Module: Group Research Project & Advanced Statistics

Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title	Group Research Project & Advanced Statistics
Module Code	PSYC308
School	37
Module Co-ordinator	Semester 1: Simon Dunne Semester 2: Simon Dunne Autumn: Simon Dunne
Module Teachers	Simon Dunne
NFQ level	8	Credit Rating	7.5
Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

None

Description

This module will provide an understanding of advanced statistical tests, when to use them, how to report them and how to interpret them. This module will also enable students to work as a team in designing, carrying out and reporting a research project within the subject of psychology. Each group will be facilitated by an experienced staff member who will provide guidance and advice throughout the process.

Learning Outcomes

1. Explain what multivariate analysis is and when its application is appropriate
2. Explain the appropriate usage of and interpret the results of dependence and interdependence multivariate techniques
3. Evaluate and review empirical research using multivariate statistics
4. Work in a group towards a common research goal
5. Disseminate research findings as a research poster

*Type*	*Hours*	*Description*
Workload	Full-time hours per semester
Lecture	10	Asynchronous online lecture content for review
Laboratory	10	Face to face facilitated sessions to progress group research
Laboratory	20	Synchronous Online Computer based workshops
Tutorial	4	Synchronous Online Statistics Based Tutorials for Exam Preparation
Class Presentation	1	Face-to-Face Conference Style Poster Presentation session
Group work	85.5	Independent Group Project work for key project stages, writing research report and preparing poster
Independent Study	57	Preparation for Exam
Total Workload: 187.5

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

Preparing for multivariate analysis (e.g. examining your data, missing data analysis, outliers, assumptions, data transformation)

Dependence techniques (e.g. multiple regression analysis, logistic regression, multivariate analysis of variance)

Interdependence techniques (e.g. factor analysis)

Research dissemination

Assessment Breakdown
Continuous Assessment	60%	Examination Weight	40%

Type	Description	% of total	Assessment Date
Course Work Breakdown
Group project	Group project written assessment work (including group report)	45%	n/a
Poster presentation	Research Poster	15%	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

Allen, P, Bennett, K. & Heritage, B.: 2019, SPSS Statistics: A Practical Guide, 4th, Cengage, 9780170421140
Field, A.: 2018, Discovering Statistics Using IBM SPSS Statistics, 5th, Sage, London, 9781526419521
Dancey, C. & Reidy, J.: 2011, Statistics without maths for Psychology, Prentice Hall, New Jersey, 9780273726029
Pallant, J.: 2016, SPSS Survival Manual, 6th, Open University Press, Maidenhead, 978-033526154
Tabachnick, B. G., & Fidell, L. S.: 2012, Using Multivariate Statistics, Ch 4, Pearson Education, Harlow,
Bell, J. (2010).: 0, Doing Your Research Project: A Guide for First Time Researchers in Education, Health and Social Science, Open University Press, Maidenhead,
Brace, N., Kemp, R., & Snelgar, R.: 2012, SPSS for Psychologists: A Guide to Data analysis using SPSS for Windows, Palgrave Macmillan, Basingstoke,
Denzin, N. K., & Lincoln, Y. S.: 2011, The Sage Handbook of Qualitative Research, Sage, London,
Gravetter, F. J., & Wallnau, L. B.: 2012, Statistics for the Behavioral Sciences, Wadsworth, Belmont, CA,
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L.: 2010, Multivariate Data Analysis, Pearson Prentice Hall, Upper Saddle River, NJ,
Hinkle, D. E., Wiersma, W., & Jurs, S. G.: 2009, Applied Statistics for the Behavioral Sciences, Houghton Mifflin, Boston,
Levin, P.: 2004, Successful Teamwork!, Open University Press, Maidenhead,
Rasch, D., Kubinger, K. D., Yanagida, T.: 2012, Statistics in Psychology Using R and SPSS, John Wiley and Sons, Hoboken, NJ,

Other Resources

None

Programme or List of Programmes

BPY	BSc (Honours) in Psychology

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