Statistical Deception . Lying with statistics 

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Presentation transcript:

Statistical Deception . Lying with statistics  Statistical Deception  Lying with statistics  Putting a “positive spin” on the facts

Statistical deception is not. necessarily a bad thing, Statistical deception is not necessarily a bad thing, but you need to be aware of it rather than just accepting statistics at face value.

Many problems with statistics involve problems with gathering the data:

1. Non-representative. samples . too small . too large  1. Non-representative samples  too small  too large  not randomly chosen * convenience sample * purposely chosen wrong

2. Generalizing to the. wrong population . sample is drawn from a 2. Generalizing to the wrong population  sample is drawn from a different population than the results imply

3. Comparing apples and. oranges . groups being compares 3. Comparing apples and oranges  groups being compares were different to begin with  difference is due to something other than the results imply

4. Survey bias  leading questions

 “Good boy” Effect People will give the answer they think you want to hear.

 “NOYB” effect

The more personal a question is (the more it is “none of your business”), the more likely people are to lie.

5. Placebo effect . In medicine a placebo is a 5. Placebo effect  In medicine a placebo is a fake treatment actually helps because people think it will work.

. Doesn’t have to deal with. medicine. . In general, when people  Doesn’t have to deal with medicine.  In general, when people think they are being watched or treated, they often act differently than they would otherwise.

Other issues can come up in interpreting and publicizing statistical results:

6. Changing the subject . a. k. a. “Moving the bullseye 6. Changing the subject  a.k.a. “Moving the bullseye to fit the arrows”  saying a result means something different than it really does  putting a “good spin” on the data

. finding one small thing. about the results that  finding one small thing about the results that supports what you want to find

Suppose you were the police chief in a town with a crime problem …

1993 – 94 … 100 more 1994 – 95 … 75 more 1995 – 96 … 50 more 1996 – 97 … 25 more

7. Reporting information. from biased sources. that have a vested 7. Reporting information from biased sources that have a vested interest.

Always ask “Who says so”? Try to get information from neutral parties who don’t have a stake in the outcome.

8. Misuse of the word. “significant” . implying significant means 8. Misuse of the word “significant”  implying significant means big, important, or dramatic  REMEMBER: it just means “unlikely to have happened by chance”

9. Discounting significance because something is “just statistics”