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Location Domestic International
Coffs Harbour Session 1 Session 1
Online Session 1 N/A

Unit Summary

Unit type

UG Coursework Unit

Credit points

12

AQF level

7

Level of learning

Advanced

Unit aim

Equips students with a range of advanced methodological and data-analysis techniques likely to be utilised in psychological research at honours level. Introduces students to the conceptual basis and practical use of the General Linear Model. Students will learn to use the SPSS computer program for the analysis of complex data using ANOVA, multiple regression, factor analysis and other routines. The treatment of potential threats to interpretation (outlying data points, failures to meet relevant assumptions) will be stressed.

Unit content

Topic 1 :Overview of basic statistical concepts, especially variance and parametric statistics

Topic 2: Introduction to the Analysis of Variance: 

  • How variance may be partitioned into between subjects and within subjects variance and 
  • The basic model

Topic 3: Assumptions of the analysis of variance

Topic 4: Performing multiple comparisons to follow up an ANOVA

Topic 5: Effect size and statistical power

Topic 6: Introduction to Factorial ANOVA

Topic 7: Following up a significant factorial ANOVA

Topic 8: Repeated measures ANOVA

Topic 9: Factorial designs involving repeated measures

Topic 10: Linear regression and introduction to multivariate statistics

Topic 11: Multiple regression

Topic 12: Factor analysis

Learning outcomes

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.

GA1: , GA2: , GA3: , GA4: , GA5: , GA6: , GA7:
On completion of this unit, students should be able to: GA1 GA2 GA3 GA4 GA5 GA6 GA7
1 demonstrate an understanding of variance and how it is partitioned during analysis of variance
2 demonstrate an understanding of research methodology and appropriate methods of data analysis
3 demonstrate an awareness of problems with data interpretation, and know how to detect outliers and lack of conformity with statistical assumptions
4 demonstrate an understanding of the difference between statistical significance and practical significance (treatment effect)
5 use SPSS to perform statistical analyses
6 report the outcome of statistical analyses in the format required by the American Psychological Association.

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

  1. demonstrate an understanding of variance and how it is partitioned during analysis of variance
    • GA4:
  2. demonstrate an understanding of research methodology and appropriate methods of data analysis
    • GA1:
    • GA4:
  3. demonstrate an awareness of problems with data interpretation, and know how to detect outliers and lack of conformity with statistical assumptions
    • GA1:
    • GA4:
  4. demonstrate an understanding of the difference between statistical significance and practical significance (treatment effect)
    • GA4:
  5. use SPSS to perform statistical analyses
    • GA4:
  6. report the outcome of statistical analyses in the format required by the American Psychological Association.
    • GA4:
    • GA6:

Prescribed texts

  • Field, A, 2013, Discovering Statistics using IBM SPSS Statistics, 4th edn, Sage Publications, London. ISBN: 978-4462-4918-5.
Prescribed texts may change in future teaching periods.