Chance News 109: Difference between revisions

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Submitted by Margaret Cibes
Submitted by Margaret Cibes


==Item 1==
==Guide to bad statistics==
[https://www.theguardian.com/science/2016/jul/17/politicians-dodgy-statistics-tricks-guide Our nine-point guide to spotting a dodgy statistic]<br>
by David Spiegelhalter, ''The Guardian'', 17 July 2016
 
Published in the wake of the Brexit debate, but obviously applicable to upcoming US presidential election, the article offers these nine strategies for twisting numbers to back a specious claim.
 
* Use a real number, but change its meaning
* Make the number look big (but not too big)
* Casually imply causation from correlation
* Choose your definitions carefully
* Use total numbers rather than proportions (or whichever way suits your argument)
* Don’t provide any relevant context
* Exaggerate the importance of a possibly illusory change
* Prematurely announce the success of a policy initiative using unofficial selected data
* If all else fails, just make the numbers up
 
To be continued...
 
Submitted by Bill Peterson


==Item 2==
==Item 2==

Revision as of 18:55, 24 August 2016

Quotations

"We’ve reached that stage of the campaign. The back-to-school commercials are on the air, and the 'unskewing' of polls has begun — the quadrennial exercise in which partisans simply adjust the polls to get results more to their liking, usually with a thin sheen of math-y words to make it all sound like rigorous analysis instead of magical thinking."

--Harry Enten, in: The polls aren’t skewed: Trump really is losing badly, FiveThirtyEight.com, 9 August 2016

Submitted by Bill Peterson

Forsooth

"The LSAT predicted 14 percent of the variance between the first-year grades [in a study of 981 University of Pennsylvania Law School students]. And it did a little better the second year: 15 percent. Which means that 85 percent of the time it was wrong."

--Lani Guinier, in: The Tyranny of the Meritocracy: Democratizing Higher Education in America (Beacon Press 2015), p. 19.

Submitted by Margaret Cibes

Guide to bad statistics

Our nine-point guide to spotting a dodgy statistic
by David Spiegelhalter, The Guardian, 17 July 2016

Published in the wake of the Brexit debate, but obviously applicable to upcoming US presidential election, the article offers these nine strategies for twisting numbers to back a specious claim.

  • Use a real number, but change its meaning
  • Make the number look big (but not too big)
  • Casually imply causation from correlation
  • Choose your definitions carefully
  • Use total numbers rather than proportions (or whichever way suits your argument)
  • Don’t provide any relevant context
  • Exaggerate the importance of a possibly illusory change
  • Prematurely announce the success of a policy initiative using unofficial selected data
  • If all else fails, just make the numbers up

To be continued...

Submitted by Bill Peterson

Item 2