IB98E-15 Forecasting
Introductory description
Decision making is an important part of business and, indeed, of life in general. Every day we make choices using a combination of opinions, facts, and 'hard evidence' in order to try and achieve better outcomes. In an uncertain environment, the success of an organisation or a policy depends upon the ability of decision makers and managers to prepare for the future.
This module will give you a thorough introduction to the field of time series analysis and will equip you with a tool bag of quantitative techniques that you can use to make forecasts. You will learn enough theory about the different methods to enable you to make sensible decisions about the best techniques to use in any given situation. However, there will be a strong focus on the practical side of forecasting, the 'art', in order to make you competent users of standard techniques.
Module aims
The module provides an introduction to some of the foundational and current quantitative forecasting methods, and its overall aim is to develop practical competence in their use and understanding of their strengths and weaknesses. The module looks at models for short term forecasting, as these illustrate all the basic principles of analysing, comparing and extrapolating different models, while maintaining an understanding of the breadth and variety of different forecasting methods from quantitative to qualitative for a variety of forecast horizons.
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
Introduction to Business Forecasting, Time Series and their components
An introduction to some of the main foundational / current time series forecasting methods, for example: Regression with Time Series Data, Smoothing methods, The Box-Jenkins (Arima) Methodology...
Learning outcomes
By the end of the module, students should be able to:
- Research a relevant topic using available literature sources and present cogently and effectively at masters level.
- Demonstrate a firm understanding of the ideas and principles underlying the most commonly used forecasting models.
- Comprehensively understand the relevant issues and measures available to aid selection of the most suitable models.
Indicative reading list
Amstrong, J. S. (Ed.) (2001). Principles of Forecasting: a handbook for researchers and practitioners. Kluwer.
Chatfield, C. (2004) The Analysis of Time Series. Chapman & Hall.
Hanke, J.E. and Wichern, D.W. (2009). Business Forecasting. Pearson Prentice Hall.
Makridakis, S. Wheelwright S.C. and Hyndman, R.J. (1998). Forecasting, Methods and Applications, 3rd ed. John Wiley & Sons.
Ord, K. and Fildes, R. (2013). Principles of Business Forecasting, International ed, South-Western Cengage Learning.
Online textbook:
Forecasting: Principles and Practice: https://www.otexts.org/fpp
Website:
http://www.forecastingprinciples.com/
Research element
The group work asks students to research a given topic in order to widen their understanding of business forecasting methods.
Subject specific skills
Apply several forecasting models to real data sets, conducting a range of analyses using appropriate software.
Investigate real data sets and be able to report on the findings from a piece of modelling and analysis in practical terms.
Transferable skills
Group working skills
Communication skills
Numeracy and IT skill
Study time
Type | Required |
---|---|
Lectures | 9 sessions of 1 hour (6%) |
Practical classes | 9 sessions of 2 hours (12%) |
Private study | 49 hours (33%) |
Assessment | 74 hours (49%) |
Total | 150 hours |
Private study description
49 hours private study
Costs
No further costs have been identified for this module.
You do not need to pass all assessment components to pass the module.
Assessment group D4
Weighting | Study time | Eligible for self-certification | |
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Assessment component |
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Group coursework | 25% | 19 hours | No |
1500 words |
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Reassessment component |
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Individual assignment | Yes (extension) | ||
Assessment component |
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In-person Examination | 75% | 55 hours | No |
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Reassessment component is the same |
Assessment group S
Weighting | Study time | Eligible for self-certification | |
---|---|---|---|
Assessment component |
|||
Group coursework | 25% | 19 hours | No |
Reassessment component is the same |
|||
Assessment component |
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Individual Assignment | 75% | 55 hours | No |
Reassessment component is the same |
Feedback on assessment
Assessments are graded using standard University Postgraduate Marking Criteria and written feedback is provided. Feedback for individual essays includes comments on a marksheet. Overall percentage marks are awarded for examination performance and general examination feedback is provided to the cohort.
Courses
This module is Optional for:
- Year 1 of TIBS-N1N3 Postgraduate Taught Business Analytics
- Year 4 of USTA-G300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics
This module is Option list C for:
- Year 4 of USTA-G300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics