STATISTICS

Statistics is an essential part of science, providing the mathematical language and techniques necessary for understanding and dealing with chance and uncertainty in Nature. Statistics involves the design, collection, analysis and interpretation of numerical data, with the aim of extracting patterns and other useful information.

Examples include:
  • The analysis of DNA and protein sequences;
  • The construction of evolutionary trees from genetic data;
  • The improvement of medical treatments via experimental designs; and 
  • The assessment of drought conditions through meteorological data.
A main feature of statistics is the development and use of statistical and probabilistic models for random phenomena, which can be analysed and used to make principled predictions and decisions. Examples of such models, to name a few, can be found in:
  • Biology (genetics, population modelling);
  • Finance (stock market fluctuations, insurance claims);
  • Physics (quantum mechanics/computing);
  • Medicine (epidemiology, spread of HIV/AIDS);
  • Telecommunications (Internet traffic, mobile phone calls); and 
  • Engineering (reliability of oil rigs, aircraft failure).

 
This major is administered by the School of Mathematics and Physics.

For further information please contact the Science Faculty.

What will I study?

The Statistics major offers students an in-depth knowledge of modern statistics, with a comprehensive treatment of both theory and applications. The Statistics and Probability group responsible for the statistics curriculum is the leading provider of statistical education in Queensland and is recognised internationally for its active and dynamic research programs across a wide range of areas of statistics and probability.
 
The Statistics major provides a unique opportunity to not only learn state-of-the art statistical techniques and software, but, just as importantly, to gain a clear understanding of the modern statistical and probabilistic theory behind the methods.
 
Because of the essential role of statistics in science, the Statistics Major can be combined with any of the other majors in the BSc to provide breadth and depth of skills.
 
The Statistics major will develop a wide range of skills, including: 
  • Probabilistic reasoning and problem solving;
  • Statistical modelling of analysis;
  • Optimal design of statistical experiments;
  • Advanced data exploration and visualisation;
  • Application of statistical software;
  • Development of statistical algorithms; and
  • Report writing and presentation.
In addition to written assignments and exams (problem solving), the assessment will sometimes include statistical research projects, report writing and practical exams.

Study Plans

Statistics is available as a Single Major. You are required to complete #14 (#6 at Level 2 and #8 at Level 3) from the Statistics course list. The following are suggested study plans for this major and should be used as a guide to planning your program.

Please refer to the course list below to ensure you complete the major requirements.

How do I use the Study Plans?

  1. Choose a study plan.
  2. Take all Compulsory Courses in each semester.
  3. Select required number of units in Key Courses for each year level. 
  4. Ensure you take at least #12 of level 3 (or 4) courses from the BSc list.
  5. Fill any gaps in each semester with Keyor Recommended Courses or electives from BSc or other programs. (Standard full-time semester load #8.)
  6. Ensure you meet the BSc requirements and rules.

What do the different columns mean?

  • Compulsory courses – compulsory for the major.
  • Key courses – electives from the major's course list.
  • Recommended courses – complement the major. 

 Statistics (Single Major) - Computational Statistics

You can find details about the first year of the program here.

Year 2 Compulsory Courses
Complete all courses
Key Courses Recommended Courses
 
Sem 1
MATH2001 Advanced Calculus and Linear Algebra1
STAT2003 Probability & Statistics
 –
CSSE2002 Programming in the Large
Sem 2
STAT2004 Statistical Modelling & Analysis
 –
COSC2500 Numerical Methods in Computational Science
Year 3 Compulsory Courses
Complete all courses
Key Courses Recommended Courses
 
Sem 1
STAT3001 Mathematical Statistics
STAT3003 Experimental Design
 –
MATH3090 Financial Mathematics
MATH3302 Coding & Cryptography
Sem 2
STAT3004 Probability Models & Stochastic Processes
STAT3500 Modern Statistics
 –
 –

 1. This course is available in semester 1 and 2.

Statistics (Single Major) - Financial Statistics

You can find details about the first year of the program here.

Year 2 Compulsory Courses
Complete all courses
Key Courses Recommended Courses
 
Sem 1
MATH2001 Advanced Calculus and Linear Algebra1
STAT2003 Probability & Statistics
 –  –
Sem 2
STAT2004 Statistical Modelling & Analysis
 –
COSC2500 Numerical Methods in Computational Science
Year 3 Compulsory Courses
Complete all courses
Key Courses Recommended Courses
 
Sem 1
STAT3001 Mathematical Statistics
STAT3003 Experimental Design
 –
MATH3090 Financial Mathematics
MATH3202 Operations Research
Sem 2
STAT3004 Probability Models & Stochastic Processes
STAT3500 Modern Statistics
 –  –

  1. This course is available in semester 1 and 2.

Statistics (Single Major) - Theoretical Statistics

You can find details about the first year of the program here.

Year 2 Compulsory Courses
Complete all courses
Key Courses Recommended Courses
 
Sem 1
MATH2001 Advanced Calculus and Linear Algebra 1
STAT2003 Probability & Statistics
 –
MATH2400 Mathematical Analysis
Sem 2
STAT2004 Statistical Modelling & Analysis
  – MATH2302 Discrete Mathematics II
Year 3 Compulsory Courses
Complete all courses
Key Courses Recommended Courses
 
Sem 1
STAT3001 Mathematical Statistics
STAT3003 Experimental Design
 –
MATH3401 Complex Analysis
MATH3402 Functional Analysis
Sem 2
STAT3004 Probability Models & Stochastic Processes
STAT3500 Modern Statistics
 –
 –

   1. This course is available in semester 1 and 2.

Statistics (Single Major) - Biostatistics

You can find details about the first year of the program here.

Year 2 Compulsory Courses
Complete all courses
Key Courses Recommended Courses
 
Sem 1
MATH2001 Advanced Calculus and Linear Algebra1
STAT2003 Probability & Statistics
 –
SCIE2100 Intro to Bioinfomatics
Sem 2
STAT2004 Statistical Modelling & Analysis
 –
BIOL2202 Genetics
Year 3 Compulsory Courses
Complete all courses
Key Courses Recommended Courses
 
Sem 1
STAT3001 Mathematical Statistics
STAT3003 Experimental Design
 –
BIOL3004 Genomics & Bioinformatics
MATH3104 Mathematical Biology
Sem 2
STAT3004 Probability Models & Stochastic Processes
STAT3500 Modern Statistics
 –  –

  1. This course is available in semester 1 and 2.

Major Convenor

Dr Richard Wilson

I am a Senior Lecturer in Statistics in the Department of Mathematics at The University of Queensland. My interests are random processes and fields, excursion sets and extreme value theory, image analysis, reliability, and the modelling and analysis of warranty. 

 

 

Careers

Students majoring in statistics are in very high demand in business, industry, research and government. In business and industry, statisticians are involved in quality control, reliability, product development and improvement, plus delivery and marketing processes. Statisticians may also manage assets and liabilities, determining the risks and returns of certain investments. Statisticians are employed by nearly every government department and in many scientific, medical, environmental, defence and agricultural agencies. Business firms rely on staff with a background in statistics to help forecast sales, analyse business conditions, and solve managerial problems.

The Statistics Major will offer a general but also deep understanding of statistics that will provide you with a broad entry point into a future career using statistics. When you complete your Statistics Major you will not only have a thorough understanding of how to apply various statistical techniques in a wide range of situations – you will also have the knowledge to modify the statistical approach when encountering a statistical problem that does not fit the regular framework. This is a highly attractive feature to future employees.