Data Driven Society. May 18th 2018. Data Driven Innovation 2018. Engineering Department, University of Roma Tre

1. ANDREA MAIETTA
HOW TO LIE
WITH STATS
AND CHARTS
@andreamaietta
amaietta@widecareservices.com

2. The truth

3. Alternative truth

4. Is truth either black or white?

5. Shades of grey

6. Statistics are not bad,
they’re drawn that way

7. The truth

8. The model

9. Different scale

10. Different precision

11. Different approaches

12. Unwilling lies

13. The truth, the whole truth,
and nothing but the truth

14. Lie without lying

15. Lie without lying
(sort of)

16. What is the truth?
«If you torture data long enough, it will
confess to anything»
Darrell Huff
Thanks to Luca Ruggeri

17. Average

18. Which average?

19. Which average?

20. Which average?

21. Normal distribution

22. Skewed distribution

23. A little example
One firm, 90 employees, 3 partners

24. A little example
One firm, 90 employees, 3 partners
Total wages: $ 1,980,000

25. A little example
One firm, 90 employees, 3 partners
Total wages: $ 1,980,000
Total salaries: $ 330,000

26. A little example
One firm, 90 employees, 3 partners
Total wages: $ 1,980,000
Total salaries: $ 330,000
Total profits: $ 450,000

27. A little example
One firm, 90 employees, 3 partners
Total wages: $ 1,980,000
Total salaries: $ 330,000
Total profits: $ 450,000
Average wage: $ 1,980,000 / 90 = $ 22,000

28. A little example
One firm, 90 employees, 3 partners
Total wages: $ 1,980,000
Total salaries: $ 330,000
Total profits: $ 450,000
Average wage: $ 1,980,000 / 90 = $ 22,000
Average salary: ($ 330,000 + $450,000) / 3
= $ 260,000

29. Not impressed

30. Let’s try again
Total wages: $ 1,980,000
Total salaries: $ 330,000
Total profits: $ 450,000

31. Let’s try again
Total wages: $ 1,980,000
Total salaries: $ 330,000
Total profits: $ 450,000
Bonus: $ 300,000
Profits: $ 150,000

32. Let’s try again
Total wages: $ 1,980,000
Total salaries: $ 330,000
Total profits: $ 450,000
Bonus: $ 300,000
Profits: $ 150,000
Total salaries: $ 330,000 + $ 300,000
= $ 630,000

33. Let’s try again
Total wages & salaries:
$ 1,980,000 + $ 630,000 = $ 2,610,000

34. Let’s try again
Total wages & salaries:
$ 1,980,000 + $ 630,000 = $ 2,610,000
Average: $ 2,610,000 / 93 = $ 28,064

35. Let’s try again
Total wages & salaries:
$ 1,980,000 + $ 630,000 = $ 2,610,000
Average: $ 2,610,000 / 93 = $ 28,064
Profits: $ 150,000 / 3 = $ 50,000

36. Let’s try again
Total wages & salaries:
$ 1,980,000 + $ 630,000 = $ 2,610,000
Average: $ 2,610,000 / 93 = $ 28,064
Profits: $ 150,000 / 3 = $ 50,000
Profits: 5,7% of total wages & salary

37. That’s better

38. Hiring?

39. Downplay for tax audit?

40. Heads or tails?

41. Heads or tails?

42. Lie by omission

43. Lie by omission

44. Little omissions

45. Sample size

46. 23% less cavities

47. 9 cats out of 10

48. 90 cats out of 100?

49. Size matters

50. The missing link

51. How about this?
90 cats out of 100

52. How about this?
90 cats out of 100
in over 1000 experiments

53. How about this?
90 cats out of 100
in over 1000 experiments
95% confidence interval: 87.3 – 92.7

54. How about this?
90 cats out of 100
in over 1000 experiments
95% confidence interval: 87.3 – 92.7
p = 0.0001

55. 83% of dentists recommend…

56. More than 80% recommend…

57. Wilful misdirection

58. Alcatraz is more expensive
than the Waldorf-Astoria

59. It’s safer being in the Navy

60. Y.M.C.A.

61. Percentiles

62. Accidents

63. Accidents

64. Use an index!

65. Spot the difference

66. Average houses
for average people

67. Average people
Average family: 3.6 persons

68. Average people
Average family: 3.6 persons
(count as 4)

69. Average people
Average family: 3.6 persons
(count as 4)
two bedrooms

70. Average people (detail)
3 or 4 persons (two bedrooms): 45%

71. Average people (detail)
3 or 4 persons (two bedrooms): 45%
1 or 2 persons (one bedroom): 35%

72. Average people (detail)
3 or 4 persons (two bedrooms): 45%
1 or 2 persons (one bedroom): 35%
More than 4 (three bedrooms): 20%

73. Average people (detail)
3 or 4 persons (two bedrooms): 45%
1 or 2 persons (one bedroom): 35%
More than 4 (three bedrooms): 20%
Won’t buy: 55%

74. Bad mistake

75. Deviations

76. Deviations

77. What is a difference?

78. What is a difference?

79. Charts

80. Don’t extrapolate

81. Sub-10sec
World Record 100m Times (Men)

82. Times change, people change,
hairstyles change

83. The past is in the past

84. Bad sales

85. Omit selection

86. Truncate the y-axis

87. Remove labels

88. Shrink the x-axis

89. Decreasing sales

90. Cumulative sales

91. Global warming

92. Absolute temperatures
(complete set)

93. Temperature change

94. Cherry picking

95. 3D Charts

96. R&D
Research 55%

97. R&D
Research 55%
Grant 18%

98. R&D
Research 55%
Grant 18%
Admin 27%

99. Does it ring a bell?

100. Let’s graph it
0%
10%
20%
30%
40%
50%
60%
Admin Grant Research

101. Turn it into a 3D chart
0%
10%
20%
30%
40%
50%
60%
Admin
Grant
Research

102. Alter perspective
0%
10%
20%
30%
40%
50%
60%

103. Change chart type
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1
Research Grant Admin

104. Alter shape
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1
Research Grant Admin

105. Pie charts

106. Pie chart
Research Grant Admin

107. A bit of perspective
Research Grant Admin

108. It works miracles!

109. Pictocharts

110. Heights or areas?

111. Correlation
or causation?

112. IE users are killers

113. Pirates cause global warming

114. Recap

115. Everybody lies

116. Number and percentages
sound closer to the truth

117. We feel deference for
authorities

118. We trust uniforms

119. Even when they’re not
(and we know it)

120. Milgram, 1974

121. Dangerous combination

122. Be careful

123. Constant vigilance!

124. “the only thing that anybody
with brains should be doing with
their life”

125. Q&A

126. Readings

127. How to lie with statistics

128. Truth, lies and statistics

129. Graphs don’t lie

130. ANDREA MAIETTA
HOW TO LIE
WITH STATS
AND CHARTS
@andreamaietta
amaietta@widecareservices.com