MDD2QTA2: Introduction to Quantitative Techniques

Module code: MDD2QTA2

Module provider: Leadership, Organisations, Behaviour and Reputation; Henley Business School

Credits: 15

Level: NA

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

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

Pre-requisite module(s): BEFORE TAKING THIS MODULE YOU MUST TAKE MDD2IAR2 AND TAKE MDD2PDM1 AND TAKE MDD2RDM2 (Compulsory)

Co-requisite module(s): IN THE SAME YEAR AS TAKING THIS MODULE YOU MUST TAKE MDD2QLA2 AND TAKE MDD2RCI1 (Compulsory)

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

Module(s) excluded:

Placement information: Mini placement

Academic year: 2025/6

Available to visiting students: Yes

Talis reading list: Yes

Last updated: 8 September 2025

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

The following penalties for work submitted late will normally apply:  

Assessments with numerical marks 

• where the piece of work is submitted up to 30 calendar days 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 30 calendar days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.  

Assessments marked Pass/Fail  

• where the piece of work is submitted within 30 calendar days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;  
• where the piece of work is submitted more than 30 calendar days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.  

Groupwork  

Where the work submitted late is a piece of groupwork submitted on behalf of the whole group, the penalty will apply to all members of the group. Individual contributions to groupwork submitted separately by each member will be subject to a late penalty only for the individual contributions that are late 

The University policy statement on penalties for late submission for Postgraduate Flexible programmes can be found at:  

https://www.reading.ac.uk/cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmissionpgflexible.pdf?la=en&hash=8A89870FCA07250F482BFA8CD308588F

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