Master of Statistics and Operations Research

Royal Melbourne Institute of Technology

About

The Master of Statistics and Operations Research program aims to provide opportunities to further your understanding in the modelling of physical, biological and economic phenomena so that you will be able to contribute to applied research and development in industry, commerce and research.

The consulting component and/or minor thesis will develop your consulting and research skills.The program furthers your knowledge of statistical and operations research methodologies and provides a theoretical foundation combined with practical applications of current techniques employed by practising engineers, scientists and other professionals in industry, research, consulting, teaching and business.MATH2349 Data Wrangling will serve as a WIL course in your first year.MATH2191 Applied Research Project will serve as a capstone experience - a culmination and application of your prior studies in this program.This program is delivered on campus;

some courses may be available online.

Structure

Year One of Program

Complete the following Four (4) Courses:

Course Title Credit Points Course Code Campus
Mathematical Modelling and Decision Analysis 12 MATH1293 City Campus
Applied Analytics 12 MATH1324 City Campus
Database Concepts 12 ISYS1055 City Campus
Data Wrangling 12 MATH2349 City Campus

Select and Complete Two (2) of the following Courses:

Course Title Credit Points Course Code Campus
Essential Mathematics 12 MATH2267 City Campus
Data Visualisation and Communication 12 MATH2270 City Campus
Applied Bayesian Statistics 12 MATH2269 City Campus
Analysis of Categorical Data 12 MATH1298 City Campus
Design and Analysis of Experiments 12 MATH1302 City Campus
Forecasting 12 MATH1307 City Campus
Multivariate Analysis Techniques 12 MATH1309 City Campus
Regression Analysis 12 MATH1312 City Campus
Statistical Inference 12 MATH1315 City Campus
Statistics of Quality Control and Performance Analysis 12 MATH1316 City Campus
Stochastic Processes and Applications 12 MATH1317 City Campus
Time Series Analysis 12 MATH1318 City Campus
Game Theory and its Applications 12 MATH1320 City Campus
Methods and Models of Operations Research 12 MATH1326 City Campus
Questionnaire and Research Design 12 MATH2218 City Campus
Systems Simulation 12 MATH2219 City Campus
System Dynamics 12 MATH2220 City Campus
Sports Analytics 12 MATH2223 City Campus
Machine Learning 12 MATH2319 City Campus
Introduction to Statistical Computing 12 MATH1322 City Campus

Select and Complete Two (2) Courses from the Science Option list below:

AND

Year Two of Program

Complete the following One (1) Course:

Course Title Credit Points Course Code Campus
Applied Research Project 12 MATH2191 City Campus

Select and complete Sixty (60) Credit Points from the following Courses:

Course Title Credit Points Course Code Campus
Data Visualisation and Communication 12 MATH2270 City Campus
Applied Bayesian Statistics 12 MATH2269 City Campus
Analysis of Categorical Data 12 MATH1298 City Campus
Design and Analysis of Experiments 12 MATH1302 City Campus
Forecasting 12 MATH1307 City Campus
Multivariate Analysis Techniques 12 MATH1309 City Campus
Regression Analysis 12 MATH1312 City Campus
Statistical Inference 12 MATH1315 City Campus
Statistics of Quality Control and Performance Analysis 12 MATH1316 City Campus
Stochastic Processes and Applications 12 MATH1317 City Campus
Time Series Analysis 12 MATH1318 City Campus
Game Theory and its Applications 12 MATH1320 City Campus
Methods and Models of Operations Research 12 MATH1326 City Campus
Minor Thesis 24 MATH1332 City Campus
Questionnaire and Research Design 12 MATH2218 City Campus
Systems Simulation 12 MATH2219 City Campus
System Dynamics 12 MATH2220 City Campus
Sports Analytics 12 MATH2223 City Campus
Machine Learning 12 MATH2319 City Campus
Introduction to Statistical Computing 12 MATH1322 City Campus

Select and Complete Two (2) Courses from the Science Option list below. Science Option Course List:

Course Title Credit Points Course Code Campus
Scripting Language Programming 12 COSC1092 City Campus
Artificial Intelligence 12 COSC1125 City Campus
Intelligent Web Systems 12 COSC1165 City Campus
Programming Techniques 12 COSC1283 City Campus
Algorithms and Analysis 12 COSC1285 City Campus
Advanced Programming 12 COSC1295 City Campus
Data Mining 12 COSC2111 City Campus
Advanced Programming Techniques 12 COSC2207 City Campus
Database Systems 12 COSC2407 City Campus
Programming Fundamentals 12 COSC2531 City Campus
Big Data Management 12 COSC2636 City Campus
Big Data Processing 12 COSC2637 City Campus
Case Studies in Data Science 12 COSC2669 City Campus
Practical Data Science with Python 12 COSC2670 City Campus
Social Media and Networks Analytics 12 COSC2671 City Campus
GIS Fundamentals 12 GEOM1159 City Campus
GIS Principles 12 GEOM1163 City Campus
Advanced GIS 12 GEOM2151 City Campus
GIS Analytics 12 GEOM2152 City Campus
Introduction to Information Security 12 INTE1120 City Campus
Case Studies in Cyber Security 12 INTE1122 City Campus
Information Theory for Secure Communications 12 INTE1128 City Campus
Information Systems Risk Management 12 INTE2396 City Campus
Knowledge and Data Warehousing 12 ISYS1072 City Campus
Web Search Engines and Information Retrieval 12 ISYS1078 City Campus
Data Visualisation and Communication 12 MATH2270 City Campus
Applied Bayesian Statistics 12 MATH2269 City Campus
Analysis of Categorical Data 12 MATH1298 City Campus
Design and Analysis of Experiments 12 MATH1302 City Campus
Forecasting 12 MATH1307 City Campus
Multivariate Analysis Techniques 12 MATH1309 City Campus
Regression Analysis 12 MATH1312 City Campus
Statistical Inference 12 MATH1315 City Campus
Statistics of Quality Control and Performance Analysis 12 MATH1316 City Campus
Stochastic Processes and Applications 12 MATH1317 City Campus
Time Series Analysis 12 MATH1318 City Campus
Game Theory and its Applications 12 MATH1320 City Campus
Methods and Models of Operations Research 12 MATH1326 City Campus
Questionnaire and Research Design 12 MATH2218 City Campus
Systems Simulation 12 MATH2219 City Campus
System Dynamics 12 MATH2220 City Campus
Sports Analytics 12 MATH2223 City Campus
Machine Learning 12 MATH2319 City Campus
Introduction to Statistical Computing 12 MATH1322 City Campus

Entry requirements

A bachelor degree

OR

At least 10 years of relevant work experience

International qualifications are assessed according to the Australian Qualifications Framework (AQF).

English language requirements

IELTS - 6.5+ (no band less than 6.0) For equivalents to English entry requirements, see the English equivalents web page

Exemptions

Some applicants might be eligible for exemptions that might change the duration of their program. Please refer to the Articulation and Pathways section for more detail.

Learning outcomes

The program has a student-focused approach that aims at developing your skills in the use of statistics and operations research in solving real world problems that arise in industry, research and business environments. This is achieved using statistical software accompanied by an in-depth understanding of the statistical processes involved. By completing this program, you will be particularly knowledgeable, creative and critical in the sense of how you interpret and analyse data. You will also be equipped with the ability to apply knowledge to solve a wide range of real world problems.

The following are the key capabilities developed in the program which will make you, as a graduate, relevant to current industry and business requirements:

Personal and professional awareness

  • the ability to contextualise outputs where data are drawn from diverse and evolving social, political and cultural dimensions
  • the ability to reflect on experience and improve your own future practice
  • the ability to apply the principles of lifelong learning to any new challenge.

Knowledge and technical competence

  • an understanding of appropriate and relevant, fundamental and applied mathematical and statistical knowledge, methodologies and modern computational tools.

Problem-solving

  • the ability to bring together and flexibly apply knowledge to characterise, analyse and solve a wide range of problems
  • an understanding of the balance between the complexity / accuracy of the mathematical / statistical models used and the timeliness of the delivery of the solution.

Teamwork and project management

  • the ability to contribute to professional work settings through effective participation in teams and organisation of project tasks
  • the ability to constructively engage with other team members and resolve conflict.

Communication

  • the ability to effectively communicate both technical and non-technical material in a range of forms (written, electronic, graphic, oral), and to tailor the style and means of communication to different audiences. Of particular interest is the ability to explain technical material, without unnecessary jargon, to lay persons such as the general public or line managers.

Information literacy

  • the ability to locate and use data and information and evaluate its quality with respect to its authority and relevance.

Ethics

  • develop the cognitive skills to review critically, analyse, consolidate and synthesise knowledge to identify and provide solutions to complex problems with intellectual independence.
  • use initiative and judgement in planning, problem solving and decision making in professional practice and/or scholarship.
  • take responsibility and accountability for own learning and professional practice and in collaborations with others within broad parameters.

Institution