Module: Quantitative Research in Psychology

Module Specifications

Academic Year 2025 - 2026

Module Title	Quantitative Research in Psychology
Module Code	PSY1113
Faculty	Science & Health	School	Psychology
NFQ level	8	Credit Rating	15

Description

This module develops students’ understanding of quantitative research in psychology and builds the skills needed to analyse, interpret, and communicate numerical data to answer psychological research questions. Students will learn to manage datasets, select appropriate statistical techniques, and conduct analyses in SPSS using clear and reproducible workflows. Through applied work with psychological datasets, students will develop competence in data visualisation, hypothesis testing, critical evaluation and interpretation of statistical findings, and the reporting of results in line with APA conventions. By the end of this module, students will be able to apply quantitative methods confidently and communicate evidence-based conclusions clearly and rigorously.

Learning Outcomes

1. Explain how quantitative research is designed, conducted, and evaluated in psychology, including ethical considerations and reproducibility principles.
2. Manage and prepare psychological datasets through appropriate data cleaning, coding, documentation, and the use of reproducible SPSS workflows.
3. Select and justify appropriate statistical approaches for answering psychological research questions, considering measurement level, research design, and analytical assumptions.
4. Conduct, interpret, and critically evaluate quantitative analyses in SPSS, assessing assumptions, effect sizes, and the strength of statistical evidence.
5. Communicate quantitative research processes and findings clearly and professionally through appropriate statistical reporting, data visualisation, and written formats consistent with APA standards.

*Type*	*Hours*	*Description*
Workload	Full time hours per semester
Lecture	45	Synchronous online classes
Online activity	60	Student-Staff and Student-Student interaction through online discussion forums and other media
Independent Study	270	Using self-directed learning module resources, textbooks and other resources
Total Workload: 375

Section Breakdown
CRN	12099	Part of Term	Semester 1 & 2
Coursework	100%	Examination Weight	0%
Grade Scale	40PASS	Pass Both Elements	N
Resit Category	RC1	Best Mark	N
Module Co-ordinator	Catherine Moran	Module Teacher

Type	Description	% of total	Assessment Date
Assessment Breakdown

Reassessment Requirement Type
Resit arrangements are explained by the following categories; RC1: A resit is available for both^* components of the module. RC2: No resit is available for a 100% coursework module. RC3: No resit is available for the coursework component where there is a coursework and summative examination element. ^* ‘Both’ is used in the context of the module having a coursework/summative examination split; where the module is 100% coursework, there will also be a resit of the assessment

Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Foundations of quantitative research and SPSS essentials

Summarising psychological data: Descriptive statistics and data visualisation

Statistical Interference and Group Comparisons: Comparing Two Groups

Comparing More Than Two Groups – ANOVA

Power and effect sizes in psychological research

Exploring relationships: Correlation and simple regression

Multiple Regression and Model Building

Categorical data analysis: Chi-square and logistic regression

Measuring psychological constructs: Psychometrics and factor analysis

Advanced ANOVA designs and reporting

Indicative Reading List

Books:

Breakwell, G. M., Smith, J. A. and Wright, D. B.: 2012, Research Methods in Psychology, Fourth Ed., SAGE Publications Ltd, London,
Field, A.: 2018, Discovering Statistics using SPSS, 5th Ed., Sage, London,
Gray, D. E.: 2018, Doing Research in the Real World, Sage, London,
Pallant, J.: 2020, SPSS survival manual: A step by step guide to data analysis using IBM SPSS, 7th Ed., McGraw-Hill Education, London, England,
Tabachnick, B. G., & Fidell, L. S.: 2013, Using Multivariate Statistics, 6th Ed., Pearson, UK,

Articles:
None

Other Resources

None