Applied Statistical Inference

Subject 620-372 (2008)

Note: This is an archived Handbook entry from 2008.Search for this in the current handbookSearch for this in the current handbook

Credit Points: 12.500
Level: Undergraduate
Dates & Locations:

This subject has the following teaching availabilities in 2008:

Semester 2, - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period not applicable
Assessment Period End not applicable
Last date to Self-Enrol not applicable
Census Date not applicable
Last date to Withdraw without fail not applicable

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: 36 lectures (three per week) and up to 12 practice classes (one per week)
Total Time Commitment: 120 hours
Prerequisites: 620-371 and 620-202.
Corequisites: None
Recommended Background Knowledge: None
Non Allowed Subjects: Credit may not be gained for both 620-372 and 300-315.
Core Participation Requirements: It is University policy to take all reasonable steps to minimise the impact of disability upon academic study and reasonable steps will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact upon their active and safe participation in a subject are encouraged to discuss this with the relevant subject coordinator and the Disability Liaison Unit.


Dr G Qian
Subject Overview:

This subject extends the theory of inference developed in 620-202 Statistics and demonstrates how it is applied in practice. Students will develop an understanding of the principles of statistical inference and will learn to use a number of important specific techniques in applied statistics.

Topics covered include principles and fundamental results in estimation and hypothesis testing, including consistency, sufficiency, minimum variance unbiased estimation, likelihood methods and associated asymptotic theory, optimal tests and likelihood ratio tests; and generalised linear models. Application of the above methodologies to logistic regression (analysis of grouped and ungrouped binary data), log-linear models (analysis of two- and higher-dimensional contingency tables) and survival analysis (Kaplan-Meier estimates, parametric models, non-parametric models) is also studied.

Assessment: Up to 50 pages of written assignments due during semester (20%); a 3-hour written examination in the examination period (80%).
Prescribed Texts: None
Breadth Options: This subject is a level 2 or level 3 subject and is not available to new generation degree students as a breadth option in 2008.
This subject or an equivalent will be available as breadth in the future.
Breadth subjects are currently being developed and these existing subject details can be used as guide to the type of options that might be available.
2009 subjects to be offered as breadth will be finalised before re-enrolment for 2009 starts in early October.
Fees Information: Subject EFTSL, Level, Discipline & Census Date

This subject is available for science credit to students enrolled in the BSc (pre-2008 degree only), BASc or a combined BSc course.

Passing 620-372 precludes subsequent credit for 620-270 or 620-272.

Related Course(s): Bachelor of Arts
Bachelor of Arts and Bachelor of Science
Bachelor of Arts and Sciences
Bachelor of Science

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