MDD2QTA2: Introduction to Quantitative Techniques

Module code: MDD2QTA2

Module provider: Marketing and Reputation; Henley Business School

Credits: 15

Level: Doctoral level

When you'll be taught: Summer (vacation) semester

Module convenor: Professor Carola Hillenbrand, email: carola.hillenbrand@henley.ac.uk

Pre-requisite module(s):

Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: No placement specified

Academic year: 2024/5

Available to visiting students:

Talis reading list:

Last updated: 28 May 2024

Overview

Module aims and purpose

This module seeks to develop understanding of some key methods and techniques in quantitative data analysis and to introduce software for quantitative data analysis. 

The key objectives  

The module aims to enable programme members to:  

• Develop their understanding of some of the main methods and techniques of quantitative data analysis 

• Develop competence in interpreting findings 

• Develop practical skills in using software for quantitative data analysis 

Module learning outcomes

This module is assessed by a quantitative methods assignment: 

By the end of the module it is expected that programme members will be able to demonstrate their ability to: 

1. Select with justification appropriate methods to analyse given data  

2. Use methods in an appropriate way with an understanding of the assumptions of a particular method 

3. Evaluate and interpret results, recognising any limitations 

4. Report findings in a clear, concise and well-structure manner  

5. Demonstrate competence in the use of appropriate software for quantitative data analysis 

Module content

The module teaching is structured around one 6-day workshop covering methods for data collection and analysis in broad terms structured around example data sets. 

More specifically, the module content includes introduction to quantitative data analysis, basic statistical concepts, exploration of research design and measurement, issues of questionnaire design and data collection and introduction to a number of multivariate statistical techniques such as multiple regression and factor analyses.  

Structure

Teaching and learning methods

Teaching will involve a combination of lectures, group seminars, practical experiential learning and individual activities in the form of guided self-study. Pre-workshop briefings will give guidance as to the preparatory readings and exercises required to get the best from the teaching.  

The contact hours are shown by semester in the table below for illustrative purposes only. The actual timing will vary depending on your cohort start date.

Study hours

At least 32 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 50% to pass this module.

Summative assessment

Penalties for late submission of summative assessment

This module is subject to the Penalties for late submission for Postgraduate Flexible programmes policy, which can be found at:

https://www.reading.ac.uk/cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmissionpgflexible.pdf

The Module Convenor will apply the following penalties to work submitted late:

• where the piece of work is submitted up to one calendar month 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; 
• where the piece of work is submitted more than one calendar month 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.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

Reassessment

Additional costs