2020/21 Undergraduate Module Catalogue
LUBS3200 Business Analytics 3: Analytics Project
40 creditsClass Size: 40
Module manager: Sajid Siraj
Email: S.Siraj@leeds.ac.uk
Taught: Semesters 1 & 2 (Sep to Jun) View Timetable
Year running 2020/21
Pre-requisites
| LUBS2920 | Advanced Analytical Methods |
| LUBS2931 | Evidence-based Consultancy |
| LUBS2940 | Business Analytics 2 |
This module is mutually exclusive with
| LUBS3300 | Economics Dissertation |
| LUBS3345 | Dissertation/Project in Management |
This module is not approved as a discovery module
Module summary
This module will allow you to undertake an independent analytics project, giving you the opportunity to apply and showcase your skills as an analyst to formulate a business problem, design and execute the data analysis, evaluate the results, write-up a project report, and reflect on your professional and personal development.Objectives
This module provides students with the opportunity to apply and showcase their skills as an analyst to formulate, design, execute, evaluate and write-up an independent analytics project.Learning outcomes
Learning Outcomes – Knowledge/Application
Upon completion of this module students will be able to:
- Interpret and explain the critical factors and associated causal mechanisms involved in the observed behaviour that is the object of enquiry (Knowledge)
- Accurately apply advanced statistical and other related analytical techniques to investigate the observed behaviour of interest (Application)
Learning Outcomes – Skills
Upon completion of this module students will be able to:
Transferable
1. Apply analytical skills – mathematical/numerical/statistical
2. Solve problems creatively
3. Think critically – reviewing evidence; interpreting results
4. Carry out analytical research
5. Communicate effectively in writing
6. Work independently
7. Manage their time effectively
8. Reflect constructively on their professional and personal development
9. Awareness of ethical issues involved in the use of confidential personal and organisational data
Subject specific
1. Formulate an unstructured business problem into a form that is amenable to data analysis
2. Design and schedule an independent analytics project to address the formulated business problem
3. Apply appropriate statistical and other quantitative methods to analyse the formulated business problem
4. Critically evaluate and interpret the real-world implications of the results of the data analysis in order to support decision makers
Skills outcomes
1. Formulate an unstructured business problem into a form that is amenable to data analysis
2. Design and schedule an independent analytics project to address the formulated business problem
3. Apply appropriate statistical and other quantitative methods to analyse the formulated business problem
4. Critically evaluate and interpret the real-world implications of the results of the data analysis in order to support decision makers
Syllabus
The module will commence with three workshops in the early weeks of Semester 1 in which students will receive guidance on the various stages involved in their analytics project: problem formulation; project design; data collection; data analysis; interpretation of results; report write-up; reflection. Students will be asked to submit their project topic by the end of Week 5 in Semester 1 after which they will be allocated a supervisor. Students will have three scheduled meetings with their supervisor. The first meeting will consider the project topic and the planned work schedule. The second meeting will discuss the initial results of the data analysis. The third meeting will focus on the reflective component of the project report.
Teaching methods
| Delivery type | Number | Length hours | Student hours |
| Workshop | 3 | 2.00 | 6.00 |
| Seminar | 3 | 1.00 | 3.00 |
| Private study hours | 391.00 | ||
| Total Contact hours | 9.00 | ||
| Total hours (100hr per 10 credits) | 400.00 | ||
Private study
This could include a variety of activities, such as reading, watching videos, question practice and exam preparation.391 hours of private study to conduct and write-up the analytics project
Opportunities for Formative Feedback
Your teaching methods could include a variety of delivery models, such as face-to-face teaching, live webinars, discussion boards and other interactive activities. There will be opportunities for formative feedback throughout the module.Methods of assessment
Coursework
| Assessment type | Notes | % of formal assessment |
| Project | 10,000 words max | 100.00 |
| Total percentage (Assessment Coursework) | 100.00 | |
The analytics project report will include two components: (i) a report on the results of the data analysis and their implications (weighted 80%); and (ii) a reflection of the experience of undertaking an extended analytics project to include discussion of, for example, problems of obtaining access to data, the practicality of alternative analytical methods, ethical issues, and personal motivation, discipline and time management (weighted 20%). If students have undertaken a placement as an analyst, they may base their analytics project on analytical work undertaken during their placement subject to the agreement of the host organisation and with full compliance of any confidentiality protocols. If failed, the project report can be revised and resubmitted by the August examination period. The resit for this module will be 100% by coursework- resubmission of improved project.
Reading list
There is no reading list for this moduleLast updated: 29/09/2020 10:19:57
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