Lesson 7: Measuring Forecast Error
February 9, 2022
Review:
- Curvilinear Regression
- Project 1: Time Series Analysis
Presentation:
- Forecast Error
- MAD – mean absolute deviation
- MAD = ∑|Actual – Forecast|/(Number of Forecasts)
- RMSE – root mean square error
- RMSE = √(∑(Actual – Forecast)^2/(Number of Forecasts))
- Scatterplot comparison – actual vs forecast
- Residual analysis
- Outliers
- MAD – mean absolute deviation
- Demonstrate with Oil Prices
- Compare to Actual Oil Prices
Activity:
- Calculate MAD and RMSE
- Compare your forecasts for Treasury Rates from Lesson 6 to actual rates.
Assignment:
