This module aims to:

Equip students with technical knowledge and practical skills required for conducting quantitative research in business and management;

Enable students to become independent, quantitative researchers
Develop awareness of open science through the practice of transparency and research integrity.

(LO1) Students will be able to write the methods section of a research paper.

(LO2) Students will be able to justify their choice of methods for the proposed research question.

(LO3)  Students will be able to formulate theory-based hypothetical arguments and subsequently propose a suitable empirical design to test the hypotheses.

(LO4) Students will be able to collect and systematically organise relevant data and information for the empirical analysis.

(LO5) Students will be able to perform simple statistical analysis using statistical software (e.g. STATA or R).

(LO6) Students will be able to correctly interpret the output from statistical software and subsequently derive conclusions for the proposed research question.

(LO7) Students will be able to critically evaluate their own research by identifying the limitations of their empirical approaches and proposing suggestions for future research.

(S1) Leadership and teamwork
Students develop this skill by leading their own research work. The lectures and seminars will guide students on how to define a research question suitable for quantitative investigation, how to design the empirical analysis, how to present the empirical results, and how to derive conclusions based on the empirical results. Some in class work for students will require them to work in groups and manage the interaction and relationships with other group members. In doing so, they will gain experience in negotiation, persuasion, influencing and managing conflict.

(S2) Numeracy
Students develop this skill by systematically organised data and information and analyse them using statistical software (STATA or R).

(S3) Organised and able to work under pressure
Students develop these skills by balancing the time and resources to study and to write the research paper.

(S4) Digital Skills
Students develop this skill by accessing databases from secondary data providers during the seminars and by conducting statistical analysis using statistical software (STATA or R).

(S5) Ethical awareness
Students develop these skills by transparently presenting how they collect data, how they code using statistical software, and how they equally report significant and not significant results.

(S6) International awareness
International issues will be covered in related group and individual activities.

(S7) Lifelong learning skills (critical thinking, problem solving and decision-making)
Students will be challenged to think critically about organisational issues and dilemmas. They will do this by gathering and synthesising information, analysing alternative perspectives and options and presenting a considered opinion or course of action in their course assessment.

(S8) Communication skills
Students will have opportunities to develop written and oral communication skills through group discussions, in-class presentations and coursework. Written communication skills will be assessed by the assignments.

12 hours lectures (6 x 2 hours)
12 hours seminars (6 x 2 hours)
176 hours self-directed learning

Topic 1: Fundamentals of quantitative research
Types of research questions suitable for quantitative research
Hypothesis testing
Internal and external validity
Research integrity (transparency & replicability)

Topic 2: Endogeneity in quantitative research
What is endogeneity
Sources of endogeneity (omitted variable bias, reverse causality, sample selection, endogenous regressor)
Addressing endogeneity (instrumental variable, Heckman selection)

Topic 3: Data for quantitative research
Types of datasets (cross-section vs panel data)
Collecting data from secondary sources
Measuring validity

Topic 4: Methods for quantitative research
Multivariate statistics tools (principal component analysis, factor analysis, cluster analysis)
Econometrics

Topic 5: Writing empirical analysis in quantitative research
Structuring the methods section
Interpreting results (statistical inference)
Robustness checks/sensi tivity analysis