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APME85 - Quantitative Marketing Research Methods

APME85-Quantitative Marketing Research Methods

Module Provider: School of Agriculture, Policy and Development
Number of credits: 10 [5 ECTS credits]
Level:7
Terms in which taught: Spring term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2019/0

Module Convenor: Dr Giacomo Zanello

Email: g.zanello@reading.ac.uk

Type of module:

Summary module description:

Good marketing decisions require solid marketing research. The main objective of this course is to provide students with the theoretical and applied knowledge of multivariate statistical techniques for data analysis in a market research environment. Students will gain an exposure and understanding to different techniques, and apply quantitative marketing methods that are typically used to analyse data in marketing.


Aims:

Assessable learning outcomes:

At the end of this module students will:




  • Recognize the role and value of statistical techniques in a market research environment.

  • Become familiar with the steps of a research design, including the structure and characteristics of a research report.

  • Gather a knowledge of a selection of statistical techniques and apply them to marketing research problems.

  • Understand the output of marketing research investigations.

  • Master SPSS for statistical analysis within a market research perspective.

  • Develop effective written communication skills for a marketing and professional environment.


Additional outcomes:

Use of SPSS for advanced statistical analysis within a market research perspective. Effective written communication skills for a marketing and professional environment.


Outline content:


  1. Introduction (data and marketing)

  2. Measurement, stats, and graphs

  3. Hypothesis testing

  4. Regression analysis (OLS)

  5. Logit and Principal Component Analysis (PCA)

  6. Cluster analysis

  7. Ordered logit

  8. Segmentation

  9. Discrete choice conjoint analysis

  10. Test (30%)


Brief description of teaching and learning methods:

Lectures will provide an understanding of fundamental concepts and demonstrate the use of data analysis methods. Practical classes will involve students analysing real data sets with a focus on learning the concepts taught in the lectures.


Contact hours:
  Autumn Spring Summer
Lectures 10
Practicals classes and workshops 10
Guided independent study:      
    Wider reading (independent) 10
    Exam revision/preparation 20
    Essay preparation 50
       
Total hours by term 0 100 0
       
Total hours for module 100

Summative Assessment Methods:
Method Percentage
Report 70
Class test administered by School 30

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:


  1. Students will submit a Marketing Report based on analysis of a real dataset. The report must not be longer than 3,500 words (excluding tables, bibliography, and appendix). The assignment will be held in Week 6 and it is due the first day of Summer Term (April 16, 2017). The Report must be submitted via Turnitin (see link under ‘Assignment’ in Blackboard). This part of the assessment carries a weight of 70%.

  2. Students also sit an examination paper consisting of 30 multiple choice questions lasting 60 minutes which covers most of the key material presented in the module. The test will be held in Week 11. This part of the assessment carries a weight of 30%.


Formative assessment methods:

Penalties for late submission:
Penalties for late submission on this module are in accordance with the University policy. Please refer to page 5 of the Postgraduate Guide to Assessment for further information: http://www.reading.ac.uk/internal/exams/student/exa-guidePG.aspx

Assessment requirements for a pass:

50%


Reassessment arrangements:

Coursework assignment to be carried out in August.


Additional Costs (specified where applicable):

Last updated: 8 May 2019

THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.

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