2024 unit offering information will be available in November 2023
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.
- Descriptive statistics
- The normal distribution and measures of association between variables
- The logic of null-hypothesis testing
- Two-sample dependent and independent means t-tests
- Threats to validity and interpretation of null-hypothesis testing
- Modern approaches to quantitative research
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||calculate basic descriptive statistics on a variety of real-world data sets|
|2||interpret measures of association between continuous variables common to psychological investigation|
|3||select and perform appropriate hypothesis tests for simple experimental designs|
|4||interpret and communicate the results of analyses using appropriate conventions in psychology|
On completion of this unit, students should be able to:
- calculate basic descriptive statistics on a variety of real-world data sets
- interpret measures of association between continuous variables common to psychological investigation
- select and perform appropriate hypothesis tests for simple experimental designs
- interpret and communicate the results of analyses using appropriate conventions in psychology
Teaching and assessment
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