Bachelor of
Science:

Study Planner Information

Year 1 Study Planner

Program Rules Course List

What do the different requirements mean?

  • Compulsory – all students must complete this course
  • Prerequisite for major – course required for this major
  • Recommended – other science course which complements the major, but can be substituted for an elective
  • Elective - an elective course from the course list, or as permitted by the program rules
Year 1 - Semester 1
Course Code & Title Requirements
SCIE1000 Theory & Practice in Science Compulsory
[ MATH1051 Calculus & Linear Algebra I1,3
OR
MATH1071 Advanced Calculus & Linear Algebra I3 ]
Prerequisite for major
MATH1061 Discrete Mathematics Recommended
Elective Elective

 

Year 1 - Semester 2
Course Code & Title Requirements
[ STAT1201 Analysis of Scientific Data
OR
STAT1301 Advanced Analysis of Scientific Data ]
Compulsory
[ MATH1052 Multivariate Calculus & Ordinary Differential Equations3
OR
MATH1072 Advanced Multivariate Calculus & Ordinary Differential Equations3 ]
Prerequisite for major
Elective Elective
Elective Elective

1. Students without at least a Sound Achievement in Senior Maths C are required to take MATH1050 as an elective before MATH1051.
2. MATH1050 is not available for students with a High Achievement or higher in Senior Maths C. MATH1050 is not available to students who have passed MATH1051 and/or MATH1071 and/or MATH1052 and/or MATH1072.
3. Students with a high achievement in Senior Maths C (or a 6 or 7 in MATH1050) should take the sequence MATH1071, MATH1072 and MATH2401.  Students with a sound achievement in Senior Maths C (or a 4 or 5 in MATH1050) should take the sequence MATH1051, MATH1052 and MATH2400.

 

Year 2 to 3 Study Planner

Program Rules Course List

What do the different columns mean?

  • Required for Major – a course required for this major
  • Recommended – an elective course from the course list, or as permitted by the program rules
  • Computational Statistics
    Year 2
    Semester Required for Major Recommended
    1 MATH2001 Advanced Calculus and Linear Algebra II1
    STAT2003 Probability & Statistics
    CSSE2002 Programming in the Large
    2 STAT2004 Statistical Modelling & Analysis COSC2500 Numerical Methods in Computational Science
    Year 3
    Semester Required for Major Recommended
    1 STAT3001 Mathematical Statistics
    STAT3003 Experimental Design
    MATH3090 Financial Mathematics
    MATH3302 Coding & Cryptography
    2 STAT3004 Probability Models & Stochastic Processes
    STAT3500 Problems & Applications in Modern Statistics
    STAT3306 Statistical Analysis of Genetic Data
    STAT4401 Advanced Statistics 12

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

    2. This course is offered in EVEN years only

  • Financial Statistics
    Year 2
    Semester Required for Major Recommended
    1 MATH2001 Advanced Calculus and Linear Algebra II1
    STAT2003 Probability & Statistics
     
    2 STAT2004 Statistical Modelling & Analysis COSC2500 Numerical Methods in Computational Science
    Year 3
    Semester Required for Major Recommended
    1 STAT3001 Mathematical Statistics
    STAT3003 Experimental Design
    MATH3090 Financial Mathematics
    MATH3202 Operations Research & Mathematical Planning
    2 STAT3004 Probability Models & Stochastic Processes
    STAT3500 Problems & Applications in Modern Statistics
    STAT4401 Advanced Statistics 12

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

    2. This course is offered in EVEN years only

  • Theoretical Statistics
    Year 2
    Semester Required for Major Recommended
    1 MATH2001 Advanced Calculus and Linear Algebra II1
    STAT2003 Probability & Statistics
    MATH2400 Mathematical Analysis
    2 STAT2004 Statistical Modelling & Analysis MATH2302 Discrete Mathematics II
    Year 3
    Semester Required for Major Recommended
    1 STAT3001 Mathematical Statistics
    STAT3003 Experimental Design
    MATH3401 Complex Analysis
    MATH3402 Functional Analysis
    2 STAT3004 Probability Models & Stochastic Processes
    STAT3500 Problems & Applications in Modern Statistics
    STAT4401 Advanced Statistics 12

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

    2. This course is offered in EVEN years only

  • Biostatistics
    Year 2
    Semester Required for Major Recommended
    1 MATH2001 Advanced Calculus and Linear Algebra II1
    STAT2003 Probability & Statistics
    SCIE2100 Introduction to Bioinfomatics
    2 STAT2004 Statistical Modelling & Analysis BIOL2202 Genetics
    Year 3
    Semester Required for Major Recommended
    1 STAT3001 Mathematical Statistics
    STAT3003 Experimental Design
    BIOL3004 Genomics & Bioinformatics
    MATH3104 Mathematical Biology
    2 STAT3004 Probability Models & Stochastic Processes
    STAT3500 Problems & Applications in Modern Statistics
    STAT3306 Statistical Analysis of Genetic Data
    STAT4401 Advanced Statistics 12

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

    2. This course is offered in EVEN years only

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.