Availabilities:
2020 unit offering information will be available in September 2019
Unit aim
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.
Unit content
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Basic concepts
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Describing and exploring data
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Basic concepts of probability
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The normal distribution
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Pearson's correlation coefficient
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Sampling distribution and central limit theorem
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Hypothesis testing: t-test for a single mean
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Hypothesis testing: repeated measures t-test
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Hypothesis testing: independent measures t-test
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Assumptions and their implications
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.
Learning outcomes and graduate attributes
GA1: Intellectual rigour,
GA2: Creativity,
GA3: Ethical practice,
GA4: Knowledge of a discipline,
GA5: Lifelong learning,
GA6: Communication and social skills,
GA7: Cultural competence| 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 | | | | Knowledge of a discipline | | | |
| 2 | understand the logic of null-hypothesis testing and its application in simple experimental designs | | | | Knowledge of a discipline | | | |
| 3 | conduct appropriate parametric hypothesis tests for one- and two-group designs | | | | Knowledge of a discipline | | | |
| 4 | interpret the description of results to be found in research publications employing simple experimental designs | | | | Knowledge of a discipline | | | |
| 5 | identify errors and interpretation problems in published research employing a range of simple experimental designs | Intellectual rigour | | | | | | |
| 6 | communicate the results of an analysis adhering to APA standards. | | | | | | Communication and social skills | |
On completion of this unit, students should be able to:
- correctly calculate basic parametric statistics on a variety of data sets
- GA4:
Knowledge of a discipline
- understand the logic of null-hypothesis testing and its application in simple experimental designs
- GA4:
Knowledge of a discipline
- conduct appropriate parametric hypothesis tests for one- and two-group designs
- GA4:
Knowledge of a discipline
- interpret the description of results to be found in research publications employing simple experimental designs
- GA4:
Knowledge of a discipline
- 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.
- GA6:
Communication and social skills
Prescribed texts
Session 2
- Field, A, 2018, Discovering Statistics Using IBM SPSS Statistics, 5th edn, Sage , London.
- Howell, G, 2016, Fundamental Statistics for the Behavioural Sciences, 9th edn, Cengage Learning, Boston, MA.
Prescribed texts may change in future study periods.