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SC2209 - Quantitative Methods in Science-Advanced

Credit points: 3
Year: 2023
Student Contribution Band: Band 1
Administered by: College of Science and Engineering

An introduction to experimental design and analysis, with particular emphasis on the formulation of appropriate statistical models for data analysis, and their applications in science. Topics include the principles of scientific sampling design; hypothesis generation for scientific experiments; collection of scientific data; manipulations and interpretation of data; statistical methods used in science; and the use of data in scientific reports. In addition, basic probability and statistical theory, and computationally intensive statistical methods will be covered. This subject is compulsory for all Bachelor of Science-Advanced students and is recommended for any Bachelor of Science students who intend to enrol in the Advanced program or any students majoring in Maths or Physics who might prefer this subject over SC2202.

Learning Outcomes

  • develop skills in the design, execution and reporting of scientific experiments and survey programs;
  • demonstrate appropriate computer skills for data management analysis, and graphical presentation;
  • design and use appropriate statistical methods to analyse scientific data;
  • apply statistical theory to identify and defend appropriate statistical methodology in research.

Subject Assessment

  • Written > Examination (centrally administered) - (40%) - Individual
  • Written > Test/Quiz 1 - (20%) - Individual
  • Weekly Assignment - (40%) - Individual.
Students enrolling in this subject should have a good understanding of level 1 science, including at least two level 1 subjects.
Prerequisites: MA1003 and ((SC1109 plus 6 credit points of other Level 1 subjects) or admission in 116409)
BS2001 BS5001 BZ5001 BZ2001 SC2202 SC5202


Cairns, Study Period 1, Internal
Census Date 23-Mar-2023
Coord/Lect: Dr Carla Ewels.
Workload expectations:

The student workload for this 3 credit point subject is approximately 130 hours.

  • 39 hours online activity
  • 26 hours online Workshops - computer workshops
  • assessment and self-directed study

Townsville, Study Period 1, Internal
Census Date 23-Mar-2023
Coordinator: Dr Carla Ewels
Lecturers: Dr Carla Ewels, Dr Martijn van de Pol.
Workload expectations:

The student workload for this 3 credit point subject is approximately 130 hours.

  • 26 hours workshops - Computer workshops
  • 39 hours online activity
  • assessment and self-directed study

Note: Minor variations might occur due to the continuous Subject quality improvement process, and in case of minor variation(s) in assessment details, the Subject Outline represents the latest official information.