Major Overview

Description

Statistics is the science concerned with developing and studying methods for collecting, analysing, interpreting and presenting data. It is becoming increasingly important as a core tool in many disciplines such as medicine, psychology, education, sociology, engineering and physics. Statistics is important in many aspects of society such as business, industry and government. It is a highly interdisciplinary field; research in statistics finds applications in virtually all scientific fields. This major will equip you with the mathematical tools and the foundational knowledge in statistics to pursue engaging careers in research, business, industry or teaching.

Outcomes

Students are able to:

  1. apply appropriate techniques to the collection, visual presentation, analysis and interpretation of data from a wide range of sources
  2. model real-world phenomena involving unpredictable variation in the language of mathematics
  3. select appropriate mathematical/statistical models of data generating mechanisms
  4. use modern statistical computing packages for statistical analysis and simulation.
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 and to pursue as many areas of interest as you can during your course of study. At the same time, we know that many of you value the University's guidance and assistance in planning your enrolment throughout your course, so we offer the following suggestions for your consideration as possible avenues to broaden your degree. Do always remember, however, that there is no wrong way to broaden your studies as long as you complete at least four units not associated with your Degree Specific Major.
Suggested units to broaden your study area, are:
(1) CITS1401 Computational Thinking with Python
(2) MATH1013 Mathematical Analysis
(3) MATH1014 Algebra
(4) MATH2030 Metric Spaces & Measure Theory
Incompatibilities

MJD-MTHST Mathematics and Statistics

Courses

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

Example Study Plans

See study plans for more information.

Units

Key to availability of units:
S1
Semester 1
S2
Semester 2

Level 1

Degree-specific major units

Take all units (12 points):

Availability Unit code Unit name unit requirements
S1, S2 MATH1011 Multivariable Calculus
Prerequisites
Mathematics Specialist ATAR
or MATH1722 Mathematics Foundations: Specialist or equivalent
S1, S2 MATH1012 Mathematical Theory and Methods
Prerequisites
Mathematics Specialist ATAR
or MATH1722 Mathematics Foundations: Specialist or equivalent
Degree-specific major units

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

Availability Unit code Unit name unit requirements
S1, S2 STAT1400 Statistics for Science
Prerequisites
Mathematics Applications ATAR
or MATH1720 Mathematics Fundamentals
or MATX1720 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 MATX1720 Mathematics Fundamentals
or ECON1111 Quantitative Methods for Business and Economics or equivalent
Incompatibility
STAT1400 Statistics for Science
or STAX1400 Statistics for Science

Level 2

Degree-specific major units

Take all units (24 points):

Availability Unit code Unit name unit requirements
S2 MATH2064 Numerical Methods
Prerequisites
MATH1011 Multivariable Calculus
or MATX1011 Multivariable Calculus
or MATH1013 Mathematical Analysis
and
MATH1012 Mathematical Theory and Methods
or MATX1012 Mathematical Theory and Methods
or MATH1014 Algebra
S2 STAT2062 Fundamentals of Probability with Applications
Prerequisites
MATH1011 Multivariable Calculus
or MATX1011 Multivariable Calculus
and
MATH1012 Mathematical Theory and Methods
or MATX1012 Mathematical Theory and Methods
Incompatibility
STAT2063 Probabilistic Methods and their Applications
S1 STAT2401 Analysis of Experiments
Prerequisites
Mathematics Applications ATAR
or MATH1720 Mathematics Fundamentals
or MATX1720 Mathematics Fundamentals or equivalent
or
Enrolment in
62530 Master of Data Science
S2 STAT2402 Analysis of Observations
Prerequisites
Mathematics Applications ATAR
or MATH1720 Mathematics Fundamentals
or MATX1720 Mathematics Fundamentals or equivalent
or
Enrolment in
62530 Master of Data Science

Level 3

Degree-specific major units

Take all units (18 points):

Availability Unit code Unit name unit requirements
S1 STAT3061 Random Processes and their Applications
Prerequisites
Enrolment in MJD-MTHST Mathematics and Statistics
STAT2062 Fundamentals of Probability with Applications
or STAT2063 Probabilistic Methods and their Applications
S1 STAT3062 Statistical Science
Prerequisites
Enrolment in MJD-MTHST Mathematics and Statistics and
STAT2062 Fundamentals of Probability with Applications
or STAT2063 Probabilistic Methods and their Applications
S1 STAT3401 Advanced Data Analysis
Prerequisites
STAT2401 Analysis of Experiments
and STAT2402 Analysis of Observations
or STAT2062 Fundamentals of Probability with Applications
Incompatibility
STAT4065 Multilevel and Mixed-Effects Modelling
Degree-specific major units

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

Availability Unit code Unit name unit requirements
S2 STAT3063 Spatial Statistics and Modelling
Prerequisites
Enrolment in MJD-MTHST Mathematics and Statistics and
STAT2062 Fundamentals of Probability with Applications
or STAT2063 Probabilistic Methods and their Applications
S2 STAT3064 Statistical Learning
Prerequisites
Enrolment in
MJD-CDSDM Computing and Data Science
or MJD-MTHST Mathematics and Statistics
or MJD-DATSC Data Science
or MJD-HSDEM Human Sciences and Data Analytics
and
STAT2401 Analysis of Experiments
and STAT2402 Analysis of Observations
or
STAT2062 Fundamentals of Probability with Applications
or STAT2063 Probabilistic Methods and their Applications
Incompatibility
STAT4067 Applied Statistics and Data Visualisation
and STAT5061 Statistical Data Science
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