Quantitative Research Methods (QUAN) 2011/2
Workload - Private Study - Assessment - Description - Learning Outcomes - Content - Teaching Materials - Recommended Books
| Module Code | COM00044M |
|---|---|
| Lecturers | Paul Cairns |
| Taken By | HCIT, LSCITS 1, LSCITS 2, LSCITS 3, LSCITS 4, NC |
| Number of Credits | 10 |
| Part | B |
| Teaching | Spring 2-5 |
| Open Assessment |
[100%] Spr/5/Wed -> Spr/10/Wed Feedback: Sum/1/Wed |
Workload
- Lectures: 8 x 2hrs
- Practicals: 4 x 2hrs
- Private Study: 26 x 1hr
- Assessment: 50 x 1hr
The lectures and practicals will structure the material for students but they will be expected to spend substantial amounts of time outside of formal contact reading around the topics and doing lecture and practical examples.
Private Study
Reading around this subject is essential in order that students have a full and rounded understanding of the topics.
Assessment
Open Assessment
- Spr/5/Wed -> Spr/10/Wed
Feedback: Sum/1/Wed
The assessment will require students to design, conduct and report an experiment.
Formative Feedback
During practicals in which students will have to design or critique experiments and use statistical software to analyse data. The results of their work will be presented to their peers and staff for formative feedback.
Description
This module aims to provide an introduction to experimental design and statistics as used in HCI and computer science for the evaluation of interactive systems, for experimental evaluation of algorithms and for research into HCI and computer science. It will cover research designs such as experimental and quasi-experimental techniques. It will introduce and compare hypothesis testing designs and problem seeking designs. It will also cover introductory descriptive and inferential statistics, emphasising clear presentation of descriptive statistics and basic inferential statistics such as t-tests and chi-squared tests
Learning Outcomes
By the end of this module, the student will be able to:
• Recognise and justify different research designs to be used at different stages of the design and evaluation lifecycle of interactive technologies or stochastic algorithms
• Design a simple empirical user requirements or evaluation investigation using the methods covered in the course
• Clearly present the quantitative data gathered in an empirical investigation so that they will be understood by clients
• Perform and interpret basic inferential statistics
Content
The module will cover topics such as:
• The scientific method and hypothesis testing
• Experimental and quasi-experimental designs
• Causal inference, artifacts in experimental designs
• Ethical considerations.
• Data types and distributions
• Data summarization and presentation
• Statistical argument and evidence
• Some typical statistical tests, such as Mann-Whitney and chi-squared
• Correlations and analysis of questionnaire data
Teaching Materials
Teaching materials will be made available online. These will include lecture slides and any accompanying class materials such as handouts and exercise sheets. Practical sheets and special papers will be posted online as well. Students will be expected to read around using suggested readings in the lectures. All of these readings should be available through the University Library but where not, these will also be made available online.
Recommended Books
| Rating | Author | Title | Publisher | Year |
|---|---|---|---|---|
| **** | Howell, D. | Fundamental statistics for the behavioural sciences, 6th edn | Wadsworth | 2007 |
| **** | Harris, P. | Designing and Reporting Experiments in Psychology, 3rd edn | OUP | 2008 |
| *** | Cairns, P., Cox, A. (eds) | Research Methods in Human Computer Interaction | Cambridge University Press | 2008 |
Last updated: 20th April 2012