Availabilities:
Unit Summary
Unit type
Hons Unit
Credit points
12
AQF level
Level of learning
Advanced
Former School/College
Pre-requisites
Unit aim
Reviews statistical methods and concepts 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
- Factorial analysis of variance
- Multiple regression
- Analysis of covariance
- The practicalities of producing a research report, including graphs and APA format.
- Introduction to advanced statistical 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.
| On completion of this unit, students should be able to: | GA1 | GA2 | GA3 | GA4 | GA5 | GA6 | GA7 | |
|---|---|---|---|---|---|---|---|---|
| 1 | be familiar with the different approaches to psychological research, and design a project that accounts for potential confounding factors | |||||||
| 2 | be familiar with 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, report on the outcomes and produce a systematic review | |||||||
| 5 | construct a psychometric test, and test its reliability and dimensionality using factor analysis. | |||||||
On completion of this unit, students should be able to:
-
be familiar with the different approaches to psychological research, and design a project that accounts for potential confounding factors
- GA1:
- GA2:
- GA4:
-
be familiar with the traditional approach to null hypothesis significance testing and its associated flaws
- GA1:
- GA4:
-
analyse complex research data using the IBM-SPSS software package
- GA4:
-
apply a relevant statistical technique to analyse a set of research data, report on the outcomes and produce a systematic review
- GA4:
-
construct a psychometric test, and test its reliability and dimensionality using factor analysis.
- GA4:
Prescribed texts
- Field, A, 2018, Discovering Statistics Using IBM SPSS Statistics, 5th edn, Sage, London.