ezoic

Saturday, July 31, 2021

an interesting website for data analysis

 

https://www.digitaling.com/


it is in chinese, 

internet industry technical terms

advertising related  


1. ad network


2. ad exchange

3. RBT real time bidding

4. DSP demand side platform

5. DMP data-management platform

6. programmatic buying

7. Private market place

8. Programmatic Direct buy

9. Premium Inventory

10. Remnant Inventory

11. CPM cost per mille

12. CPC cost per click, Cost Per Thousand;Cost Per Impressions

13. CPC (Cost Per Click;Cost Per Thousand Click-Through)

14. CPA(Cost-per-Action)

15. CPS(Cost-Per-Sale)

16. CPT cost per time

17. CPV cost per visit

18. CPI cost per visit

19. CPD cost per download

20. banner

21 Interstitial

22. Native Advertising (Native Ads)

Operation related


23. AARRR :Acquisition、Activation、Retention、Revenue、Refer

24. DNU(Daily New Users)

25. CAC(Customer Acquisition Cost)

26. CPC (Cost Per Customer )

27. CR (Conversions Rates)

28. DAU(Daily Active Users)

29. WAU(Weekly Active Users)

30. MAU(Monthly Active Users)

31. DEC(Daily Engagement Count)

32. DAOT/AT(Daily Avg.Online Time)

33. DAU (Daily Active User)

34. MAU (Monthly active users)

35.Users Retention

36. Day 1/3/7/30 Retention Ratio

37. Users Churn

38. Day 1 Churn Ratio

39. Day 7 Churn Ratio

40. Day 30 Churn Ratio

41. MPR(Monthly Payment Ratio)

42.  MAU, APA

43. APA(Active Payment Account)

44. ARPU(Average Revenue per Uers)

45. ARPU

46. monthly ARPU= /MAU

47.ARPPU(Average Revenue per Paying User)

48. ARPPU

monthly ARPPU=

49. life time

50 life time value

51 PCU(Peak Concurrent Users)

52. ACU(Average Concurrent Users)

53. New Users Converstion Rate

54. SEO(Seach Engine Optimization)

55. SEM (Search Engine Marketing)

56. ASO (App Store Optimization)

57. KPI(Key performance indicators)

58. GMV(Gross Merchandise Voltume )

59. SKU (Stock Keeping Unit)

60. ‎Long Tail Keyword

61. MVP(Minimum Viable Product )

62. SP (Service Provider)

63. CP(Content Provider

64. BD (Business Development)

65. SDK (Software Development Kit)

66. UE/UE(User Experience)

67. EDM (Email Direct Marketing)

68. SNS (Social Networking Services)

69. UGC (User Generated Content)

70. PGC(Professional Generated Content)

71. OGC(Occupationally-generated Content)

72. KOL(Key Opinion Leader)


Tuesday, July 13, 2021

statistics knowledge websites

 


https://stattrek.com/


https://www.khanacademy.org/math/statistics-probability


https://brilliant.org/


https://www.datacamp.com/community/tutorials

statistical knowledge

 1. how to normalize data

2. how to detect outlier, what is IQR?

3. how to reverse a list in python

4. how to insert a number in a list in python

5. how does spark's rdd work? how is it diffrent from pyspark's dataframe?

6. how to calculate cumulative sums in a table in sql

7. what is the difference between mapreduce and in-memory?

8. what is mapreduce?

9. what is lag?

10. proceeding and in sql?

11. how to count number of data points in a numpy array?

12. how to do hyperthesis test?

13. what is false positive rate? what is false negative rate? 

14. how to delete duplicates in a dataframe in python?

15. what is false discovery rate? and  bonferroni correction?


Monday, July 12, 2021

what is false discovery rate

 what is false discovery rate?


https://www.youtube.com/watch?v=3PVkfQRUGI4


an interesting video talking about it. 

it is something we predefined in a hyperthesis testing.  a type one erro for the multiple testing we tried to control. 



a concise video about bonferroni correction

 https://www.youtube.com/watch?v=HLzS5wPqWR0


to understand bonferroni correction, first , we need to understand family-wise error rate, 

a1=type one error


FWER=1-(1-a1)^m


m is the number of tests


bonferroni correction 

corrected a1

=a1/k


k is the number of tests performed. 


FWER=1-(1-a1/k)^k








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