University of Technology SydneyHandbook 2007

C07082v5 Graduate Diploma in Statistics

Award(s): Graduate Diploma in Statistics (GradDipStats)
UAC code: 942715 (Autumn semester), 945715 (Spring semester)
CRICOS code: 015949A
Load credit points: 48
Course EFTSL: 1
Faculty/institute responsible: Science

Note(s)

Mid-year (Spring) entry is only available on a part-time basis.


Overview
Course aims
Career options
Articulation
Additional admission requirements
Additional recognition of prior learning
Course duration and attendance
Course structure
Course completion requirements
Course program
Other information

Overview

Although a knowledge of statistical methodology is becoming ever more important in many disciplines, degree courses in the sciences, engineering and business often do not provide the exposure to statistics which graduates find they need in employment. The Graduate Diploma in Statistics is suitable for such graduates and also for those who have completed degrees in pure or applied mathematics without a major in statistics.

The subjects, constituting the program, cover standard statistical techniques and their theoretical foundations. The range of topics and the level of presentation are commensurate with those found in senior undergraduate studies in the discipline.

Course aims

The Graduate Diploma in Statistics aims to train graduates in the methods and principles of applied statistics.

Career options

Career options include statistician, or a position in banking, finance, marketing or quality control.

Articulation

Subject to elective choices, successful completion of the Graduate Diploma enables graduates to proceed into the Bachelor of Science (Honours) in Mathematics (C09020), provided an acceptable standard is reached.

Additional admission requirements

Applicants should have a Bachelor's degree from UTS or other recognised institution and are expected to have knowledge in mathematics comparable with the first-year subjects in the Department of Mathematical Sciences at UTS. Applicants who do not satisfy the second of these requirements may consider enrolment in the Graduate Certificate in Mathematical Sciences (C11147).

Additional recognition of prior learning

Exemptions from core subjects, due to prior study, may be approved. Contact the Faculty for further details.

Course duration and attendance

For applicants enrolling in Autumn semester, the course is offered on a full-time basis normally over two semesters, or on a part-time basis normally over four semesters. For applicants enrolling in Spring semester, the course is only offered on a part-time basis over four semesters. Applicants should be aware that attendance at daytime classes may be unavoidable.

Course structure

Students are required to complete 48 credit points, comprising four core subjects and four electives. Elective subjects can be chosen from the list of options below but are not limited to it. Elective choice should be consistent with the aims of the program, and must be approved by the Course Director, Postgraduate Programs.

Course completion requirements

35252 Statistics 2 6cp
35356 Design and Analysis of Experiments 6cp
35361 Probability and Stochastic Processes 6cp
35353 Regression Analysis 6cp
Select 24 credit points from the following options: 24cp
35254 Health Statistics6cp 
35255 Forensic Statistics6cp 
35355 Quality Control6cp 
35363 Stochastic Models in Operations Research6cp 
35281 Numerical Methods6cp 
35212 Linear Algebra6cp 
35393 Seminar (Statistics)6cp 
Total 48cp

Course program

The example program below shows full-time attendance for Autumn-commencing students.

 
Year 1
Autumn semester
35212 Linear Algebra 6cp
35356 Design and Analysis of Experiments 6cp
35252 Statistics 2 6cp
35363 Stochastic Models in Operations Research 6cp
Spring semester
35361 Probability and Stochastic Processes 6cp
35353 Regression Analysis 6cp
Select 12 credit points from the following options: 12cp
35255 Forensic Statistics6cp 
35281 Numerical Methods6cp 
35355 Quality Control6cp 
35393 Seminar (Statistics)6cp 
35254 Health Statistics6cp 

Other information

Further information is available from: