PS923-15 Methods & Analysis in Behavioural Science

Department: Psychology
Level: Taught Postgraduate Level
Module leader: Peter Trimmer
Credit value: 15
Module duration: 10 weeks
Assessment: 100% coursework
Study location: University of Warwick main campus, Coventry

Introductory description

The purpose of the module is to introduce experimental design and statistical programming.

Module aims

Behavioural scientists need statistical analysis of experimental data and of large data sets. This module covers these topics to allow students to understand how to test hypotheses, plan experimental design and perform statistical analysis using R.

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

Introduction to research methods, statistics, and R
Modern R: tidyverse et al.
Data visualization with ggplot2
Simple Linear regression
Multiple Linear regression
One categorical Covariate
Interactions of categorical predictors
More theory
Repeated-measures and pooling

Learning outcomes

By the end of the module, students should be able to:

2. Be able to design and report studies in a manner that permits replication attempts.
1. Understand hypothesis testing and the relationship between hypotheses and experimental planning and design.
3. Be able to program reproducible statistical analyses.

Indicative reading list

Baguley, T. (2012). Serious stats: a guide to advanced statistics for the behavioral sciences. Houndmills,
Basingstoke, Hampshire; New York: Palgrave Macmillan.
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2002). Applied Multiple Regression/Correlation Analysis for
the Behavioral Sciences. New York: Routledge Academic.
Fox, J. (2015). Applied regression analysis and generalized linear models. Los Angeles: Sage.
Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. London: Sage.
Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel/hierarchical models. Cambridge;
New York: Cambridge University Press.
Grolemund, G. (2014). Hands-on programming with R. Sebastopol, CA: O’Reilly.
Howell, D. C. (2010). Statistical methods for psychology (7th ed.). Belmont, CA: Wadsworth.
Howell, D. C. (2013). Fundamental Statistics for the Behavioral Sciences, 8th Edition. Belmont, CA: Wadsworth Cengage Learning. Wickham, H., & Grolemund, G. (2017). R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. Sebastopol CA: O’Reilly.

Subject specific skills

R statistical programming language
Understanding of hypothesis testing
Understanding of the relationship between hypotheses and experimental planning and design.

Transferable skills

Statistical analysis
demonstrate techniques for displaying data
evaluate the appropriateness of different approaches

Study time

Type	Required
Lectures	20 sessions of 1 hour (13%)
Practical classes	10 sessions of 2 hours (13%)
Private study	110 hours (73%)
Total	150 hours

Private study description

110 hours private guided study, including completion of assessments

Costs

No further costs have been identified for this module.

You do not need to pass all assessment components to pass the module.

Assessment group A5

	Weighting	Eligible for self-certification
Presentation	12%	No
15-30 mins
weekly assignments	16%	No
8 weekly brief assessments
Assignment 1	36%	Yes (extension)
Assignment 2	36%	Yes (extension)

Feedback on assessment

For the class test and written assignments, students will receive individual feedback on their
solution plus model answers.
For the group presentations, students will receive written feedback at the end of the term.
For the weekly brief assignments, model answers will be provided.

Courses

This module is Core for:

Year 1 of TPSS-C803 Postgraduate Taught Behavioural and Data Science
TPSS-C8P7 Postgraduate Taught Behavioural and Economic Science (Science Track)
- Year 1 of C8P7 Behavioural and Economic Science (Science Track)
- Year 1 of C8P7 Behavioural and Economic Science (Science Track)
Year 1 of TECS-C8P8 Postgraduate Taught Behavioural and Economics Science (Economics Track)

This module is Core optional for:

Year 1 of TPSS-C8P9 Postgraduate Taught Psychological Research

This module is Optional for:

Year 2 of TIMS-L990 Postgraduate Big Data and Digital Futures
Year 1 of TIMA-L99D Postgraduate Taught Urban Analytics and Visualisation

This module is Core option list A for:

Year 1 of TPSS-C8P9 Postgraduate Taught Psychological Research

This module is Option list A for:

Year 1 of TIMS-L990 Postgraduate Big Data and Digital Futures