Easy Data Analyst questions

34 questions · 5 points each for a correct first answer.

1. 1.WHERE vs HAVINGsql, aggregationeasy
2. 2.Mean or median for salariesdescriptive-statisticseasy
3. 3.Which join keeps all customerssql, joinseasy
4. 4.COUNT(*) vs COUNT(column)sql, null-handlingeasy
5. 5.Best chart for a trenddata-visualizationeasy
6. 6.What a pivot table doesexcel, aggregationeasy
7. 7.Finding NULL valuessql, null-handlingeasy
8. 8.Correlation and causationstatistics, critical-thinkingeasy
9. 9.COUNT(DISTINCT) with NULLssql, aggregationeasy
10. 10.Rows from an INNER JOINsql, joinseasy
11. 11.UNION vs UNION ALLsql, set-operationseasy
12. 12.AVG with a NULL valuesql, null-handlingeasy
13. 13.Bucketing with CASE WHENsql, case-expressionseasy
14. 14.Dividing two integers in SQLsql, data-typeseasy
15. 15.Why this GROUP BY failssql, aggregationeasy
16. 16.Does BETWEEN include the endssql, filteringeasy
17. 17.Matching text with LIKEsql, filteringeasy
18. 18.Top seller with ORDER BY and LIMITsql, sortingeasy
19. 19.Absolute references in Excelexcel, formulaseasy
20. 20.VLOOKUP returns wrong pricesexcel, lookupseasy
21. 21.SUMIFS with two conditionsexcel, formulaseasy
22. 22.Median of an even-sized liststatistics, descriptive-statisticseasy
23. 23.Percent change up and downbusiness-math, metricseasy
24. 24.Percentage points vs percentbusiness-math, communicationeasy
25. 25.Calculating monthly churnmetrics, retentioneasy
26. 26.Overall funnel conversionmetrics, funnelseasy
27. 27.Chart for 12 product categoriesdata-visualizationeasy
28. 28.Lost leading zeros in IDsdata-cleaning, exceleasy
29. 29.Counting missing values in pandaspython, pandaseasy
30. 30.Total sales per city in pandaspython, pandaseasy
31. 31.Type of a 1 to 5 ratingstatistics, data-typeseasy
32. 32.Dimensions vs measuresbi-tools, data-visualizationeasy
33. 33.Which set has more spreadstatistics, descriptive-statisticseasy
34. 34.What a primary key guaranteessql, data-modelingeasy