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Module Catalogue

IB98D-15 Advanced Data Analysis

Department
Warwick Business School
Level
Taught Postgraduate Level
Module leader
Wenjuan Zhang
Credit value
15
Module duration
9 weeks
Assessment
25% coursework, 75% exam
Study location
University of Warwick main campus, Coventry

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Introductory description

The module provides an opportunity to pursue a more advanced area of analytics, focusing on the use of a range of applied multivariate data analysis techniques to convert information into knowledge.

Module web page

Module aims

The module provides an opportunity to pursue a more advanced area of analytics (building on the core module in Business Statistics). Today organisations and businesses collect and store information in data warehouses, and such information is available to be ‘mined' for improved management decision making. Some of that information can be analysed with simple statistics, but much of it requires more complex, multivariate statistical techniques. The module thus focuses on the use of a range of applied multivariate data analysis techniques to convert information into knowledge.

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

  1. Types of Multivariate Data Analysis Techniques
  2. Preparing data for analysis and use of appropriate software (e.g. SPSS)
  3. Multivariate Regression Analysis
  4. Factor Analysis
  5. Discriminant Analysis
  6. Cluster Analysis

Learning outcomes

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

  • Develop a comprehensive understanding of the different categories of multivariate modelling, and how they are inter-related.
  • Demonstrate a sound knowledge of the relevant issues and measures available to aid selection of the most suitable models.

Indicative reading list

Chatfield, C. and Collins, A.J. (1989). Introduction to Multivariate Analysis. Chapman and Hall.
Flury, B. and Riedwyl, H. (1989). Multivariate Statistics: a Practical Approach. Chapman and Hall.
Field, A. (2013) Discovering statistics using IBM SPSS statistics, 4th ed. Los Angeles: Sage.
Hair, J.F. et al (2014) Multivariate analysis, 7th ed. Harlow Pearson Education Limited.
Hair, J.F. et al (2006). Multivariate Data Analysis, 6th ed. Pearson International Edition.
Hooley, G.J. and Hussey, M.K. (1994). Quantitative Methods in Marketing. Academic Press.
Sharma, S. (1996). Applied Multivariate Techniques. Wiley.
Tabachnick, B.G. & Fidell, L.S. (2001). Using Multivariate Statistics, 4th ed. Allyn and Bacon.

Subject specific skills

Apply several multivariate statistical models to real data sets, conducting a range of analyses using appropriate software.
Produce reports investigating real data sets and be able to report on the findings from a piece of modelling and analysis in practical terms.

Transferable skills

Numerical and IT skills.
Problem solving skills .
Group working skills.

Study time

Type Required
Lectures 9 sessions of 3 hours (18%)
Private study 123 hours (82%)
Total 150 hours

Private study description

Self study hours to include preparation for assessment and pre-reading for lectures

Costs

No further costs have been identified for this module.

You do not need to pass all assessment components to pass the module.

Assessment group D2
Weighting Study time Eligible for self-certification
Assessment component
Group Project (2000 words) 25% Yes (extension)
Reassessment component is the same
Assessment component
2 hour examination (April) 75% No
Reassessment component is the same
Feedback on assessment

Feedback via My.WBS

Past exam papers for IB98D

Courses

This module is Optional for:

  • Year 1 of TIBS-N1N3 Postgraduate Taught Business Analytics