Practice Evaluation Metrics for Forecasting - 10.10 | 10. Time Series Analysis and Forecasting | Data Science Advance
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does MAE stand for and how is it calculated?

💡 Hint: Look for average and absolute differences in your resources.

Question 2

Easy

What is MSE and why is it important?

💡 Hint: Think about how squaring errors affects their significance.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What does RMSE provide that's different from MAE?

  • Average errors
  • Percentage errors
  • Error in original units

💡 Hint: Think about which metric helps in understanding actual data more clearly.

Question 2

True or False: MAPE can be misleading when actual values are close to zero.

  • True
  • False

💡 Hint: Consider the impact of division by small numbers.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

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.

💡 Hint: Work step by step: calculate the differences first!

Question 2

Explain why MAPE might be a misleading metric in certain situations and suggest an alternative.

💡 Hint: Reflect on the cases where actuals fluctuate significantly.

Challenge and get performance evaluation