Applied Multivariate Analysis MGT5360

  • Academic Session: 2023-24
  • School: Adam Smith Business School
  • Credits: 20
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No

Short Description

This module introduces some common methods for analysing datasets involving several variables per observation and covers topics such as multivariate regression and factor analysis.

Timetable

The course combines seminars and workshops run in Semester 2.

Requirements of Entry

None

Excluded Courses

None

Co-requisites

Quantitative Data Analysis SPS5033

Assessment

The individual assessment will comprise a 3,000-word report focusing on data analysis, diagnostics, interpretation, and conclusions concerning a management research problem. The word count will exclude specification and analysis, the student will have a choice of data to use and data will be provided for those who do not wish to work with their own data, statistical package will also be provided and determined by the lecturer.

Course Aims

Applied Multivariate Analysis provides an advanced introduction to multivariate data analysis in Management. The module starts where the course "Quantitative Data Analysis" ends and develops an applied knowledge and research skills concerning a range of multivariate techniques, including multiple regression and factor analysis. The course aims to explain the specific techniques in multivariate analysis, determine which techniques are appropriate for a specific research problem and discuss the conceptual and statistical issues inherent in multivariate analyses in management research.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

■ Critically evaluate selected multivariate techniques including multiple regression and factor analysis

■ Assess data requirements and code and modify datasets accordingly

■ Critically assess and interpret parameter estimates and quality indicators for each technique

■ Implement multivariate techniques in the context of observational data involving business and management phenomena and apply the methods to relevant management research questions

■ Design, perform and interpret multivariate analyses using statistical packages (e.g. SPSS)

■ Critically evaluate the statistical analyses in current published articles in highly ranked management journals

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.