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Module Specifications.

Current Academic Year 2024 - 2025

All Module information is indicative, and this portal is an interim interface pending the full upgrade of Coursebuilder and subsequent integration to the new DCU Student Information System (DCU Key).

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Date posted: September 2024

Module Title Group Research Project & Advanced Statistics
Module Code PSYC308 (ITS) / PSY1096 (Banner)
Faculty Science & Health School Psychology
Module Co-ordinatorSimon Dunne
Module Teachers-
NFQ level 8 Credit Rating 7.5
Pre-requisite Not Available
Co-requisite Not Available
Compatibles Not Available
Incompatibles Not Available
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



Workload Full-time hours per semester
Type Hours Description
Lecture10Asynchronous online lecture content for review
Laboratory10Face to face facilitated sessions to progress group research
Laboratory20Synchronous Online Computer based workshops
Tutorial4Synchronous Online Statistics Based Tutorials for Exam Preparation
Class Presentation1Face-to-Face Conference Style Poster Presentation session
Group work85.5Independent Group Project work for key project stages, writing research report and preparing poster
Independent Study57Preparation 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 Assessment60% Examination Weight40%
Course Work Breakdown
TypeDescription% of totalAssessment Date
Group project Group project written assessment work (including group report)45%n/a
Poster presentation Research Poster15%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

  • 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

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