EHR415 Research Design & Statistics (8)

The aim of this subject is to inform students of the scientific method, resultant research process, related research designs and perform pertinent statistical analyses using computer software within the quantitative discipline of exercise and sport science.

No offerings have been identified for this subject in 2019.

Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject Information

Grading System

HD/FL

Duration

One session

School

School of Exercise Science, Sport and Health

Enrolment Restrictions

Available to students in:

Graduate Diploma in Exercise and Sport Science

or as approved by the Course Director
 

Assumed Knowledge

Students should have an understanding of basic algebra and computer skills prior to undertaking this subject.

Learning Outcomes

Upon successful completion of this subject, students should:
  • be able to apply the practice of science and the scientific method to research in exercise science;
  • be able to identify and explain obstacles to adhering to the scientific method;
  • be able to demonstrate estimation of sample size apriori for human subjects research;
  • be able to examine the organisational and ethical issues of research in health practice settings;
  • be able to develop a research question and formulate an appropriate design and protocol to investigate and answer the question;
  • be able to apply acquired knowledge and skill in the future completion of a NEAF submission for a developed research project;
  • be able to apply software and information technology for referencing, surveys and statistical analyses;
  • be able to assess the appropriateness of a variety of statistical analyses for different research designs.

Syllabus

This subject will cover the following topics:
  • Research, science and the scientific method;
  • Introduction to research design and descriptive statistics;
  • Applying correlations;
  • How to select subjects;
  • Analysing variance;
  • Multiple factor designs, ANOVA, ANCOVA and MANOVA;
  • Multiple regression, discriminant function (DFA) and factor analysis;
  • Putting it all together: matching research questions, research designs and statistics.

Contact

For further information about courses and subjects outlined in the CSU handbook please contact:

Current students

Future students

The information contained in the CSU Handbook was accurate at the date of publication: May 2019. The University reserves the right to vary the information at any time without notice.

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