PSY30350 Research Methods & Stats III

Academic Year 2023/2024

This module is designed to develop students' understanding of advanced methodological and statistical techniques in psychological research. The module will teach students why, when and how to use these advanced methods and statistical techniques in psychology. Techniques include qualitative data analysis, power analysis, complex designs, ANCOVA, two-way ANOVA, tests of simple effects for interaction, linear regression and mixed methods designs. Over the course of the module students will practice these techniques by hand and using common software analysis tools. The emphasis is on understanding the nature and role of complex designs and the interpretation of data within a psychological context. To facilitate learning, in-class examples are used throughout the trimester.

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Curricular information is subject to change

Learning Outcomes:

On completion of this module students should be able to:
1. Conduct and critically evaluate an example of qualitative data analysis.
2. Demonstrate an understanding of and carry out a priori power analysis.
3. Demonstrate an understanding of complex designs, including the implications of an interaction effect and the type of interaction.
4. Conduct various complex analyses with more than one variable including ANCOVA, two-way ANOVA and tests of simple main effects.
5. Demonstrate an understanding of and carry out linear regression analysis.

Student Effort Hours: 
Student Effort Type Hours
Lectures

20
Tutorial

3
Seminar (or Webinar)

4
Specified Learning Activities

20
Autonomous Student Learning

78
Total

125
Approaches to Teaching and Learning:
Research design and statistical analysis is a skill, akin to learning a language or a physical technique, rather than some “correct” information that you should know. For this reason, students’ skill is practiced over the course of the module. Students need to be prepared for a career where they can adapt their analyses to suit different research design and topic contexts. Key tests are presented in specific examples and students are required to continuously practice these with different examples to build up their skills. As we move through the content in the module, later topics will build on the skills of earlier topics and so students will benefit from working hard in the earlier weeks so refine skills in later weeks. As with other skill development, exposure, repetition, feedback, discussion, group-work, and participation are encouraged/required for students to achieve the learning outcomes for this module. 
Requirements, Exclusions and Recommendations
Learning Recommendations:

PSY20160 Research Methods & Statistics II


Module Requisites and Incompatibles
Pre-requisite:
PSY20160 - Research Methods & Stats II, PSY30100 - Intermediate Analysis and Desi

Additional Information:
Pre-requisites: one of the listed modules.

Equivalents:
Advanced Analysis and Design (PSY40010)


 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: Conduct and report a short analysis of qualitative data Week 5 n/a Graded No

30
Portfolio: Participation portfolio Throughout the Trimester n/a Alternative linear conversion grade scale 40% No

30
Examination: Assessment on statistical analyses 2 hour End of Trimester Exam No Standard conversion grade scale 40% No

40

Carry forward of passed components
Yes
 
Resit In Terminal Exam
Spring Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
• Peer review activities
• Self-assessment activities

How will my Feedback be Delivered?

Individual feedback on mid-semester assignment is provided online. Solutions and feedback are provided in class on participation activities. These allow for self/peer assessment. All learning from participation activities is applied in the end-of-semester exam.

Name Role
Dr Brendan Rooney Lecturer / Co-Lecturer
Jordan Crupper Tutor
Hau Nguyen Tutor
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
 
Autumn
      
Lecture Offering 1 Week(s) - 1 Wed 10:00 - 11:50
Lecture Offering 1 Week(s) - 2, 3, 4, 5, 6, 7, 9, 10, 11, 12 Wed 10:00 - 11:50
Tutorial Offering 1 Week(s) - 3, 6, 9 Mon 14:00 - 14:50
Tutorial Offering 2 Week(s) - 3, 6, 9 Mon 17:00 - 17:50
Tutorial Offering 3 Week(s) - 3, 6, 9 Wed 09:00 - 09:50
Tutorial Offering 4 Week(s) - 3, 6, 9 Wed 15:00 - 15:50
Tutorial Offering 5 Week(s) - 3, 6, 9 Fri 13:00 - 13:50
Autumn