Predictive Modelling with R

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
• Extrapolation
• 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

Judgemental methods

• Surveys
• Delphi method
• Scenario building
• Technology forecasting
• Forecast by analogy

Simulation and other methods

• Simulation
• Prediction market
• Probabilistic forecasting and Ensemble forecasting