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Unit of Study BHS20008 - Quantitative Methods in Psychology (2017)

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Unit Snapshot

  • Enrolment information

    Students should have basic mathematical skills equivalent to Year 10 Maths. Students should have basic computer literacy and familiarity with a spreadsheet program, such as Excel.

Unit description

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

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

Availabilities

Location Domestic International
Coffs Harbour Session 2 Session 2
Online Session 2 N/A

Learning outcomes and graduate attributes

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: Intellectual rigour, GA2: Creativity, GA3: Ethical practice, GA4: Knowledge of a discipline, GA5: Lifelong learning, GA6: Communication and social skills, GA7: Cultural competence
Learning outcome count Learning outcome description 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 learning resources

Prescribed Texts
  • No prescribed texts.

Prescribed Learning Resources may change in future Teaching Periods.