1. Python or R – Which one would you prefer for text analytics?
  2. Differentiate between univariate, bivariate and multivariate analysis.
  3. Define some key performance indicators for the product
  4. Which technique is used to predict categorical responses
  5. What is logistic regression? Or State an example when you have used logistic regression recently.
  6. What are Recommender Systems?
  7. Why data cleaning plays a vital role in analysis?
  8. Differentiate between univariate, bivariate and multivariate analysis.
  9. What do you understand by the term Normal Distribution?
  10. What is Linear Regression?
  11. What is Interpolation and Extrapolation?
  12. What is power analysis?
  13. What is the difference between Cluster and Systematic Sampling?
  14. Are expected value and mean value different?
  15. What does P-value signify about the statistical data?
  16. How you can make data normal using Box-Cox transformation?
  17. What is the goal of A/B Testing?
  18. What is an Eigenvalue and Eigenvector?
  19. What is Gradient Descent?

TOP MNC DATA SCIENCE INTERVIEW QUESTIONS