1. Practical computer-based class test, 1 hour and 15 minutes, 50% (Learning outcomes 1,2 and 3)
2. Examination, 2 hours, 50% (All learning outcomes)

Rationale for and limitations of forecasting.
Decomposition methods for time-related data. Identification of trend, seasonal components for additive and multiplicative models; seasonal indices; forecasts. Use of simple exponential smoothing.
Understanding relationships between paired data. Scatter diagrams. Coefficients of correlation and determination. Simple linear regression techniques. Estimates for intercept, slope and predictions. Variability and consideration of accuracy of estimates.
Introduction to hypothesis testing. t-test for regression parameter estimates.
Nature and cost aspects of stock control. Economic order quantity, lead times, re-order levels, discounts and stockouts. Understanding the role of uncertainty and safety stock.

Delivery will be via a 1 hour lecture and 2 hour practical/lab tutorial of size 20.
Lecture material will demonstrate and explain the mathematical concepts and techniques relevant to the module content. Lab based tutorials will reinforce the lecture material and provide an opportunity to analyse data, practice techniques and learn to use appropriate computer software and interpret its output.

Les Oakshott, Essential Quantitative Methods for Business Management and Finance, 2nd edition, Palgrave 2001, ISBN: 0333985761
Bancroft & O'Sullivan, Quantitative Methods for Accounting and Business Studies McGraw-Hill 1993, ISBN: 0070845646
Gaynor & Kirkpatrick, Introduction to Time-series Modeling and Forecasting in Business & Economics McGraw-Hill 1994, ISBN: 0071133348

Spreadsheet and statistical software such as Excel and SPSS

Knowledge of simple mathematical/statistical methods and basic computer literacy, for example Data Analysis module or equivalent.