PS923: Methods and Analysis in Behavioural Science (2022/23)
Module Code: |
PS923 |
Module Name: |
Methods & Analysis in Behavioural Science |
Module Credits (CATS): |
15 |
Module Convener |
Pete Trimmer |
Module Teachers |
Pete Trimmer, Mikhail Spektor |
Module Aims The purpose of the module is to introduce experimental design and statistical programming. 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. |
Learning Outcomes |
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By the end of the module, students should be able to:
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Assessed by:
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Module Work Load |
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Module Length |
10 weeks |
Lectures |
10 lectures of 2 hours each |
Practical classes |
10 practical classes of 2 hours each |
Attendance |
Attendance at lectures and practical classes is compulsory |
Module Assessment |
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Assessed work: Modelling Assignment 1 – based on modelling in R Modelling Assignment 2 – based on modelling in R Weekly brief assignments - 8 assignments in weeks 3-10 worth 2% each Group presentation – based on weekly assignments |
Weighting: 36% 36% 16% 12% |
Module Programme |
Topics covered on the course will likely include:
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Module 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. |