1. How do data scientists use statistics?
  2. What’s the difference between SAS, R, And Python Programming?
  3. What are interpolation and extrapolation?
  4. What is the difference between population and sample in data?
  5. What are the steps in making a decision tree?
  6. How is machine learning deployed in real-world scenarios?
  7. How is machine learning deployed in real-world scenarios?
  8. What do you mean by the term linear regression?
  9. What is the difference between extrapolation and interpolation?
  10. What is the purpose of A/B testing?
  11. How different is a mean value different from expected value?
  12. Why is it mandatory to clean a data set?
  13. What are the steps involved in analytics projects?
  14. What do you understand by the term recommender systems?
  15. If you had to choose between the programming languages R and Python, Which one would you use for text analytics?
  16. For linear regression, what are some of the assumptions a data scientist is most likely to make?
  17. How do you find the correlation between a categorical variable and a continuous variable?

TOP MNC DATA SCIENCE INTERVIEW QUESTIONS