From Betsey Stevenson & Justin Wolfers, a short primer on separating lies from statistics:
1. Focus on how robust a finding is, meaning that different ways of looking at the evidence point to the same conclusion. Do the same patterns repeat in many data sets, in different countries, industries or eras?
2. Results that are Statistically Significant means it’s unlikely findings simply reflect chance. Don’t confuse this with something actually mattering.
3. Be wary of scholars using high-powered statistical techniques as a bludgeon to silence critics who are not specialists.
4. Don’t fall into the trap of thinking about an empirical finding as “right” or “wrong.”
5. Don’t mistake correlation for causation.
6. Always ask “so what?” The “so what” question is about moving beyond the internal validity of a finding to asking about its external usefulness.
Great stuff. I recall something from Carl Sagan on this — I’ll see if I can dig it up.
Six Ways to Separate Lies From Statistics
By Betsey Stevenson & Justin Wolfers
Bloomberg View, May 1, 2013 http://www.bloombergview.com/articles/2013-05-01/six-ways-to-separate-lies-from-statistics
Please use the comments to demonstrate your own ignorance, unfamiliarity with empirical data and lack of respect for scientific knowledge. Be sure to create straw men and argue against things I have neither said nor implied. If you could repeat previously discredited memes or steer the conversation into irrelevant, off topic discussions, it would be appreciated. Lastly, kindly forgo all civility in your discourse . . . you are, after all, anonymous.
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