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Unit Summary

Unit type

UG Coursework Unit

Credit points

12

Faculty/College

Faculty of Health

Pre-requisites

BHS20008 Quantitative Methods in Psychology

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, and factor analysis. The treatment of potential threats to interpretation (outlying data points, failures to meet relevant assumptions) will be discussed.

Unit content

The development of quantitative knowledge and skills allows for competent comprehension of research literature, the ability to conduct quantitative research, and increased options for collaboration with professionals from many fields. Advanced Quantitative Methods in Psychology will give students knowledge and skills in:

  • Statistical concepts, such as variance
  • Parametric statistics, including:
    • Between-groups analysis of variance (ANOVA)
    • Within-groups ANOVA
    • Factorial and mixed factorial ANOVA
    • Simple linear regression
    • Multiple regression
    • Factor analysis
  • Assumptions of statistical tests, their importance and how to test them
  • Calculating and interpreting effect size
  • Statistical power

 

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.

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
2 demonstrate an understanding of quantitative research methodology and appropriate methods of data analysis
3 demonstrate an awareness of problems with data interpretation, outliers and lack of conformity with statistical assumptions
4 demonstrate an understanding of the difference between statistical significance and practical significance (treatment effect)
5 demonstrate competency in the use of Statistical Package for Social Science [SPSS]
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
  2. demonstrate an understanding of quantitative research methodology and appropriate methods of data analysis
  3. demonstrate an awareness of problems with data interpretation, outliers and lack of conformity with statistical assumptions
  4. demonstrate an understanding of the difference between statistical significance and practical significance (treatment effect)
  5. demonstrate competency in the use of Statistical Package for Social Science [SPSS]
  6. report the outcome of statistical analyses in the format required by the American Psychological Association.

Prescribed texts

  • Field, A, 2018, Discovering Statistics using IBM SPSS Statistics, 5th edn, Sage Publications, London.
Prescribed texts may change in future teaching periods.