Major Overview

Description

Note: this major is only available to re-enrolling students.

Quantitative methods are used in a variety of subject areas such as science, economics, marketing, engineering, medicine, public health, psychology, education and sport. An increasing number of industries use quantitative reasoning for improving product and service quality, increasing efficiency in the workplace, and assessing their growth strategies. This major has a full, structured curriculum that provides you with practical, interdisciplinary research skills based on sound disciplinary foundations. The units are designed to empower you by ensuring you develop a broad range of skills and abilities that you will find useful and relevant to your own interests.

Outcomes

Students are able to (1) appreciate different possible approaches and tools for quantitative problem solving; (2) acquire a broad range of basic quantitative and computational techniques in the context of real applications; (3) understand the meaning and interpretation of basic quantitative methods; (4) suggest a method of solution when presented with an quantitative problem; (5) select the most appropriate technique when presented with two alternative techniques for solving a quantitative problem; (6) recognise which technique is being applied when presented with a step-by-step description of a quantitative technique; (7) select and apply basic quantitative and computational techniques, in practice, on a broad range of real data; (8) write succinct interpretations of the results, identify correct and incorrect interpretations, and identify the most appropriate statistical graphic supporting the conclusion when presented with the results of a quantitative technique; (9) extract key information relevant to a quantitative problem from various kinds of material (written documents, video recordings, role-playing interactions); (10) express specified quantitative information in language appropriate to a specified audience; (11) explain in lay terms the meaning of a computer output or statistical calculation; (12) identify obvious flaws in the presentation of quantitative information in newspaper and TV reports; and (13) recognise basic features and key results of quantitative analysis presented in scientific literature.

Broadening guidelines

All students studying towards a Bachelor's Degree at UWA are required to Broaden their studies by completing a minimum of four units (24 points) of study outside their degree specific major. Broadening is your opportunity to explore other areas of interest, investigate new disciplines and knowledge paradigms and to shape your degree to suit your own aspirations and interests. Many of you will be able to undertake more than this minimum amount of broadening study and we encourage you to do so if this suits your aspirations. Over the next few months you will find here some broadening suggestions related to your degree-specific major. While we know that many students value guidance of this sort, these are only suggestions and students should not lose sight of the opportunity to explore that is afforded by your Broadening Choices. Advice can also be sought from your Allocated Student Advising Office.

Courses

Quantitative Methods can be taken as a degree-specific major in the following degree courses:

No study plans found for this major. See study plans for more information.

Units

Key to availability of units:
S1
Semester 1
S2
Semester 2
N/A
not available in 2023 – may be available in 2024 or 2025

Level 1

Degree-specific major units

Take unit(s) to the value of 6 points:

Availability Unit code Unit name unit requirements
S1, S2 MATH1012 Mathematical Theory and Methods
Prerequisites
Mathematics Specialist ATAR
or MATH1722 Mathematics Foundations: Specialist or equivalent
S1, S2 STAT1400 Statistics for Science
Prerequisites
Mathematics Applications ATAR
or MATH1720 Mathematics Fundamentals or equivalent
Incompatibility
STAT1520 Economic and Business Statistics
S1, S2 STAT1520 Economic and Business Statistics
Prerequisites
Mathematics Applications ATAR
or MATH1720 Mathematics Fundamentals
or ECON1111 Quantitative Methods for Business and Economics or equivalent
Incompatibility
STAT1400 Statistics for Science
Degree-specific major units

Take unit(s) to the value of 6 points:

Availability Unit code Unit name unit requirements
S2 CITS1402 Relational Database Management Systems
Prerequisites
Mathematics Applications ATAR
or MATH1720 Mathematics Fundamentals or equivalent
Incompatibility
CITS2232 Databases
S1 ECON1111 Quantitative Methods for Business and Economics
Prerequisites
Mathematics Applications (ATAR)
or WACE Mathematics 2C/2D
or TEE Discrete Mathematics
or MATH0700 Preparatory Mathematics
Incompatibility
Mathematics Methods (ATAR) or higher.
WACE Mathematics 3A/3B or higher.
TEE Applicable Mathematics.
TEE Calculus.
or MATH1701 Introductory Mathematics Foundations
S1, S2 MATH1011 Multivariable Calculus
Prerequisites
Mathematics Specialist ATAR
or MATH1722 Mathematics Foundations: Specialist or equivalent
Complementary units

Take the complementary unit (6 points) (not required by students who have Mathematics: Methods ATAR or WACE Mathematics 3A/3B or equivalent or higher):

Availability Unit code Unit name unit requirements
S1, S2 MATH1720 Mathematics Fundamentals
Prerequisites
Mathematics Applications ATAR [with a scaled score of less than 50] or with permission
Incompatibility
Mathematics Applications ATAR [with a scaled score of 50 or greater] or Equivalent or higher

Level 2

Degree-specific major units

Take all units (12 points):

Availability Unit code Unit name unit requirements
S1 STAT2401 Analysis of Experiments
Prerequisites
Mathematics Applications ATAR
or MATH1720 Mathematics Fundamentals or equivalent
S2 STAT2402 Analysis of Observations
Prerequisites
Mathematics Applications ATAR
or MATH1720 Mathematics Fundamentals or equivalent

Level 3

Degree-specific major units

Take all units (24 points):

Availability Unit code Unit name unit requirements
S1 STAT3401 Advanced Data Analysis
Prerequisites

Course Enrolment in
the MJD-QTMTD Quantitative Methods major
or the MJD-CDSDM Computing and Data Science major
or the MJD-HSDEM Human Sciences and Data Analytics major
and STAT2401 Analysis of Experiments
and STAT2402 Analysis of Observations
or STAT2062 Fundamentals of Probability with Applications
Incompatibility
STAT4065 Multilevel and Mixed-Effects Modelling
N/A STAT3402 Communication and Problem Solving with Statistics
Prerequisites
Enrolment in
in the MJD-QTMTD Quantitative Methods major STAT3401 Advanced Data Analysis
S2 STAT3405 Introduction to Bayesian Computing and Statistics
Prerequisites

Course Enrolment in
the MJD-DATSC Data Science major
or the MJD-QTMTD Quantitative Methods major
and STAT2401 Analysis of Experiments
and STAT2402 Analysis of Observations
or STAT2062 Fundamentals of Probability with Applications
Incompatibility
STAT4066 Bayesian Computing and Statistics
S1 STAT3406 Applied Statistics and Data Visualisation
Prerequisites

Course Enrolment in
the MJD-QTMTD Quantitative Methods major
or the MJD-HSDEM Human Sciences and Data Analytics major
or the MNR-ASTAT Applied Statistical Learning minor
and STAT2401 Analysis of Experiments
and STAT2402 Analysis of Observations
or STAT2062 Fundamentals of Probability with Applications
Incompatibility
STAT4064 Applied Predictive Modelling