The objective of this program is to present a comprehensive view of the various tools and techniques used in forecasting for managerial decision-making, including the problem of demand estimation, market size determination, sales projections, analyzing, and predicting stock prices. The methodology, covering various time series analysis techniques, and regression methods, is presented with appropriate mix of case analysis and numerical demonstration with the aid of software package (R) to enable the participants to meet their own forecasting needs.
Participants would be divided into small groups to work on forecasting projects that would be either decided/brought by the participants or given to them. Learning from these projects will be the key take-away from the program. Better part of a program day is reserved for participants to work on this project. In addition, the participants are expected to work during the evenings of the program days.
Program Contents:
- Basic statistical concepts: standard error, confidence interval estimation, and significance values in testing.
- Simple and Multiple regression
- Logit Profit Models
- Time Series Decomposition Models
- Smoothing Models
- Box Jenkins (ARIMA)
- ARIMA with regression errors and ARIMAX
- Models for time series with multiple-level seasonality.
- Bass Model for new product forecasting
- Combining Forecast and Forecast Evaluation
- Forecasting projects/case studies from Industry
- Project work and presentations
Participants having some introduction to elementary statistics at 10+2 or Undergraduate level.
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