Course coordinator
Dr Christoph Klebl
Course overview
- Study period
- Semester 1, 2025 (24/02/2025 - 21/06/2025)
- Study level
- Postgraduate Coursework
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Psychology School
The aim of this course is to expand student's understanding of theory and practice of research methodology, data analysis and report writing in psychology. Topics covered include design and measurement issues, methods for analysing psychological data, procedures involved in the reporting of psychological research, and issues concerned with the interpretation of such research.
This course introduces students to the principles of behavioural data. The aim is to expand students' understanding of theory and practice of research methodology, data analysis, and report writing in psychology. Topics covered include design and measurement issues, methods for analysing psychological data, procedures involved in the reporting of psychological research, and issues concerned with the interpretation of such research.
Course contact
Course staff
Lecturer
Dr Christoph Klebl
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
The aim of this course is to expand students' understanding of theory and practice of research methodology, data analysis, and report writing in psychology. Topics covered include design and measurement issues, methods for analysing psychological data, procedures involved in the reporting of psychological research, and issues concerned with the interpretation of such research.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Critically review and apply the theoretical background of, application of, and mathematical formulation for the following statistical procedures: 1. z-test 2. Repeated measures and independent groups t-tests 3. Power 4. ANOVA 5. Correlation 6. Multiple regression 7. Non-parametric versions of each of the above
LO2.
Interpret results from statistical analyses involving multiple independent variables or predictors, and identify the implications of the results for hypotheses and research questions.
LO3.
Report and discuss the results of statistical analyses that involve multiple independent variables or predictors, following standard conventions in Psychology.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Paper/ Report/ Annotation | LITERATURE REVIEW | 35% |
2/05/2025 4:00 pm |
| Presentation | PRESENTATION | 30% |
23/05/2025
In the final workshop |
| Paper/ Report/ Annotation | BUSINESS REPORT | 35% |
16/06/2025 4:00 pm |
Assessment details
LITERATURE REVIEW
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 35%
- Due date
2/05/2025 4:00 pm
- Learning outcomes
- L01, L02
Task description
In this Assignment 1, you will be asked to conduct and write a literature review of research relating to employee turnover. Your literature review should include
- A description of the topic that is being investigated.
- A summary of findings of previous studies relating to that problem.
- A critique of the previous research and recommendations for new research that addresses the issues raised.
Submission guidelines
Your assignment should be submitted via email attachment to the course coordinator.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
For full details please review the School of Psychology Student Guidelines - Extensions and Deferred quiz/exam.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
PRESENTATION
- Mode
- Activity/ Performance
- Category
- Presentation
- Weight
- 30%
- Due date
23/05/2025
In the final workshop
- Learning outcomes
- L01, L02, L03
Task description
In Assignment 2, you will be asked to deliver a presentation (in the final workshop) based on your literature review and the t-test and ANOVA analyses you've been conducting. Your presentation should include:
- A description of the problem that may affect an organisation (drawing on appropriate academic sources to support your arguments).
- A summary of the results of the literature review relating to the problem.
- A description of how the data were collected and analysed.
- A summary of the findings in non-technical language, but using figures and tables where appropriate.
- A discussion of the implications of the findings in relation to organisational outcomes such as the physical and mental health of the employees, implications for productivity etc.
Submission guidelines
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
In case of illness, the presentation may be rescheduled to the next workshop session.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
For full details please review the School of Psychology Student Guidelines - Extensions and Deferred quiz/exam.
BUSINESS REPORT
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 35%
- Due date
16/06/2025 4:00 pm
- Learning outcomes
- L01, L02, L03
Task description
In Assignment 3, you will be asked to write a business report. The business report builds on your presentation by incorporating the new results from your correlation and regression analyses.
Submission guidelines
The report should be submitted via email attachment to the course coordinator.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
For full details please review the School of Psychology Student Guidelines - Extensions and Deferred quiz/exam.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Percent | Description |
|---|---|---|
| 1 (Low Fail) | 0 - 29.99 |
Absence of evidence of achievement of course learning outcomes. |
| 2 (Fail) | 30 - 46.99 |
Minimal evidence of achievement of course learning outcomes. |
| 3 (Marginal Fail) | 47 - 49.99 |
Demonstrated evidence of developing achievement of course learning outcomes |
| 4 (Pass) | 50 - 64.99 |
Demonstrated evidence of functional achievement of course learning outcomes. |
| 5 (Credit) | 65 - 74.99 |
Demonstrated evidence of proficient achievement of course learning outcomes. |
| 6 (Distinction) | 75 - 84.99 |
Demonstrated evidence of advanced achievement of course learning outcomes. |
| 7 (High Distinction) | 85 - 100 |
Demonstrated evidence of exceptional achievement of course learning outcomes. |
Supplementary assessment
Supplementary assessment is available for this course.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Library resources are available on the UQ Library website.
Other course materials
Recommended
| Item | Description | Further Requirement |
|---|---|---|
| Navarro DJ and Foxcroft DR (2019). learning statistics with jamovi: a tutorial for psychology students and other beginners. (Version 0.70). DOI: 10.24384/hgc3-7p15 | https://www.learnstatswithjamovi.com/ | |
| Rafi, J. (2020). The jamovi quickstart guide. | https://www.jamoviguide.com/index.html |
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Week 1 (24 Feb - 02 Mar) |
Lecture |
Lecture 1. Overview and Z distributions This lecture covers normal distributions and z-scores. Learning outcomes: L01 |
Week 2 (03 Mar - 09 Mar) |
Lecture |
Lecture 2. Single sample tests This lecture covers hypothesis-testing, single sample tests (when the POPULATION variance is known (Z test) and the POPULATION variance is not known (single sample t test). Learning outcomes: L01 |
Workshop |
Workshop 1. Overview and Literature Review In this workshop, we'll discuss the aims and objectives of this course, and learn how to conduct a literature review. Learning outcomes: L02 |
|
Week 3 (10 Mar - 16 Mar) |
Lecture |
Lecture 3. t-tests This lecture covers two sample tests, using the same people twice (repeated measures t-test) and two different groups (independent groups t-test). We will also cover the assumptions of t-tests Learning outcomes: L01 |
Week 4 (17 Mar - 23 Mar) |
Lecture |
Lecture 4. Power and effect size This lecture covers power and effect size. Learning outcomes: L01 |
Workshop |
Workshop 2. Working with Data In this workshop, we will begin working with data. We'll focus on data management and data visualisation. Learning outcomes: L02 |
|
Week 5 (24 Mar - 30 Mar) |
Lecture |
Lecture 5. ANOVA I (one-way independent groups) This lecture is the first of four lectures covering the most frequently used analysis for group designs: Analysis of Variance (ANOVA). An overview of one-way ANOVA will be presented, including the calculation of the omnibus test, partitioning of variance, and the underlying structural model. Learning outcomes: L01 |
Workshop |
Workshop 3. t-tests and ANOVA In this workshop, we will learn how to run and interpret the results of statistical tests. We'll being with t-tests and analyses of variance (ANOVAs) using JOMAVI. Learning outcomes: L01, L02, L03 |
|
Week 6 (31 Mar - 06 Apr) |
Lecture |
Lecture 6. ANOVA II (Follow-up tests) This lecture continues from the calculation of the omnibus tests of the overall one-way to assess group differences using planned comparisons and post-hoc tests. Learning outcomes: L01 |
Week 7 (07 Apr - 13 Apr) |
Lecture |
Lecture 7. ANOVA III (Repeated Measures) This is the third lecture on ANOVA. In this lecture, students will be shown how the analysis of variance can be used to test repeated time points. Learning outcomes: L01 |
Workshop |
Workshop 4. Correlation and Regression I In this workshop, we will continue running and interpreting statistical analyses, focusing this time on correlation and regression analyses. Learning outcomes: L01, L02 |
|
Week 8 (14 Apr - 20 Apr) |
Lecture |
Lecture 8. ANOVA IV Factorial & Non-Parametric This lecture is the fourth lecture on ANOVA and begins a new topic on analyses that can be used to test data that do not meet the assumptions required to use t-tests or ANOVA. Learning outcomes: L01 |
Mid-sem break (21 Apr - 27 Apr) |
No student involvement (Breaks, information) |
Mid-semester break: No lecture this week. Learning outcomes: L01 |
Week 9 (28 Apr - 04 May) |
Lecture |
Lecture 9: Chi-Square This lecture will focus on the Chi-Square tests. Learning outcomes: L01 |
Workshop |
Workshop 5. Correlation and Regression II In this workshop, we will continue with correlation and regression analyses. Learning outcomes: L01, L02, L03 |
|
Week 10 (05 May - 11 May) |
Lecture |
Lecture 10. Correlations I This lecture introduces correlations, focusing on the calculation of r, variance accounted (r square), and non-parametric versions of r. Learning outcomes: L01 |
Week 11 (12 May - 18 May) |
Lecture |
Lecture 11. Correlation II & Regression In this lecture, the concept of correlation (relationship between two variables) is extended to regression (using a known association to make a prediction). Learning outcomes: L01 |
Workshop |
Workshop 6. Presentations In this workshop, students will deliver their presentations. Learning outcomes: L01, L02, L03 |
|
Week 12 (19 May - 25 May) |
Lecture |
Lecture 12. Regression In this final lecture, the concept of regression is further extended. Learning outcomes: L01 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.
School guidelines
Your school has additional guidelines you'll need to follow for this course: