Back to Find Units Page

Unit of Study MAT83001 - Analysis of Multivariate Behavioural Data (2015)

Show me unit information for year

Unit Snapshot

  • Enrolment information

    N/A

Unit description

Reviews statistical methods and concepts from previous years and considers research methodology and data analysis at an advanced level.  Modern approaches to null hypothesis testing and alternative approaches to data analysis are considered. The construction and analysis of psychometric tests is discussed.

Unit content

  • Systematic reviews
  • Review of research methods, especially analysis of variance and linear regression
  • Designing research projects in Psychology, and power analysis
  • The logic of null hypothesis significance testing
  • The empirical bases underpinning the construction of widely used cognitive and personality assessments
  • Factor analysis
  • Multiple regression
  • Analysis of covariance
  • Multivariate analysis of variance
  • The practicalities of producing a research report, including graphs and APA format.
  • Introduction to advanced statistical analysis

Availabilities

Location Domestic International
Coffs Harbour Session 1 Session 1

Learning outcomes and graduate attributes

Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes. The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.

On completion of this unit, students should be able to:

GA1: Intellectual rigour, GA2: Creativity, GA3: Ethical practice, GA4: Knowledge of a discipline, GA5: Lifelong learning, GA6: Communication and social skills, GA7: Cultural competence
Learning outcome count Learning outcome description GA1 GA2 GA3 GA4 GA5 GA6 GA7
1 Design a research project that accounts for potential confounding factors in research designs
2 Demonstrate an understanding of the logic of the traditional approach to null hypothesis significance testing and its associated flaws
3 Analyse complex research data using the IBM-SPSS software package
4 Apply a relevant statistical technique to analyse a set of research data and report on the outcomes
5 Demonstrate an understanding of professional issues involved in psychometric testing and the construction and validation of psychometric tests
6 Write a brief systematic review using the PRISMA format

On completion of this unit, students should be able to:

  1. Design a research project that accounts for potential confounding factors in research designs
    • GA1:
    • GA2:
    • GA4:
  2. Demonstrate an understanding of the logic of the traditional approach to null hypothesis significance testing and its associated flaws
    • GA1:
    • GA4:
  3. Analyse complex research data using the IBM-SPSS software package
    • GA4:
  4. Apply a relevant statistical technique to analyse a set of research data and report on the outcomes
    • GA4:
  5. Demonstrate an understanding of professional issues involved in psychometric testing and the construction and validation of psychometric tests
    • GA4:
  6. Write a brief systematic review using the PRISMA format
    • GA1:

Prescribed learning resources

Prescribed Texts
  • No prescribed texts.

Prescribed Learning Resources may change in future Teaching Periods.