monash University students) are expected to have a pre-requisite intermediate knowledge of linear models including associated linear algebra results and also of theory related to statistical inference.

Learning resources

Readings

Resource Type	Title	Resource Requirement	Author and Year	Publisher
Readings	Statistical Inference, 2nd edition (2002)	Recommended	Recommended text: Casella, G. and Berger, R.L.	N/A

Melbourne, 2014, Semester 1, Day

Overview

Online enrolment: Yes

Maximum enrolment size: N/A

Enrolment information:

Subject Instance Co-ordinator: Paul Kabaila

Class requirements

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

Assessments

Assessment element	Comments	%
Final examination (2-hour short answer)		60
Seven assignments (approx. 400 words each)		40

Melbourne, 2014, Semester 2, Day