Methods and Statistics in Psychology II

Module titleMethods and Statistics in Psychology II
Module codePSY2206
Academic year2018/9
Module staff

Dr Cris Burgess (Convenor)

Duration: Term123
Duration: Weeks



Number students taking module (anticipated)


Description - summary of the module content

Module description

This module will extend your knowledge and the skills necessary to understand and conduct research in psychology. You will increase your understanding of the main scientific research methods, their advantages and disadvantages, and areas of application. You will also develop your skills in writing (scientific) reports and using library and online resources for scientific research, as well as extending your understanding of ethical issues related to conducting research in psychology.

Most psychological research involves quantitative analysis of numerical data. The main purpose of the statistical analysis sections of this module is to introduce you to techniques that represent extensions of the General Linear Model (GLM), introduced in PSY1205. Hence, it is important that you have an understanding of the basic concepts in research statistics delivered in PSY1205; the distinction between descriptive and inferential statistics, statistical significance and significance testing, as well as practical experience of using relevant statistical software for carrying out between-subjects analysis of variance (ANOVA) procedures.

The module continues the discussion of what is almost certainly the most widely used statistical method within Psychology, analysis of variance (ANOVA), describing between-subjects ANOVA, contrasts and multi-factorial designs, and goes on to introduce linear regression. The module discusses conceptual issues and provides hands-on experience of using statistical software for carrying out such analyses in the practical classes.

The statistical techniques covered in this module are widely used within Psychology, but also within other disciplines, such as Business, Biosciences, Geography and Sport and Health Sciences.

Module aims - intentions of the module

The central objective of this module is to provide you with the skills to carry out research in psychological domains, analyse relevant datasets using statistical software to carry out within-subjects ANOVA and multiple linear regression, and interpret the results, allowing you to then report your findings using relevant reporting conventions. These skills will assist you in your practical work at this level and the Final Year Research Project.

A broader objective is to equip you with the skills to understand published research papers that employ these methods and forms of analysis, allowing you to understand the Methods and Results sections of such papers and provide opportunities for critical appraisal of the methods used to collect and analyse data, and to critically assess the conclusions drawn by the authors.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

  • 1. Carry out effective and efficient online literature searches
  • 2. Write psychology research reports
  • 3. Identify the practice of psychology as an ethical science
  • 4. Identify weaknesses in specific methodologies and understand the relative merits of quantitative and qualitative approaches
  • 5. Describe the conceptual basis and the purpose of analysis of variance and multiple linear regression
  • 6. Carry out ANOVA and regression quickly and without error using the most widely available computer statistical software, Statistical Package for the Social Sciences (SPSS)
  • 7. Interpret ANOVA and regression results correctly and report the results using journal conventions
  • 8. Interpret the results of research using these methods
  • 9. Decide when it is appropriate to use these techniques for purposes of analysing data for any projects they are planning and collect data in an appropriate form so that the analysis can be used properly

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

  • 10. Review and evaluate published work and identify some of the strengths and weaknesses of this work, and at a basic level structure this literature to present logical and coherent arguments
  • 11. Address well-defined problems systematically, think critically and creatively, and begin to appreciate the complexities of the issues at a basic level
  • 12. Learn quickly how to use new or more advanced forms of analysis should the need arise
  • 13. Evaluate and analyse critically empirical evidence
  • 14. Identify and evaluate critically the strengths and weaknesses of published work
  • 15. Apply detailed knowledge and understanding of critical principles in designing research
  • 16. Demonstrate awareness of ethical issues relating to the subject and its application

ILO: Personal and key skills

On successfully completing the module you will be able to...

  • 17. Manage information, collect appropriate information from a range of sources and undertake essential study tasks under guidance
  • 18. Use and interpret statistical data with a scope extending well beyond the coverage of the module itself
  • 19. Master a sophisticated software package on a largely self-taught basis (including use of Help facility provided with the software)
  • 20. Use electronic information including resources posted on the module ELE page
  • 21. Work individually and in small groups, tackling and completing complex tasks effectively

Syllabus plan

Syllabus plan

Statistics topics covered on this module will include:

Analysis of Variance (ANOVA):

  • Revision of basic concepts in ANOVA including SPSS methods for running 1-, 2- and 3-way univariate analyses and instructions for running planned and post-hoc comparisons.
  • Introduction to repeated measures designs. SPSS methods for running repeated-measures ANOVAs; Sphericity assumption; Greenhouse-Geisser and Huynh-Feldt procedures for dealing with sphericity violations.
  • SPSS procedures for 1 and 2-way repeated-measures and mixed designs; dealing with planned and unplanned contrasts on repeated measures factors.
  • More complex repeated-measures and mixed designs; overview, including interpretation of error terms and of 3-way interactions, use of decision-tree to select analyses, review of treatment of fixed and random effects etc.
  • Assumptions and robustness of ANOVA. When not to use it. Power of ANOVA designs.
  • Explanation of use of Monte Carlo methods for assessing robustness; Introduction to multivariate techniques:
  • Relevance of the General Linear Model in linking ANOVA with multivariate statistical techniques.

Linear regression

  • From ANOVA to Regression: aims to show how Regression relates to ANOVA, and gives some general rules for Multiple Regression; From Simple to Multiple Regression: describes regression with more than one regressor and explains how to assess a model's goodness of fit.
  • Multiple Regression in Practice: uses ‘real life’ examples to demonstrate utility of technique, and uses SPSS demonstrations to show how to carry out analyses.
  • Model Checking: explains how to report Multiple Regression analyses, and how to check the model using residuals analysis.
  • Reporting conventions and interpretation: how to correctly report analyses and how to interpret such analyses in published research.
  • Choosing Between Regression Models: how to choose regressors for a regression model, and how to choose between models.
  • Regression with Categorical Variables: how to deal with unordered category (nominal) variables as regressors in a regression model using dummy variables.

In addition, the following research methodology topics will be covered:

  • Online literature searches
  • Practical report guidance
  • Questionnaire and survey design
  • Qualitative methods and discourse analysis
  • Ethical considerations in research
  • Clinical research methods
  • Developmental research methods
  • Psychophysiological research methods
  • Animal behaviour research methods

Learning and teaching

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching ActivitiesGuided independent studyPlacement / study abroad

Details of learning activities and teaching methods

CategoryHours of study timeDescription
Scheduled Learning and Teaching33Lectures
Scheduled Learning and Teaching12Examples classes
Guided Independent Study12Completing the weekly assignments using online resources and support via ELE
Guided Independent Study93Revision and wider reading


Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Weekly exercise12 x 1 hour5-9, 17-21Personal contact with module convenor and demonstrators within practical classes
Formative online tests (via module ELE page)30 minutes per week1-20Automatic feedback provided on-screen in response to correct/incorrect student responses

Summative assessment (% of credit)

CourseworkWritten examsPractical exams

Details of summative assessment

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
Examination1003 hours1-16Generic feedback posted on module ELE page.


Details of re-assessment (where required by referral or deferral)

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
ExaminationExamination1-16Aug Ref/Def

Re-assessment notes

One assessment is required for this module. Where you have been referred/deferred in the examination you will have the opportunity to take a second examination in the August/September re-assessment period. If you are successful on referral, your overall module mark will be capped at 40%; deferred marks are not capped.


Indicative learning resources - Basic reading

Core reading:

  • Field, A, (2013) Discovering Statistics Using SPSS (4th Revised Edition) London: Sage.
  • Haslam, S. A., and McGarty, C. (2003). Research methods and statistics in psychology. London, UK and Thousand Oaks,CA: Sage.
  • Pallant, J. (2013) SPSS survival manual (5th Edition) Maidenhead, Berks.: OUP/McGraw-Hill Education.

Recommended reading:

  • Harris, P. (2002) Designing and Reporting Experiments in Psychology (2nd Edition) Buckingham: OUP.
  • Howell, D. C. (1997). Statistical Methods for Psychology (4th Edition) Belmont, Calif.: Duxbury Press. (Earlier editions also include most of what you need, as does Howell’s book on: “Fundamental statistics for the behavioral sciences”).
  • Howell, D.C. (1995). Fundamental Statistics for the Behavioural Sciences (3rd Edition). Duxbury.
  • Howitt, D. & Cramer, D. (2008) Introduction to Statistics in Psychology (4th Edition) Harlow, Essex: Prentice-Hall.
  • Kirk, P.E. (1968). Experimental Design. Procedures for the Behavioural Sciences. Brooks/Cole.
  • Myers, J.L. (1972). Fundamentals of Experimental Design. Second Edition. Allyn and Bacon.
  • Myers, J.L, & Well, A.D. (1991) Research Design and Statistical Analysis. HarperCollins: New York.

Indicative learning resources - Web based and electronic resources

  • ELE page: (provides lecture slides, lecture notes, podcast lectures,weekly assignment exercises, online SPSS instructions, screen-capture videos of SPSS procedures and links to further online resources.)

Module has an active ELE page

Indicative learning resources - Other resources

  • Statistics and Computing Helpdesk in the computer room (220/221 WSL) is available for help and advice.

Key words search

Psychology, research methods, research statistics, SPSS, ANOVA, linear regression, multivariate

Credit value15
Module ECTS


Module pre-requisites

PSY1205 Introduction to Statistics and PSY1206 Introduction to Research Methods (or equivalent)

Module co-requisites


NQF level (module)


Available as distance learning?


Origin date


Last revision date