Availabilities:

Location Domestic International
Coffs Harbour Session 2 Session 2
Online Session 2 Session 2

Unit Summary

Unit type

UG Coursework Unit

Credit points

12

AQF level

7

Level of learning

Intermediate

Unit aim

Equips students with a range of quantitative data analytic techniques utilised in psychological research. Provides methods for describing, summarising, and illustrating the results of experiments. Students are introduced to parametric statistics and correlations as methods for the description of variables and their relations. A basic understanding of the concepts underlying hypothesis testing is provided, with emphasis upon the normal distribution and central limit theorem. The use of t-tests for examining hypotheses about differences between groups and conditions is described. The conceptual basis of analysis of variance for testing hypotheses regarding experiments where the number of groups exceeds two is also described.

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 theorem
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
 

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 use a spreadsheet program such as Excel to 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 quantitative analyses on simple data sets using a spreadsheet such as Excel
4 correctly 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 in an effective manner adhering to APA standards

On completion of this unit, students should be able to:

  1. use a spreadsheet program such as Excel to 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 quantitative analyses on simple data sets using a spreadsheet such as Excel
    • GA4:
  4. correctly 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 in an effective manner adhering to APA standards
    • GA6:

Prescribed texts

  • Boslaugh, S, 2012, Statistics in a Nutshell, 2nd edn, O'Reilly Media, Sebastapol, CA. ISBN: Print ISBN: 978-1-4493-1682-2, Ebook ISBN: 978-1-4493-1692-1.
Prescribed texts may change in future teaching periods.