Practice Evaluation Metrics For Forecasting (10.10) - Time Series Analysis and Forecasting

Practice: Evaluation Metrics for Forecasting

Lesson 10.10Time Series Analysis and Forecasting

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10 questions

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5 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
4 questions · about 3 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What does MAE stand for and how is it calculated?
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Look for average and absolute differences in your resources.
Question 2.
What is MSE and why is it important?
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Think about how squaring errors affects their significance.
3Question 3.
What does RMSE provide that's different from MAE?
- Average errors
- Percentage errors
- Error in original units
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Think about which metric helps in understanding actual data more clearly.
4Question 4.
True or False: MAPE can be misleading when actual values are close to zero.
- True
- False
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Consider the impact of division by small numbers.
Question 5.
A forecasting model predicts sales for five consecutive months. The predictions were [200, 220, 240, 250, 230], while the actual sales were [180, 210, 240, 270, 210]. Calculate MAE, MSE, and RMSE.
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Work step by step: calculate the differences first!
Question 6.
Explain why MAPE might be a misleading metric in certain situations and suggest an alternative.
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Reflect on the cases where actuals fluctuate significantly.

6 more questions in this section. Enroll free to practise them all.