Statistical Practice 2
PostgraduateSWI-STA600052024
Course information for 2024 intake
Practice and advance your statistical knowledge and extend ideas. Produce an independent investigation. Get analytical and compare groups using parametric and non-parametric methods. Stop generalising, question assumptions and identify data limits.
Enrolments for this course are closed, but you may have other options to start studying now. Book a consultation to learn more.
- Study method
- 100% online
- Assessments
- Subject may require attendance
- Entry requirements
- Part of a degree
- Duration
- 13 weeks
- Loan available
- FEE-HELP available
Statistical Practice 2
About this subject
Students who successfully complete this subject will be able to:
- Choose the appropriate statistical analysis based on the research hypothesis, the level of measurement of the variables and the testing of the appropriate assumptions
- Select appropriate statistical procedures, for example, using appropriate packages and mathematical calculations, to analyse data in a variety of contexts
- Explain the relationship between the concepts of effect size, sample size, one or two tailed tests, level of significance and power of a statistical test
- Write interpretive summary reports for inferential statistical techniques
- Identify when more advanced techniques are needed by comparing properties of statistical techniques to the nature of the complex research question.
- Statistical Power
- Identifying and reducing bias
- Non parametric tests: Wilcoxon Signed Rank test, Friedman test, Wilcoxon Rank Sum test, Kruskal-Wallis Test
- Bivariate and Multiple Regression including: inferential, assumption testing and transformations to achieve linearity
- Spearman's and Kendal's Tau-b correlation
- Single factor independent groups design analysis of variance
- Completely randomised, factorial analysis of variance
- Single factor repeated measures analysis of variance
- Mixed design analysis of variance
- Chi-Square, Fisher's Exact test, Cramer's V, Odds Ratio, Lambda
- Chi Square goodness of fit test
This subject extends the ideas developed in Statistical Practice 1 to include more advanced analyses, broaden the range of applications students are familiar with so that they will be able to carry out independent statistical investigations, and develop an awareness of the assumptions and limitations involved in the generalisation of results of such investigations.
Please note: assessment values are indicative only, details will be advised at the start of the subject.
- Invigilated Exam (50%)
- Quizzes — Online (10%)
- Assignments — 2 (40%)
For textbook details check your university's handbook, website or learning management system (LMS).
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Entry requirements
Part of a degree
To enrol in this subject you must be accepted into one of the following degrees:
Core
- SWI-STA-GCE-2024 - Graduate Certificate of Applied Statistics
Prior study
To help set you up for success before you start this subject, we suggest completing or having equivalent knowledge in:
one of
- SWI-STA60001-Statistical Practice 1
SWI-HMS770 (Not currently available)
Equivalent subjects
You should not enrol in this subject if you have successfully completed any of the following subject(s) because they are considered academically equivalent:
SWI-HMS771 (Not currently available)
Others
If you have some statistical background it is possible to complete STA60001 concurrently with STA60005.
Additional requirements
- Other requirements - You will require access to a recent version of SPSS - at least the SPSS Grad Pak.
Study load
- 0.125 EFTSL
- This is in the range of 10 to 12 hours of study each week.
Equivalent full time study load (EFTSL) is one way to calculate your study load. One (1.0) EFTSL is equivalent to a full-time study load for one year.
Find out more information on Commonwealth Loans to understand what this means to your eligibility for financial support.
Related degrees
Once you’ve completed this subject it can be credited towards one of the following courses
Graduate Certificate of Applied Statistics
PostgraduateSWI-STA-GCE