Overview

This unit of study extends the ideas developed in previous units 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.

Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date

Learning outcomes

Students who successfully complete this unit 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 SPSS, Java applets on the web 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

Teaching methods

Hawthorn

Type Hours per week Number of weeks Total (number of hours)
Online Contact (Phasing out)
Collaboration		1.00 12 weeks 12
Online
Directed Online Learning and Independent Learning		11.50 12 weeks 138
TOTAL150

Hawthorn

Type Hours per week Number of weeks Total (number of hours)
Face to Face Contact (Phasing out)
Lecture		2.00 12 weeks 24
Online Contact (Phasing out)
Collaboration		1.00 12 weeks 12
Specified Learning Activities (Phasing out)
Various		2.00 12 weeks 24
Unspecified Learning Activities (Phasing out)
Independent Learning		7.50 12 weeks 90
TOTAL150

Assessment

Type Task Weighting ULO's
ExaminationIndividual 50% 1,3,4,5 
Online QuizzesIndividual 10% 1,3,5 
Written AssignmentIndividual 40% 2,4 

Content

  • 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.

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.