MG527
Advanced Quantitative Analysis for Research in Management
This information is for the 2024/25 session.
Teacher responsible
Dr Elizabeth Stillwell MAR.5.23
Availability
This course is available on the MRes/PhD in Management (Employment Relations and Human Resources) and MRes/PhD in Management (Organisational Behaviour). This course is available with permission as an outside option to students on other programmes where regulations permit.
Students on other MRes programmes in the Department of Management may also attend specific seminars depending on their area of research.
Research students on other MRes/PhD programmes from other departments that would benefit from this training may be allowed to attend at the discretion of the course leader.
Pre-requisites
Students must have completed Introduction to Quantitative Analysis (MY551A) or Introduction to Quantitative Analysis (MY551W).
Students must have completed the first year of the MRes/PhD in Management (ERHR/OB) to take this course.
Course content
This course is designed to complement the required quantitative methodology coursework, including MY551 (Introduction to Quantitative Analysis) and MY555 (Multivariate Analysis and Measurement), with a focus on conceptualising, evaluating, and applying multivariate methods used in management and organisational sciences. It is also designed to enable students to develop skills in using software for data analysis, likely R or Mplus.
The course is intended for students with introductory experience with univariate and bivariate data analysis and an appreciation of multiple linear regression. Course content will focus on examples of research using: (1) scale construction, reliability and validity, (2) exploratory and confirmatory factor analysis, (3) causal inference and experimental design, (4) multivariate regression, (5) meta-analysis, (6) latent variable models (including factor analysis, structural equation models, latent growth models), (7) moderation, mediation, and moderated mediation, (8) multilevel modelling, and (9) longitudinal data analysis. Students will also discuss the best practices in reviewing and providing feedback on quantitative methods for academic publications.
The primary goal of the course will be to enable students to translate and apply their understanding of general principles of data analysis and research methods to common management problems and research questions, and organisational contexts. Students will develop understanding and build skills throughout the course. It will focus on the contemporary debates and challenges of quantitative methodology in organisational research. Students will read, discuss, and evaluate current management journal articles from a range of specialisms using different methodologies, practice reviewing others' work and delivering thoughtful feedback, and identify areas where their own work may be improved throughout the course.
It is anticipated that students within the seminar will be at different stages in their research and data gathering. It is envisaged that the early seminars students will work on a common dataset, and as the teaching progresses students would be given the option to use their own data set or remain practicing on the common dataset. Each seminar will also offer an advanced element/option for students with more experience or further along in their research.
Teaching
30 hours of seminars in the AT.
Each seminar will be a 2+1 hour seminar format with input from a variety of Department of Management Faculty. The first two hours will focus on theory, current research examples and discussion and the final hour will be focused on practical work and experimentation with data set using the R/ software.
In its Ethics Code, ÐÓ°ÉÂÛ̳ upholds a commitment to intellectual freedom. This means we will protect the freedom of expression of our students and staff and the right to engage in healthy debate in the classroom.
Formative coursework
Students will be expected to produce 1 piece of coursework in the AT.
Students will be expected to write a 2000 word report on the Application of Quantitative Methods to Real-world Problems.
Assessment
There is no summative assessment for this course.
Key facts
Department: Management
Total students 2023/24: Unavailable
Average class size 2023/24: Unavailable
Value: Non-credit bearing
Course selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.
Personal development skills
- Self-management
- Problem solving
- Application of information skills
- Communication
- Application of numeracy skills
- Specialist skills