33 Forecasting Interview Questions (Time Series Analysis)

Hany Hossny, PhD
2 min readApr 16, 2022
  1. What is Moving Average?
  2. What is Auto Regression (AR)?
  3. What is the difference between ARMA and ARIMA?
  4. Can you explain RNN and LSTM, and when you use each for TSA?
  5. Can you explain Dynamic Time Warping?
  6. Can you explain the Hidden Markov Model?
  7. How would you evaluate a time series forecasting model?
  8. What is the Sliding Window method for Time Series Forecasting?
  9. Can you explain Backward Shift and Difference Operators?
  10. How the IQR (Interquartile Range) is used in Time Series Forecasting?
  11. what methods will you use to measure the similarity/difference between two time-series vectors?
  12. Can Non-Sequential Deep Learning Models outperform Sequential Models in Time-Series Forecasting?
  13. Can you list some Forecasting methods for Stationary and Non-stationary Time-Series?
  14. How do you Normalise Time-Series Data?
  15. How is Pearson Correlation used with Time Series? What are its assumptions and limitations?
  16. What does it mean to have zero Pearson Correlation?
  17. What is cross-correlation?

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Hany Hossny, PhD

An AI/ML enthusiast, academic researcher, and lead scientist @ Catch.com.au Australia. I like to make sense of data and help businesses to be data-driven