AP2EQ5-Research Methods and Data Analysis
Module Provider: School of Agriculture, Policy and Development
Number of credits: 20 [10 ECTS credits]
Level:5
Terms in which taught: Autumn term module
Pre-requisites: AP1EQ5 Research and Professional Skills for Business and Marketing
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2023/4
Module Convenor: Prof Kelvin Balcombe
Email: k.g.balcombe@reading.ac.uk
Module Co-convenor: Dr Daniele Asioli
Email: d.asioli@reading.ac.uk
Type of module:
Summary module description:
Gain fundamental understanding of research processes, with special emphasis on conclusive research design, techniques for primary data collection and multivariate and statistical tools for data analysis. Explore the applications of these tools in a consumer and market research environment. Develop the statistical ideas that you will need in your career. Through hands-on tutorial sessions, master the software to deal with data such as Qualtrics, Excel and JASP applied to case studies. Go beyond data summary and understand how to employ statistical methods in a context of your chosen subject.
Aims:
To introduce students to research processes, with special emphasis on conclusive research design, techniques for primary data collection and tools for exploratory data analysis. The module includes the use of statistical software for selected statistical techniques and their applications in a consumer and market research environment. To build a further understanding of some of the key quantitative skills used by applied economists and business managers working in key marketing sectors.
Assessable learning outcomes:
- LO1 Be able to recognise, describe and solve marketing problems
- LO2 To develop specific research designs to enable understanding of how to achieve marketing and consumer research objectives
- LO3 Be able to test research hypotheses using a logical sequence of research tasks
- LO4 Identify research tasks to enable collection of information for a specific research design
- LO5 Learn to choose a suitable measurement and scaling technique, the most appropriate data collection and sampling method, and the right multivariate statistical analysis
- LO6 Interpret results from a marketing and consumer angle
- LO7 Perform and use an extended set of multivariate statistical methods and techniques to solve a range of problems relating to business and economics applications
- LO8 Gain an understanding of the most important quantitative methods to provide a foundation for learning more sophisticated methods
Additional outcomes:
- LO9 Identify and use appropriate statistical methods to solve a range of problems relating to business and economics applications
- LO10 Be proficient in the use of Excel in order to present and analyse business and economics data
- LO11 Develop familiarity with the use of statistics and data processing software - particularly JASP- within the marketing and consumer context
- LO12 Be able to exploit the research techniques for use in project work later in their degree program
- LO13 Develop effective written communication skills for a marketing and professional environment
Outline content:
- Marketing research and marketing research process
- Research design
- Contingency tables
- Non-Parametric Tests
- Correlation
- Regression
- Analysis of Variance
- Logit/Probit Models
- Measurement and scaling. Comparative and non-comparative scaling
- Sampling design
- Questionnaire design
- Primary data collection methods
- Principal Component Analysis
- Cluster Analysis
Brief description of teaching and learning methods:
Theory and methods will be presented by means of lectures that will also involve interactively using practical exercises of a quantitative nature using spreadsheets and statistical software. Introduction to data collection software (Qualtrics), statistical software and data presentation software (Excel, JASP). Help is available from lecturers and teaching assistant(s). Students will need to bring laptops to the lectures with the appropriate software.
Autumn | Spring | Summer | |
Lectures | 40 | ||
Guided independent study: | |||
Wider reading (directed) | 40 | ||
Exam revision/preparation | 30 | ||
Advance preparation for classes | 20 | ||
Preparation of practical report | 10 | ||
Revision and preparation | 40 | ||
Essay preparation | 20 | ||
Total hours by term | 200 | 0 | 0 |
Total hours for module | 200 |
Method | Percentage |
Written exam | 40 |
Set exercise | 30 |
Class test administered by School | 30 |
Summative assessment- Examinations:
1 hour and a half examination paper worth 40%
Summative assessment- Coursework and in-class tests:
1 data analysis assignment (30%);
1 one-hour In-class tests in the Autumn Term ( 30%)
Formative assessment methods:
Penalties for late submission:
The Support Centres will apply the following penalties for work submitted late:
- where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of five working days;
- where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.
Assessment requirements for a pass:
A mark of 40% overall.
Reassessment arrangements:
By examination in August/September only.
Additional Costs (specified where applicable):
1) Required text books:
2) Specialist equipment or materials:
3) Specialist clothing, footwear or headgear:
4) Printing and binding:
5) Computers and devices with a particular specification:
6) Travel, accommodation and subsistence:
Last updated: 18 September 2023
THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.