The objective of this module is to introduce the fundamental concepts and processes in doing quantitative and qualitative research. Its particular features are accessibility for all students irrespective of their academic background, focus on applicability of tools and methods, and relevance to all the postgraduate programmes in the Department.
Aims
- To provide the postgraduate students with an understanding of the purpose, nature and conduct of quantitative and qualitative research in the context of issues and topics of relevance to their field of study.
- To ensure that students have sufficient understanding of research methods to enable them to plan, develop and carry out their own research projects as well as being able to appraise the research methods, analyses and outputs of other researchers.
- To introduce research methods that are fundamental to all MPhil students in the department, such as regression techniques and survey design methods.
Keyword Syllabus
Lecture 1: Introduction & Review of Basic Statistics
Population; Sample; Statistical inference; Hypothesis testing; Significance level, Simple Linear Regression; Ordinary least squares (OLS); Intercept; Slope; Parameters; Estimates; t test; R2
Lecture 2: Multiple Linear Regression – Introduction
F test; Adjusted R square; Variable selection; Hypothesis testing in multiple linear regressions.
Lecture 3: Multiple Linear Regression – Assumptions and Diagnostic Tests
OLS assumptions; Heteroskedasticity; Autocorrelation; Stationarity; Spurious regression.
Lecture 4: Multiple Linear Regression – Model Specification
Modelling non-linear relationships by OLS; Functional form; Transformation; Dummy variables; Partial F test; The Chow test; Predictive failure test.
Lecture 5: Multiple Linear Regression – Hedonic Price Modelling
The concept of Hedonic Price Modelling; Omitted variable bias; Misspecification bias, RESET test.
Lecture 6: Qualitative Dependent Variable Models
Qualitative dependent variables; Discriminant score; Estimation sample and validation sample; logistic function; maximum likelihood estimation.
Lecture 7: Qualitative Research Methods – Introduction
Overview of qualitative research methods; Case Studies; Literature Reviews; Meta-analysis; Online Survey; Crowdsourcing.
Lecture 8: Survey Design and Implementation
Sampling methods; Ethics and data collection; Reliability and validity; Response rate; Pilot testing; Questionnaire administration methods; Preparing data for analysis.
Teaching Method
Students will have a two-hour lecture and case discussion combined session per week. Cases taken from real-world situations will be used for analysis. The use of statistical software in these applications will be discussed and demonstrated throughout the lectures. Students are encouraged to bring their own laptops to the class to practice with examples and exercises. Data for class exercises and examples will be available online before each session.
Assessment
The course will be assessed by an individual coursework with a word limit of 4,000.
Readings
Essential:
- Hill, R. C., W. E. Griffiths, and G. C. Lim (2018), Principles of Econometrics, 5th ed. New York: John Wiley. ISBN: 1119510562.
- De Vaus, D. A. (2014). Surveys in Social Research, 6th ed. London: Routledge. ISBN: 9780415530187.
Supplementary:
- Bao H. X. H. (2020), Behavioural Science and Housing Decision Making: A Case Study Approach, London, Routledge, ISBN: 978-0-367-13576-8 (paperback), 978-0-429-02725-3 (ebook) and 978-0-367-13575-1 (hardback).
- Gifford R. (2015), Research Methods for Environmental Psychology. Wiley-Blackwell, ISBN: 978-1118795385.
- Silva E., P. Healey, N. Harris, and P. Van den Broeck (2014), The Routledge Handbook of Planning Research Methods, Taylor and Francis, ISBN: 978-0-415-72795-2.
Software