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Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title Research Methods & Statistics 2
Module Code PSYC212
School 37
Module Co-ordinatorSemester 1: Johannes Karl
Semester 2: Johannes Karl
Autumn: Johannes Karl
Module TeachersLisa Fitzgerald
Johannes Karl
NFQ level 8 Credit Rating 5
Pre-requisite None
Co-requisite None
Compatibles None
Incompatibles None
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.



Workload Full-time hours per semester
Type Hours Description
Lecture36Psychological skills are supported using learning activities analysing data sets
Independent Study39Write up of practicals, becoming familiar with statistical concepts and research methods, identifying and critiquing key readings, report and tutorial preparation
Online activity13Students will access digital resources relating to statistical reasoning, data entry and data visualisation
Online activity37Students 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 Assessment100% Examination Weight0%
Course Work Breakdown
TypeDescription% of totalAssessment Date
Loop QuizCompletion of online six Loop quizzes relating to the content of the module.12%n/a
Loop QuizCompletion 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 submission10%n/a
Reassessment Requirement Type
Resit arrangements are explained by the following categories;
1 = A resit is available for all components of the module
2 = No resit is available for 100% continuous assessment module
3 = No resit is available for the continuous assessment component
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.
Programme or List of Programmes
BPDTBSc Psychology & Disruptive Technologies
BPMBSc in Psychology with Mathematics
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