This document discusses ways that statistics can be misleadingly presented and summarizes four methods: 1. Making wrong conclusions from off-target data, like concluding all students are good at syntax based on average scores. 2. Using plausible but misleading charts and graphs without necessary context. 3. Omitting reference points like possible ranges or zero values, making claims easier to prove. 4. Using deceptively small samples that don't represent the whole population, like a survey with a biased sample group.

2. M. Vikri Pradana Raudhatul JannahAstrid
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8. THE MISLEADING AVERAGE
Made a wrong conclusion with an off target data.
“Students in Class R 4D are good in
Syntax. Data shows the average of their
syntax’s score is above 7.”
Example:

9. Plausible Charts and GraphsPlausible Charts and Graphs

10. Example:

11. Example:

12. Presenting the Facts Without a
Reference Point
Demonstrating facts beyond the resources.
How it works:
Omitting the possible range of the data and the
zero reference point, so that it will be much
easier to prove your point.

13. Example:

14. Exercise 1
• “94% of Indonesian women agree that the
Garnier light cream can make their skin
more shinning, 92% agree the Garnier white
cream can reduce oil in their face, 93% agree
it can reduce black spot of acne.”

15. •The Deceptive
Sample

16. Exercise 2

17. Presenting
the Facts
Without a
Preference
Point
What is the answer?

18. Exercise 3
• An education report recently an increase in
Malaysian senior high school students’
mastery of English in the last three years. The
English average score achieved by students in
National Final Test in Kuala Lumpur was 76
(2001), 82 (2002) and 90 (2003). In Selangor
the average score was 74 (2001), 84 (2002)
and 88 (2003)

19. •The Misleading
Average

21. “Recognizing Statistical
Slips”
(this presentation is an excerpt
of Chapter 7 of “Critical
Reading”, an internal publication
of Unindra)