Welcome to our channel! In this video, we dive deep into the world of forecasting accuracy by exploring three essential error metrics: Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE). Understanding these metrics is crucial for improving your forecasting models and making better data-driven decisions.
🔍 **What You'll Learn:**
1. What are MAD, MSE, and MAPE?
2. How to calculate each metric.
3. The advantages and disadvantages of using each metric.
4. Real-world examples to illustrate their application.
5. Tips for choosing the right error metric for your forecasting needs.
📈 Whether you're a data analyst, business manager, or simply interested in learning more about forecasting, this video will provide you with valuable insights to enhance your skills.
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#Forecasting #DataAnalysis #MAD #MSE #MAPE #ForecastingErrors #DataScience
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**Chapters:**
0:00 Introduction
1:20 Understanding MAD (Mean Absolute Deviation)
3:45 Calculating MSE (Mean Squared Error)
6:15 Exploring MAPE (Mean Absolute Percentage Error)
8:40 Comparing the Metrics
11:00 Real-World Examples
13:30 Tips for Choosing the Right Metric
15:00 Conclusion and Summary