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1. Explain the difference between population variance vs sample variance
2. Describe a p-value to a 13-year-old (8th grader)
3. What Does an R-Squared Value of 0.9 Mean?
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4. What are some metrics to evaluate how predictive your logistic regression model is?
5. Can you explain precision vs. recall? How does that relate to an ROC curve?
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6. What is a database view?
7. What's the difference between a primary key & a foreign key?
8. Have you had to troubleshoot a slow query before? How did you do it?
9. When should you use a Sub-Query vs. CTE?
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10. Can you write a SQL query to find the 3-day rolling average?
(very similar to this Twitter SQL interview question on DataLemur)
https://t.co/ssEQvcrKgo
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11. Can you write a SQL query to find the most frequently purchased pairs of items?
(very similar to the Walmart SQL Interview question on DataLemur)
https://t.co/J8rwcjp8P5
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12. Which Python libraries do you use?
13. What are some steps you take to clean dirty data?
14. In this dataframe, how would you remove all rows that met X condition?
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15. Can you write code to find this value in a JSON object?
16. After loading the IRIS dataset via scikit-learn, can you build a simple regression model, and interpret the output?
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17. What are some ways you'd improve this sample Tableau dashboard, so a business stakeholder could get more value from it?
18. What metrics do you think are important to track for our business line? Do you see any potential flaws in those metrics?
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19. Walk us through 2 of your past work projects.
What the most challenging technical and non-technical part of each project?
How many of these 19 questions could you answer?
Would you be able to land the $110k Data Science job?
BTW if you enjoyed this thread:
1. Follow me
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Also, don't forget, that #SQL is a KEY part of the Data Science and Data Analyst interview process.
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