Module overview
Linked modules
Pre-requisites: MANG1047 or MANG1019
Aims and Objectives
Learning Outcomes
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- interpret results of different types of predictive models and explain the value of the results in different business contexts.
- apply a range of regression modelling and forecasting techniques using real world problems;
- use predictive analytic techniques to handle a variety of business problems;
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- criteria for choosing the appropriate predictive techniques for particular problems.
- a range of statistical techniques for modelling and predicting future trends;
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- predict the future trends in data.
- apply predictive modelling concepts in real world situations;
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- plan and control effectively for successful completion of a personal workload;
- use your analytic skills in problem solving.
- self-manage the development of learning and study skills;
Syllabus
Learning and Teaching
Teaching and learning methods
Type | Hours |
---|---|
Completion of assessment task | 60 |
Revision | 12 |
Tutorial | 20 |
Wider reading or practice | 30 |
Preparation for scheduled sessions | 12 |
Lecture | 16 |
Total study time | 150 |
Resources & Reading list
Textbooks
Kuhn M. and Johnson K (2018). Applied Predictive Modelling. Springer.
Albright S. and Winston W.L. (2017). Business Analytics: Data Analysis & Decision Making (6th Ed). Cengage.
Evans, J. R. (2013). Business Analytics. Methods, Models and Decisions. Pearson Education.
Hastie T., Tibshirani R. and Friedman J (2008). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer Series in Statistics.
Urdan, T.C. (2010). Statistics in Plain English (3rd Edition). Taylor & Francis Group.
Assessment
Formative
This is how we’ll give you feedback as you are learning. It is not a formal test or exam.
Class participation
- Assessment Type: Formative
- Feedback: •Verbal formative feedback will be given by the lecturer/tutor throughout the module during lectorials and during one-to-one sessions during office hours. •Written feedback will also be provided by the lecturer/tutor through email communications. •Peer-to-peer feedback will also be key for developing and supporting learning objectives. •Students’ knowledge will be used formative tests.
- Final Assessment: No
- Group Work: No
Summative
This is how we’ll formally assess what you have learned in this module.
Method | Percentage contribution |
---|---|
Assignment | 30% |
Examination | 70% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
Method | Percentage contribution |
---|---|
Examination | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
Method | Percentage contribution |
---|---|
Examination | 100% |
Repeat Information
Repeat type: Internal & External