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Unit Summary

Unit type

UG Coursework Unit

Credit points

12

AQF level

7

Level of learning

Intermediate

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

  • Basic concepts
  • Describing and exploring data
  • Basic concepts of probability
  • The normal distribution
  • Pearson's correlation coefficient
  • Sampling distribution and central limit theorem
  • Hypothesis testing: t-test for a single mean
  • Hypothesis testing: repeated measures t-test
  • Hypothesis testing: independent measures t-test
  • 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.

GA1: , GA2: , GA3: , GA4: , GA5: , GA6: , GA7:
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:

  1. correctly calculate basic parametric statistics on a variety of data sets
    • GA4:
  2. understand the logic of null-hypothesis testing and its application in simple experimental designs
    • GA4:
  3. conduct appropriate parametric hypothesis tests for one- and two-group designs
    • GA4:
  4. interpret the description of results to be found in research publications employing simple experimental designs
    • GA4:
  5. identify errors and interpretation problems in published research employing a range of simple experimental designs
    • GA1:
  6. communicate the results of an analysis adhering to APA standards.
    • GA6:

Prescribed texts

  • 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 teaching periods.