1 x 9-day intensive workshop per semester
1 108 units of topics
2 Admission into BSCHAB-Bachelor of Science (Honours) (Animal Behaviour)
2a Admission into BSCHAQ-Bachelor of Science (Honours) (Aquaculture)
2b Admission into BSCHBD-Bachelor of Science (Honours) (Biodiversity and Conservation)
2c Admission into BSCHMN-Bachelor of Science (Honours) (Marine Biology)
2d Admission into BSCHMNAQ-Bachelor of Science (Honours) (Marine Biology and Aquaculture)
2e Admission into BSCHFS-Bachelor of Science (Honours) (Forensic and Analytical Science)
2f Admission into BSCH-Bachelor of Science (Honours) (Enhanced Program for High Achievers)
2g Admission into BSCHBT-Bachelor of Science (Honours) (Biotechnology)
2h Admission into BSCHPL-Bachelor of Science (Honours) (Palaeontology)
2i Admission into BSCHPSC-Bachelor of Science (Honours) (Plant Science)
3 108 units of topics
4 Admission into BSC-MCRB-Microbiology
4a Admission into BSC-MCBL-Molecular Biology
4b Admission into BSC-BIOL-EX-Biological Sciences
4c Admission into BSC-BIOL-Biological Sciences
4d Admission into BSC-EBEV-Ecology, Behaviour and Evolution
4e Admission into BSC-BINF-EX-Bioinformatics
4f Admission into BSC-BLCM-EX-Biological Chemistry
4g Admission into BSC-MBMB-EX-Molecular Biosciences & Microbiology
4h Admission into BSC-MBSC-Molecular Biosciences
4i Admission into BSC-EEOB-Ecology, Evolution and Organismal Biology
4j Admission into BSC-BTEC-Biotechnology
5 Admission into HBSC-Bachelor of Science (Honours)
5a Admission into HBA-Bachelor of Arts (Honours)
5b Admission into HBBSC-Bachelor of Behavioural Science (Honours)
5c Admission into HBSCAB-Bachelor of Science (Animal Behaviour) (Honours)
5d Admission into HBSCMN-Bachelor of Science (Marine Biology) (Honours)
5e Admission into HBAGIS-Bachelor of Applied Geographical Information Systems (Honours)
5f Admission into MSCES-Master of Science (Environmental Science)
Must Satisfy: ((1 and (2 or 2a or 2b or 2c or 2d or 2e or 2f or 2g or 2h or 2i)) or (3 and (4 or 4a or 4b or 4c or 4d or 4e or 4f or 4g or 4h or 4i or 4j)) or ((5 or 5a or 5b or 5c or 5d or 5e or 5f)))
Enrolment not permitted
BIOL4720 has been successfully completed
Project, Quizzes, Workshop participation
Topic description

This topic develops skill sets that empower the student to understand experimental design and statistics used in natural sciences and apply those skills to develop a robust experimental design for their research project.

The topic provides a firm basis in experimental design, and an understanding of the philosophy of statistical analysis that will allow students to interpret these elements of research. It gives students practice in statistics and experimental design (using computer exercises on data they collect) that will allow them to critically review the literature relevant to their area of research.

Educational aims

This topic aims to provide research training for Honours students in Natural Sciences:

  • Understand principles of experimental design and the statistical analyses commonly used in natural sciences
  • Use "The R Project for Statistical Computing" to analyse data in natural sciences
  • Critically reviewing experimental design and statistics in scientific publications
  • Prepare and evaluate the experimental design for their own research project
  • Evaluate experimental design used in other research projects
Expected learning outcomes
On completion of this topic you will be expected to be able to:

  1. Develop a firm basis for experimental design in research in natural sciences
  2. Gain a firm understanding of the philosophy and methodology that are the foundations of statistical analyses
  3. Visualize the results of the most commonly used statistical techniques and transmit those results to others by the use of two-, or occasionally three-dimensional graphs
  4. Gain practical experience in analysing data using graphs and statistics using "The R Project for Statistical Computing"
  5. Develop an outline and evaluated the experimental design and statistical methods they intended to use in their research project
  6. Be familiar with, and have experience at, critically reviewing experimental design and statistical analyses in oral presentations and research papers
  7. Gain valuable experience in problem solving and optimising experimental design