Module: Research Methods & Statistics 2

Module Specifications.

Current Academic Year 2024 - 2025

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Date posted: September 2024

Module Title	Research Methods & Statistics 2
Module Code	PSYC212 (ITS) / PSY1032 (Banner)
Faculty	Science & Health	School	Psychology
Module Co-ordinator	Johannes Karl
Module Teachers	Lisa Fitzgerald
NFQ level	8	Credit Rating	5
Pre-requisite	Not Available
Co-requisite	Not Available
Compatibles	Not Available
Incompatibles	Not Available

Coursework Only

Description

This module builds on PSYC113 and PSYC114 in year 1 and introduces students to more advanced quantitative research methodologies, designs, and analytical techniques in psychology, including applied psychology and technology-focused research. It also introduces students to advanced regression techniques (multiple regression and moderation) and their specific incarnations in tests such as ANOVAs, their appropriate usage and how to compute them. Practical experience through laboratory experiments and computer-based exercises will continue.

Learning Outcomes

1. Discuss quantitative research designs and methods, and assess their strengths and limitations
2. Understand the principles of regression, appropriately carry out such analyses and report statistical results in a manner consistent with APA recommendations.
3. Identify the importance of power and effect size when carrying out any analysis
4. Be proficient in identifying the limitations of specific methodologies and in understanding the relative merits of quantitative approaches to an identified research question
5. Think critically about research to identify the strengths and weaknesses of design, methods, analysis, data, and conclusion
6. Use advanced searching skills to effectively use library and online psychology resources
7. Gain an understanding of data structures and data in the real world
8. Communicate data through statistical, graphical, and verbal means.
9. Develop, analyze, and interpret complex research designs, incorporating modulating factors.
10. Gain first hand research experience by participating in psychological research projects within the school including those of staff, post-graduate students and undergraduate final year projects.

*Type*	*Hours*	*Description*
Workload	Full-time hours per semester
Lecture	36	Psychological skills are supported using learning activities analysing data sets
Independent Study	39	Write up of practicals, becoming familiar with statistical concepts and research methods, identifying and critiquing key readings, report and tutorial preparation
Online activity	13	Students will access digital resources relating to statistical reasoning, data entry and data visualisation
Online activity	37	Students will complete topic-related loop quizzes and access directed online resources that describe the fundamental concepts of statistics and relate to the processes involved in statistical modeling.
Total Workload: 125

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

Advanced information literacy skills

Describing and exploring Data using advanced graphs

Multiple Regression

Moderated Regression

Special Cases of Regression (ANOVA, Binary Data)

Open Science, Statistical power, Effect Size

Experimental and Survey Design with complex Dependencies

Assessment Breakdown
Continuous Assessment	100%	Examination Weight	0%

Type	Description	% of total	Assessment Date
Course Work Breakdown
Loop Quiz	Completion of online six Loop quizzes relating to the content of the module.	12%	n/a
Loop Quiz	Completion of online four Loop quizzes relating to the content of the module, combined with a section covering the writeup of a statistical test.	28%	n/a
Report(s)	Write-up of a complete APA-style psychology report with revision opportunity worth 50% of overall module grade.	50%	n/a
Report(s)	Structured response letter to the initial report submission	10%	n/a

Reassessment Requirement Type
Resit arrangements are explained by the following categories: Resit category 1: A resit is available for both* components of the module. Resit category 2: No resit is available for a 100% continuous assessment module. Resit category 3: No resit is available for the continuous assessment component where there is a continuous assessment and examination element.
* ‘Both’ is used in the context of the module having a Continuous Assessment/Examination split; where the module is 100% continuous assessment, there will also be a resit of the assessment
This module is category 1

Indicative Reading List

Rajiv S. Jhangiani: 2019, Research Methods in Psychology, https://kpu.pressbooks.pub/psychmethods4e, 1085976920
Garrett Grolemund,Hadley Wickham: 2017, R for Data Science, https://r4ds.had.co.nz/, 1491910399
American Psychological Association: 2018, Publication Manual of the American Psychological Association (7th ed.),
Russell A. Poldrack: 2018, Statistical Thinking for the 21st century, https://statsthinking21.github.io/statsthinking21-core-site/,
Thulin, M.: 2021, ). Modern Statistics with R.,
Dr Peter Allen,Kellie Bennett,Dr Brody Heritage: 2018, SPSS Statistics: A Practical Guide with Student Resource Access 12 Months, 4th, Cengage AU, 9780170421140
Andy Field,Jeremy Miles,Zoë Field: 2012, Discovering Statistics Using R, SAGE Publications, 9781446200469
Cozby,Scott Bates: 2018, Methods in Behavioral Research, 13th Ed, Mc Graw Hill, 9781260084207
Cohen, B.H.: 2013, Explaining psychological statistics, 4th, Wiley, 9781118436608
Barbara G. Tabachnick,Linda S. Fidell,Jodie B. Ullman: 2019, Using Multivariate Statistics, Pearson, 9780134790541

Other Resources

None

Readings will be supplemented by items such as journal articles, readers in psychology, and material prepared for lectures and practical sessions.