Fitted Error and Forecast Error #timeseriesanalysis

Fitted Error and Forecast Error #timeseriesanalysis In this video, we introduce the foundational concepts of forecast errors and fitted errors in time series analysis, perfect for beginners! Whether you're just starting out or brushing up on your forecasting skills, this video breaks down the basics in an easy-to-understand way. 📊 What you'll learn: What is a forecast error? What is a fitted error? How to distinguish between past fitted values and future forecasted values. The importance of reference time (Yt) in time series analysis. We’ll use simple examples to explain how forecast and fitted values are derived from historical data, showing how errors occur and why they matter in forecasting models. Chapters 00:20 - Reference Time 01:25 - Fitted Error 02:20 - Forecast Error 🔍 Key Concepts: Reference time (Yt) – The actual value at a specific point in time. Fitted values (Ft-1, Ft-2, Ft-3) – Model predictions for past periods. Forecast values (Ft+1, Ft+2, Ft+3) – Model predictions for future periods. Fitted error – The difference between the actual value and fitted value. Forecast error – The difference between the actual value and forecasted value. If you're new to time series analysis, this video will help you understand the basics of forecasting models and the types of errors they produce. 🎯 Make sure to: Like the video 👍 Subscribe for more time series tutorials 🔔 Drop any questions or comments below! 💬 #ForecastingBasics #TimeSeriesAnalysis #FittedError #ForecastError #DataScience #ForecastingTutorial #BeginnersGuide