Quantitative Research Design and Analysis in Education and Policy Research

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The module provides a practical guide to designing and developing a research project based on quantitative dates. It focuses on key aspects of research design, how to work with theory, identify key concepts and operationalise them with quantitative data. It will explore the use of applied statistical methods for data analysis, their applications in academic research, and how to interpret statistical outputs. Although the illustrative examples are mainly drawn from education and policy research, the statistical and design knowledge and skills acquired via this module are also applicable to other social sciences research topics and areas.

Outline

The module consists of four lectures (two-hours per session) including:

• Lecture 1: Introduction to quantitative research design
• Lecture 2: Key statistical concepts and methods
• Lecture 3: Applied social statistics in education research
• Lecture 4: Education and social policy evaluation

Contents

Lecture 1 will focus on how to design quantitative studies, including formulating research questions, engaging with theoretical and empirical evidence, developing hypothesises, as well as preparing relevant data. Lecture 2 will cover some of the widely used statistical toolkits for data description and hypothesis testing, such as graphs, z-score, conference intervals, parametric and non-parametric tests, correlation and regression analyses. Lecture 3 applies the principles of research design and key statistical methods to examples drawn from education research. It will highlight regression analyses and the interpretation of statistical outputs. Lecture 4 will introduce a few causal inference methods, such as matching, instrumental variables, difference-in-differences, and regression discontinuity design, which are commonly used in social policy evaluations.

• Postgraduate students and staff
• Further details regarding eligibility criteria are available here

Number of sessions: 4

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

• Understand how to design quantitative studies
• Understand key statistical theories and methods widely used in academic research
• Analyse and interpret quantitative research papers and reports
• Understand causal inference methods widely used in policy evaluations

Teaching will take place in person, with each session lasting for 2 hours. No specific lab sessions are planned; however, Stata codes will be provided whenever relevant to facilitate learning and practice.

The module uses Stata software for practical examples. Basic knowledge of Stata is recommended to maximise the learning experience.

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