UG Coursework Unit
Level of learning
A basic understanding of the concepts underlying hypothesis testing is provided, with emphasis upon the normal distribution and central limit theorem. Equips students with a range of quantitative data analytic techniques (correlation, z-test, single-sample t-test, between groups t-test, and repeated measures t-test) utilised in psychological research.
Topic 1: Basic concepts
Topic 2: Describing and exploring data
Topic 3: Basic concepts of probability
Topic 4: The normal distribution
Topic 5: Pearson's correlation coefficient
Topic 6: Sampling distribution and central limit theorum
Topic 7: Hypothesis testing: t-test for a single mean
Topic 8: Hypothesis testing: repeated measures t-test
Topic 9: Hypothesis testing: independent measures t-test
Topic 10: Assumptions and their implications
Topic 11: Hypothesis testing for 3 or more means, analysis of variance (ANOVA)
Topic 12: Revision
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||correctly calculate basic parametric statistics on a variety of data sets|
|2||understand the logic of null-hypothesis testing and its application in simple experimental designs|
|3||conduct appropriate parametric hypothesis tests for one- and two-group designs|
|4||interpret the description of results to be found in research publications employing simple experimental designs|
|5||identify errors and interpretation problems in published research employing a range of simple experimental designs|
|6||communicate the results of an analysis adhering to APA standards.|
On completion of this unit, students should be able to:
correctly calculate basic parametric statistics on a variety of data sets
understand the logic of null-hypothesis testing and its application in simple experimental designs
conduct appropriate parametric hypothesis tests for one- and two-group designs
interpret the description of results to be found in research publications employing simple experimental designs
identify errors and interpretation problems in published research employing a range of simple experimental designs
communicate the results of an analysis adhering to APA standards.
- Howell, G., 2016, Fundamental Statistics for the Behavioural Sciences, 9th edn, Cengage Learning, Boston, MA. ISBN: 978-1-305-65297-2.