Estimation Calibration: Make Your Forecasts More Reliable
This course will teach you how to do estimation calibration through Structured Expert Judgment to make your forecasts more reliable by calculating and analyzing calibration and information scores.
What you'll learn
Managers and subject matter experts (SMEs) are faced with many challenges particularly in making reliable forecasts with minimal forecasting errors. In this course, Estimation Calibration: Make Your Forecasts More Reliable, you’ll learn to implement estimation calibration through the Structured Expert Judgment (SEJ) method by calculating calibration and information scores. First, you’ll learn what a calibration score is, and how to calculate it. Next, you’ll discover what an information score is, how it's different from the calibration score, and how to calculate it. Finally, you’ll learn how to analyze both calibration score and information score obtained from the calculation to evaluate the assessments made by experts. When you’re finished with this course, you’ll have the skills and knowledge of calculating calibration and information score under Structured Expert Judgment (SEJ) which is needed to make your forecasts more reliable through estimation calibration.
Table of contents
- Structured Expert Judgment (SEJ) Definition 4m
- Structured Expert Judgment (SEJ) Relevance 2m
- Structured Expert Judgment (SEJ) Application 2m
- Accuracy, Precision, and Statistical Accuracy Comparison 6m
- Forecasting Errors 4m
- Uncalibrated Forecast Problems 1m
- Use Case: Identifying Forecasting Errors in Work Scenarios 5m