Module overview

Topics covered will include: • The strengths and weaknesses of correlational designs • How to construct a questionnaire • Psychometrics in classical test theory (including reliability, validity, and exploratory factor analysis) • Correlation analyses (Bivariate correlation, partial correlation, and non-parametric correlation) • Multiple linear regression (including hierarchical regression) • Logistic regression (including binary and multinomial logistic regression) • Extensions to regression using mediation and moderation Sessions will be structured to enable an understanding of the appropriate use of and assumptions relating to analyses, the recommended sample size to ensure sufficient power for a given effect size, a step-by-step guide to carrying out analyses in SPSS, interpreting SPSS output, and how to report results. Employability Skills The transferable skills you will develop during this module include: • Research and Inquiry - Research and Inquiry underpin the formulation of well-informed new ideas and a creative approach to problem resolution and entrepreneurial behaviours • Academic - Academic attributes are the tools that sustain an independent capacity to critically understand a discipline and apply knowledge • Communication Skills - Communication Skills encompass an individual’s ability to demonstrate knowledge, and to express ideas with confidence and clarity to a variety of audiences • Reflective Learner - The Reflective Learner is capable of the independent reflection necessary to develop their learning and continuously meet the challenge of pursuing excellence Alignment with Research Development Framework (RDF) and Transferable skills acquired (RDF employability lens): Sub domain A1 (Knowledge base) Knowledge of: • The methods and experimental techniques appropriate for research design • Literacy and numeracy skills and language abilities appropriate for research Behaviour: • Identifies, applies and develops methods and experimental techniques appropriate for research projects Sub domain A2 (Cognitive abilities) Behaviour: • Analyses and evaluates findings using appropriate methods • Recognises and validates problems; formulates and applies solutions to a range of research problems One of the pre-requisites for PSYC8042. The module assumes a level of prior knowledge of statistical methods and SPSS equivalent to that provided during an undergraduate degree in Psychology.

Details

School	Module Code	Credit Points	Level
School of Psychology	RESM6011	10	Level 7

Staff

Module Lead
Sarah Kirby

Requisites

Requisites are modules you must have before or at the same time as this module.

For RESM6011 there are no requisites.

Aims

The purpose of this module is to refresh and build upon statistical knowledge and skills acquired during undergraduate research methods training. This correlational methods module is divided into six sessions that cover relevant methodological concepts used in applied psychology and hands-on experience using SPSS. Sessions will be primarily in-person with some supplementary online materials to support independent study, and will comprise lectures, SPSS demonstrations, quizzes and activities to practice what has been learnt.

Learning Outcomes

Reference	Learning Outcome
LO1	critically evaluate the strengths and limitations of correlational research designs.
LO2	evaluate whether the use of correlational techniques is appropriate.
LO3	apply relevant factors in operationalising variables and designing questionnaires.
LO4	demonstrate practical skills in psychometric evaluation of the reliability and validity of questionnaire data
LO5	apply and report correlational techniques appropriately, with specific reference to: Applying parametric assumptions and data checking requirements, sample size calculations, carrying out relevant analyses using SPSS, Interpreting and communicating results of analyses at a professional level

Syllabus summary

1. Correlational designs and questionnaire development. 2. Bivariate correlation, partial correlation, and non-parametric correlation. 3. Principal component analysis and exploratory factor analysis. 4. Multiple Linear Regression (including hierarchical regression) & Logistic regression (binary and multinomial). 5. Interactions in regression: Moderation analysis. 6. Simple path analysis using regression: Mediation analysis.

Learning and Teaching Summary

Learning and teaching methods

This is a 10 CATS (5 ECTS) module, which translates into a total study time of 100 hours. These 100 hours are split into 18 teaching hours and 82 hours of independent study. The 18 teaching hours will be spread out across six sessions (3 hours per session). Sessions will be primarily in-person with some supplementary online materials to support independent study, and will comprise lectures, SPSS demonstrations, quizzes and activities during which you will be able to gain hands-on experience using the techniques described in the lectures, and give you the opportunity to reinforce your learning from lectures and independent study.

Study Time

Type	Hours
Completion of assessment task	24 hrs
Lecture	12 hrs
Practical classes and workshops	6 hrs
Preparation for scheduled sessions	12 hrs
Wider reading or practice	46 hrs
Total study time	100 hrs

Assessment and Feedback Summary

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Costs

Health & Safety

no identifiable risks

Resources

Optional

Essential

Key

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