Measuring Forecast Error in Time Series Forecasting using MSE, MAD, and MAPE techniques

This lecture recording provides an overview of Measuring Forecasting Error. The Forecast Error is the difference between the observed value of the times series and the forecast. We will review three types of Forecast Errors, including Mean Absolute Deviation Error (MAD), Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE). Content derived from from the Textbook "Operations Management, Sustainability and Supply Chain" 13th edition by Jay Heizer, Barry Render and Chuck Munson. Chapter 4 on Forecasting.

At www.operationsuniversity.org you can get Free copies of this Slide Deck and other Chapter Outlines. Practice Problems & Homework Support (step by step guides how to complete the quantitative questions + MS Excel templates) are available for a small fee.

For membership options on joining the Operations & Supply Chain University community and details on how to get exclusive perks & free products, click the link below:    / @operationsandsupplychain