PS923-15 Methods & Analysis in Behavioural Science
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
Reading lists can be found in Talis
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 | 2 sessions of 2 hours (3%) |
| Online learning (scheduled sessions) | 8 sessions of 2 hours (11%) |
| 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 A8
| Weighting | Study time | Eligible for self-certification | |
|---|---|---|---|
Assessment component |
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| Presentation | 12% | No | |
|
15-30 mins |
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Reassessment component is the same |
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Assessment component |
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| weekly assignments | 16% | Yes (waive) | |
|
8 weekly brief assessments |
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Reassessment component is the same |
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Assessment component |
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| Assignment 1 | 36% | Yes (extension) | |
Reassessment component is the same |
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Assessment component |
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| Assignment 2 | 36% | Yes (extension) | |
Reassessment component is the same |
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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-L981 Postgraduate Social Science Research
-
TIMA-L995 Postgraduate Taught Data Visualisation
- Year 1 of L995 Data Visualisation
- Year 2 of L995 Data Visualisation
- 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