Learning Outcomes
1.Understand the importance of forecasting
2.Understand the theory of different forecasting methods (exponential smoothing models, simple and multiple linear regression and non-linear regression models)
3.Classify exponential smoothing methods (Holt, Brown, Holt-Winter Gardner-McKenzie) by Pegel and by Gardner-McKenzie
4.Apply computer software (Data analysis, Solver, Minitab) to calculate model parameters
5.Evaluate forecast accuracy
6.Combine statistical and critical forecasting methods to solve business problems
Course Content (Syllabus)
Importance of forecasting, forecasting categories, key forecasting steps. Data preparation: missing values - calendar adjustments - price indices - chi-squared goodness-of-fit test. Evaluating forecast accuracy. Confidence intervals for forecasting. Moving average methods. Exponential smoothing methods (Holt, Brown, Holt-Winter models). Exponential smoothing with correction parameter (Gardner-McKenzie model). Classification of exponential smoothing methods by Gardner-McKenzie and Pegel. Simple and multiple linear regression. Non-linear regression. Computer forecasting programs. Time series decomposition methods. Intermittent demand forecasting models (Croston, SBA). Critical methods: the Delphi method and the forecast by analogy method.
Description
The final grade Β is a combination of the grades in the final written examination (T), the midterm examination (Π) and the project/homework (E) as follows:
• If either Τ < 4,5 or (Τ+Π)/2 < 4, then the final grade is Β = (0,8)Τ.
• In every other case the final grade is Β = max {(0,6)Τ + (0,3)Π + (0,2)Ε, (0,8)T}.
Course Bibliography (Eudoxus)
1. Πετρόπουλος, Φ., Ασημακόπουλος Β., 2013. Επιχειρησιακές προβλέψεις, Εκδόσεις Συμμετρία.
2. Αγιακλόγλου, Χ., Οικονόμου Γ., 2004. Μέθοδοι Προβλέψεων και Ανάλυσης Αποφάσεων, Εκδόσεις Μπένου.
Additional bibliography for study
- Hanke, J., Wichern, D., 2009. Business Forecasting, 9th edition, Pearson Education Inc.
- Makridakis, S., Wheelwright, S., Hyndman, R., 1998. Forecasting: Methods and Applications, 3rd edition, Wiley.
- Mendenjall, W., Sincich, T., 1996. A second course in statistics: regression analysis, 5th edition, Prentice Hall.
- Montgomery, D., Runger, G., Hubele, N., 2007. Engineering Statistics, Wiley.