14 hours (usually 2 days including breaks)
This course is part of the Data Scientist skill set (Domain: Analytical Techniques and Methods).
R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.
Problems facing forecasters
- Customer demand planning
- Investor uncertainty
- Economic planning
- Seasonal changes in demand/utilization
- Roles of risk and uncertainty
Time series Forecasting
- Seasonal adjustment
- Moving average
- Exponential smoothing
- Linear prediction
- Trend estimation
- Stationarity and ARIMA modelling
Econometric methods (casual methods)
- Regression analysis
- Multiple linear regression
- Multiple non-linear regression
- Regression validation
- Forecasting from regression
- Delphi method
- Scenario building
- Technology forecasting
- Forecast by analogy
Simulation and other methods
- Prediction market
- Probabilistic forecasting and Ensemble forecasting
He was very informative and helpful.
Elena Velkova - CEED Bulgaria
Practical exercises with R were very helpful.