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Predicting key business and economic variables is increasingly important, as it drives both objective decision-making and improved profitability. This course aims to cover the basic forecasting methods used to predict business and economic variables, based on historical data. These include traditional regression, time series, as well as emerging methods such as ensemble forecasts. Throughout, the focus will be on practical implementation of forecasting techniques using the publicly available software “R”. The importance of benchmarking, the assessment of forecasts from different models, and the use of forecasts in decision-making frameworks, will also be highlighted.
Intended learning outcomes
On completion of this subject, students should be able to demonstrate;
- an understanding of a range of models relevant to forecasting time series data.
- the skills to apply appropriate modelling and forecasting techniques in the “R” software to business and economic contexts, and to critique and compare competing methodologies.
- the skills to translate forecasting outputs to information and provide recommendation for relevant business problems.
Last updated: 6 December 2019