MQM2IL06: Data Analysis

Module code: MQM2IL06

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

Credits: 0

Level: 6

When you'll be taught: Full year

Module convenor: Dr Sinem Bulkan, email: s.bulkan@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: 19 November 2024

Overview

Module aims and purpose

This module forms part of the Henley Executive Diploma in Managing Business Transformation (Improvement Leader Apprenticeship), and as such, sets out to provide the knowledge, skills and behaviours required by Improvement Leaders/Change Managers/Business Transformation managers in today’s world, in relation to Data Analysis. The module is designed to meet the learning outcomes of the Improvement Leader Apprenticeship Standard.

The module covers key data analysis and statistical methods, statistical and graphical analysis, and statistical process control to build the organisation’s knowledge and skills and make recommendations for improvement that extend the capabilities of the organisation. It aims to develop the learner’s skills in the use of systematic decision-making tools (statistical process control) through the implementation of statistical-based techniques to monitor and control a process to advance the quality or uniformity of the output of a process. 

The module focusses on developing the skills of the learner in data analysis especially in terms of assessing the organisation’s approach to these data analyses, guiding others on the completion of these analyses, and making recommendations to drive sustained improvement strategy. Additionally, the module covers the use of Minitab for graphical and statistical analysis. 

Key behavioural skills – professionalism, and strategic thinking – are strongly outlined throughout the module. The learner therefore gains knowledge and understanding of how to plan and implement data and statistical analysis at unit/business/corporate level focusing not just on techniques and tools, but also on sustainable behavioural outcomes.

Module learning outcomes

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

1. Develop knowledge and understanding of graphical and statistical analyses, investigating, and evaluating the measurement and analysis approaches.

2. Develop knowledge and understanding of the implementation of multiple regression or binary regression analysis and guiding others on the completion of the regression analysis.

3. Develop knowledge and understanding of data acquisition and data-driven decision making. 

4. Develop the skills to accurately assess and provide constructive feedback on graphical and statistical analysis conducted by others and make recommendations.

5. Develop the skills to make recommendations on how an organisation can drive sustained improvement through the application of statistical process control.

6. Develop knowledge and understanding of the use of Minitab for graphical and statistical analysis.

Module content

The module covers the following topics:

• Regression Analysis (Multiple & Binary Logistic)

• Forecasting and Queueing Theory

• Principles and Benefits of Statistical Modelling

• Data Acquisition for Analysis

• Data-driven decision-making

• Statistical and Graphical Analysis

• Statistical Process Control (Objectives, Selection of variables, Rational Subgrouping, Control Chart Selection, Control Chart Analysis)

• Use of Minitab or Equivalent tool (Graphs and Quality Tools and the Stat Menu in Minitab)

• Virtual Tools

-The topics are specifically linked to the behavioural skills (Professionalism, strategic thinking).

-The content should be mapped against the OFSTED requirements (British values / Safeguarding / Prevent / Maths / English).

-The content should acknowledge limitations and challenges to the approaches discussed within the module content.

Structure

Teaching and learning methods

Teaching and learning takes place through a blended learning approach. The teaching and learning methods comprise a combination of self-study via a range of online materials on the Canvas learning platform, face-to-face workshops with Academic Faculty and Learning Coaches, and interaction with a Learning Coach (face-to-face and online) who supports the cohort throughout the module. Each person participates in a facilitated Action Learning sets either individually or in teams in week 4 of the module.
Materials on Canvas include content on-screen, videos, PowerPoint presentations, journal articles, book chapters, practical activities, e-portfolio, and reflection points.

Teaching and learning activities will be delivered online.

Study hours

At least 0 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

The work-based projects are not marked. Evaluation of the work-based project leads to a decision of ‘Proceed’ or ‘Revise’.  To gain a ‘Proceed’ the learner must satisfactorily meet the assignment brief requirements.
Any learning outcomes not achieved will be highlighted for the learner, so that it is clear that these learning outcomes should be addressed prior to reaching Gateway for the End Point Assessment (EPA). 
Learners may revise their project as many times as necessary, as they progress through the programme. However, only one resubmission will be evaluated, and feedback provided by the Learning Coach (see reassessment arrangements, below).

Summative assessment

Penalties for late submission of summative assessment

There is no penalty for late submission. However, if learners are at risk of missing the deadline, they are asked to submit an ECF (Exceptional Circumstances Form) requesting a 14-day extension.

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.

One 1500-word Work-Based Project, for which formative feedback will be provided.

Reassessment

Additional costs