Bachelor of Science (Statistics)

Royal Melbourne Institute of Technology

About

The program BP245 Bachelor of Science (Statistics) will:enable you to become highly employable in the field of statistics provide you with a sound knowledge of basic (and some advanced) statistical theory expose you to a wide range of statistical models, approaches and software enable you to select and apply the appropriate statistical theories, techniques and software to solve a wide range of problems expose you to related fields of study which require statistical expertise, such as finance, marketing or environmental modelling develop your knowledge of the types of industry which employ statisticians and the variety of tasks they undertake develop your range of generic skills and abilities to operate effectively in professional settings that involve mathematical and statistical expertise.

These include good communication skills, technology literacy and the ability to work in a team and interact with others identify the need for an ethical approach to your work.Year 1 is designed to build a common platform of mathematical and statistical knowledge, conceptual and analytical skills that are essential for Years 2 & 3.

It also includes an overview of the different components of applied mathematics which can be explored in depth in subsequent years.

In Years 2 and 3 of BP245 Bachelor of Science (Statistics), there is a large number of option courses which allow you to tailor your studies according to your interests in areas like finance, marketing, biology and ecology modelling and analytics.

You are also able to select two University-wide electives.

In Semester 1 of Year 3 you have the possibility of undertaking a student mobility program overseas, either in industry or in a partner university.MATH2197 Industrial Applications of Mathematics and Statistics 2 serves as a capstone experience - a culmination and application of knowledge and skills from your prior studies.

You will participate in a group project or industry placement under the supervision of the teaching team and eventually under the supervision of a representative from a partner institution.

Regular interactions with your supervisor(s) will allow you to obtain technical advice, to construct a milestone(s) plan and get feedback on your progress.

You will respond to real world problems using the knowledge and competencies acquired during your program to propose solutions.MATH2197 Industrial Applications of Mathematics and Statistics 2 and its pre-cursor, MATH2196 Industrial Applications of Mathematics and Statistics 1 are the designated WIL courses for the BP245 program.This program requires on-campus attendance.

Courses include on-line components.

Structure

Year One of Program

Complete the following Eight (8) Courses:

Course Title Credit Points Course Code Campus
Calculus and Analysis 1 12 MATH1142 City Campus
Introduction to Probability and Statistics 12 MATH2200 City Campus
Mathematical Computing and Algorithms 12 MATH2109 City Campus
Discrete Mathematics 12 MATH1150 City Campus
Problem Solving and Algorithms 12 MATH2313 City Campus
Calculus and Analysis 2 12 MATH1144 City Campus
Basic Statistical Methodologies 12 MATH2201 City Campus
Data Preparation for Analytics 12 MATH2202 City Campus
AND

Year Two of Program

Complete the following Four (4) Courses:

Course Title Credit Points Course Code Campus
Linear Algebra and Vector Calculus 12 MATH2140 City Campus
Industrial Applications of Mathematics and Statistics 1 12 MATH2196 City Campus
Linear Models and Experimental Design 12 MATH2203 City Campus
Statistical Inference 12 MATH2155 City Campus

Select and Complete Three (3) Courses from the following list:

Select and Complete One (1) Course from the following list:

AND

Year Three of Program

Complete the following Two (2) Courses:

Course Title Credit Points Course Code Campus
Multivariate Analysis 12 MATH2142 City Campus
Industrial Applications of Mathematics and Statistics 2 12 MATH2197 City Campus

Select and Complete Two (2) Courses from the following list:

Select and Complete Two (2) Courses from the following list:

Select and Complete Two (2) Courses from:

AND

List of Option Courses:

Option List 1 (Year Two and Year Three)

Course Title Credit Points Course Code Campus
Data Visualisation 12 MATH2237 City Campus
Analysis of Categorical Data 12 MATH2300 City Campus
Sampling and Quality Control 12 MATH2205 City Campus
Time Series and Forecasting 12 MATH2204 City Campus
Predictive Modelling 12 MATH2301 City Campus
Applied Bayesian Statistics 12 MATH2305 City Campus
Sports Statistics 12 MATH2206 City Campus
Systems Simulation 12 MATH2309 City Campus
Scientific Computing 12 MATH1155 City Campus
Complex Networks 12 MATH2312 City Campus
Modelling with Differential Equations 12 MATH2138 City Campus
Graph Algorithms and Applications 12 MATH2308 City Campus
Applied Linear Algebra 12 MATH2311 City Campus
Linear Programming and Modelling 12 MATH1288 City Campus
System Dynamic Modelling 12 MATH2127 City Campus
Advanced Mathematical Modelling 12 MATH2139 City Campus
Nonlinear Optimisation 12 MATH2143 City Campus
Numerical Solutions of DEs 12 MATH2144 City Campus
Algebra for Information Security 12 MATH2148 City Campus
Mathematical Modelling 12 MATH2194 City Campus
AND

List of Option Courses:

Option List 2 (Year Two and Year Three)

Course Title Credit Points Course Code Campus
Business Finance 12 BAFI1008 City Campus
Financial Markets 12 BAFI1002 City Campus
Prices and Markets 12 ECON1020 City Campus
Data Visualisation 12 MATH2237 City Campus
Analysis of Categorical Data 12 MATH2300 City Campus
Sampling and Quality Control 12 MATH2205 City Campus
Time Series and Forecasting 12 MATH2204 City Campus
Predictive Modelling 12 MATH2301 City Campus
Applied Bayesian Statistics 12 MATH2305 City Campus
Sports Statistics 12 MATH2206 City Campus
Systems Simulation 12 MATH2309 City Campus
Scientific Computing 12 MATH1155 City Campus
Complex Networks 12 MATH2312 City Campus
Modelling with Differential Equations 12 MATH2138 City Campus
Graph Algorithms and Applications 12 MATH2308 City Campus
Applied Linear Algebra 12 MATH2311 City Campus
Linear Programming and Modelling 12 MATH1288 City Campus
System Dynamic Modelling 12 MATH2127 City Campus
Advanced Mathematical Modelling 12 MATH2139 City Campus
Nonlinear Optimisation 12 MATH2143 City Campus
Numerical Solutions of DEs 12 MATH2144 City Campus
Algebra for Information Security 12 MATH2148 City Campus
Mathematical Modelling 12 MATH2194 City Campus
Marketing Principles 12 MKTG1025 City Campus
Marketing Communication 12 MKTG1041 City Campus
Market Research 12 MKTG1045 City Campus
Global Mobility Elective 12 EXTL1195 City Campus

Entry requirements

Program entry requirements

Successful completion of an Australian Year 12 senior secondary certificate of education or equivalent.

For information on international qualifications and corresponding entry requirements that are equivalent to Australian academic entry requirements, see the Country equivalents web page.

Prerequisites

Victorian Certificate of Education (VCE) prerequisite Units 3 and 4 — a study score of at least 20 in one of Mathematical Methods (CAS) or Specialist Mathematics; and a study score of at least 30 in English (EAL) or at least 25 in any other English.

English language requirements

A minimum IELTS (Academic module) overall score of 6.5, with no band below 6.0; or equivalent.

For equivalents to English entry requirements, see the English equivalents web page.

Learning outcomes

On completion of BP245 Bachelor of Science (Statistics) you will be able to:

PLO 1 Personal and professional awareness

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

PLO 2 Knowledge and technical competence

  • use appropriate and relevant, fundamental and applied mathematical and statistical knowledge, methodologies and modern computational tools.

PLO 3 Problem-solving

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

PLO 4 Teamwork and project management

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

PLO 5 Communication

  • communicate effectively 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.

PLO 6 Information literacy

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

PLO 7 Ethics

  • discuss the ethical considerations that inform judgments and decisions in academic and professional settings.

Institution