MMD017: Introduction to Quantitative Research Design and Techniques

Module code: MMD017

Module provider: Henley Business School

Credits: 20

Level: NA

When you’ll be taught: Semester 2

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: NA

Academic year: 2026/7

Available to visiting students: No

Talis reading list: Yes

Last updated: 9 June 2026

Overview

Module aims and purpose

This module is designed to develop students’ understanding of key principles in quantitative research design, quantitative research methods, and quantitative data analysis. It introduces students to quantitative reseach questions and hypothesis testing, basic descriptive and inferential statistics, exploratory data analysis, and multivariate analysis. Students will be encouraged to engage with readings covering a range of quantitative research methodologies and the module aims to build confidence in understanding and interpreting statistical language. The module also provides an introduction to software used for quantitative data analysis and aims to develop practical skills in using these tools effectively.

Module learning outcomes

By the end of the module, it is expected that students will be able to: 

1. Convert broad research questions into specific statistical hypotheses. 
2. Demonstrate competence in designing a quantitative research approach.
3. Select with justification appropriate methods to analyse a given problem. 
4. Use methods in an appropriate way with an understanding of the assumptions of a particular method 
5. Evaluate and interpret results, recognising any limitations and report findings in a clear, concise and well-structure manner
6. Demonstrate competence in the use of introductory software for quantitative data analysis

Module content

The module covers a broad introduction to quantitative research designs and quantitative data analysis. It begins with key statistical concepts, including descriptive and inferential statistics, the examination of empirical data, handling missing data, identifying outliers, and assessing assumptions such as normality. Students will explore a range of research designs and measurement approaches, along with practical considerations in questionnaire construction and data collection, including sampling strategies commonly used in quantitative research.
The module also provides an introduction to several multivariate statistical techniques, such as factor analysis, multiple regression analysis, cluster analysis, t-tests, and analysis of variance (ANOVA). In addition, students will be introduced to different approaches to structural equation modelling, gaining insight into how complex relationships among variables can be analysed and interpreted.

Structure

Teaching and learning methods

The teaching and learning methods in this module will include a combination of lectures, seminars, practical workshops, small-group activities, and individual exercises. No prior knowledge or experience in data analysis is required; however, students are expected to engage in substantial independent reading and come to each class prepared to participate.
A quantitative dataset will be provided as a case study for each student. Using this dataset, students will apply fundamental descriptive and inferential statistical techniques to explore the data and test statistical hypotheses. This hands-on approach is designed to help students develop confidence in conducting quantitative analyses and interpreting statistical findings.
The pedagogical approach used for this module is based on active learning and there is an expectation that students take ownership of their learning, hence there is a strong expectation that students come prepared and engage with the hands-on activities during and after class. 

Study hours

At least 30 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.

Small homework exercises will be made available to students at the end of classes so that students can practice the course material. Students are encourage to engage with the task and a review session will be held at the beginning of the next class, at which verbal feedback will be provided to those who did the task. 

Reassessment

Additional costs