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C06097v1 Graduate Diploma in Mathematics and Statistics for Business and Finance

Award(s): Graduate Diploma in Mathemtics and Statistics for Business and Finance (GradDipMathStat)
UAC code: 942741 (Autumn semester), 945741 (Spring semester)
CRICOS code: 065346C
Load credit points: 48
Course EFTSL: 1
Location: City campus

Overview
Course aims
Admission requirements
Course duration and attendance
Course structure
Course completion requirements
Course program
Other information

Overview

A sound knowledge of mathematical and statistical methods is in ever growing demand in various government organisations, ranging from defence to education, and in such diverse fields as finance and public health, construction industry and agriculture, manufacturing and transportation. Despite the demonstrated and continuing demand for specialists trained in mathematics and statistics, most university graduates do not acquire the required knowledge in their bachelor's programs.

This course is designed for bachelor's degree holders who need more mathematics and/or statistics in their everyday work or who wish to broaden their career choices.

Course aims

This course aims to provide a solid mathematical and statistical background by means of a flexible study program that can be tailored to suit various categories of university graduates who need this knowledge in their work or plan to pursue further studies.

Admission requirements

Applicants should have a bachelor's degree from UTS or other recognised institution. They are also expected to have knowledge in mathematics comparable with the following UTS Mathematical Sciences foundation stream subjects:

  • 35101 Introduction to Linear Dynamical Systems
  • 35102 Introduction to Analysis and Multivariable Calculus
  • 35151 Introduction to Statistics

Applicants who do not satisfy this requirement should instead consider enrolment in the Graduate Certificate in Mathematics (C11210).

Course duration and attendance

The duration of the course depends on the choice of subjects and their availability. As a guide, minimum full-time attendance is one year of study, and part-time attendance is two years of study. Applicants should be aware that subjects may require attendance at daytime classes. The current timetable is available at:

Course structure

Students are required to complete 48 credit points, comprising three core subjects and five electives (options). 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.

Note: Subjects listed as electives (options) are only offered in a particular semester (or year) if there is sufficient demand and the necessary resources.

Course completion requirements

35353 Regression Analysis 6cp
35363 Stochastic Models 6cp
35241 Optimisation in Quantitative Management 6cp
Select 30 credit points from the following options: 30cp
35100 Introduction to Sample Surveys6cp 
35111 Applications of Discrete Mathematics6cp 
35140 Introduction to Quantitative Management6cp 
35212 Computational Linear Algebra6cp 
35231 Differential Equations6cp 
35232 Advanced Calculus6cp 
35252 Mathematical Statistics6cp 
35255 Forensic Statistics6cp 
35321 Analysis 16cp 
35322 Advanced Analysis6cp 
35335 Mathematical Methods6cp 
35340 Quantitative Management Practice6cp 
35342 Nonlinear Methods in Quantitative Management6cp 
35344 Network and Combinatorial Optimisation6cp 
35355 Quality Control6cp 
35356 Design and Analysis of Experiments6cp 
35361 Stochastic Processes6cp 
35383 High Performance Computing6cp 
35391 Seminar (Mathematics)6cp 
35393 Seminar (Statistics)6cp 
Total 48cp

Course program

Three example programs are shown below.

The first program shows full-time attendance for Autumn-commencing students and is recommended for those who are interested in acquiring a solid mathematical background for pursuing a career in finance.

The second program shows full-time attendance for Autumn-commencing students and is recommended for those who need in-depth knowledge in quantitative management.

The third program shows full-time attendance for Autumn-commencing students and is recommended for those who wish to pursue career in statistics.

 
Finance, Autumn commencing, full time
Year 1
Autumn semester
35232 Advanced Calculus 6cp
35241 Optimisation in Quantitative Management 6cp
35252 Mathematical Statistics 6cp
35363 Stochastic Models 6cp
Spring semester
35322 Advanced Analysis 6cp
35342 Nonlinear Methods in Quantitative Management 6cp
35353 Regression Analysis 6cp
35361 Stochastic Processes 6cp
 
Quantitative Management, Autumn commencing, full time
Year 1
Autumn semester
35140 Introduction to Quantitative Management 6cp
35212 Computational Linear Algebra 6cp
35241 Optimisation in Quantitative Management 6cp
35363 Stochastic Models 6cp
Spring semester
35340 Quantitative Management Practice 6cp
35342 Nonlinear Methods in Quantitative Management 6cp
35344 Network and Combinatorial Optimisation 6cp
35353 Regression Analysis 6cp
 
Statistics, Autumn commencing, full time
Year 1
Autumn semester
35241 Optimisation in Quantitative Management 6cp
35252 Mathematical Statistics 6cp
35356 Design and Analysis of Experiments 6cp
35363 Stochastic Models 6cp
Spring semester
35100 Introduction to Sample Surveys 6cp
35353 Regression Analysis 6cp
35361 Stochastic Processes 6cp
Select one of the following: 6cp
      35393 Seminar (Statistics)6cp 
      35355 Quality Control6cp 

Other information

Further information is available from the UTS Student Centre on: