Sandbox: Difference between revisions

From ChanceWiki
Jump to navigation Jump to search
No edit summary
Line 1: Line 1:
==Lucky Charms and Disappointing Journalism==
==Odds are, it's wrong==
[http://online.wsj.com/article/SB10001424052748703648304575212361800043460.html The power of lucky charms: New research suggests how they really make us perform better]<br>
[http://www.sciencenews.org/view/feature/id/57091/title/Odds_Are,_Its_Wrong Odds are, it's wrong]<br>
by Carl Bialik, ''Wall Street Journal'', 28 April 2010
by Tom Siegfried, ''Science News'', 27 March 2010


The headline of the article is eye catching.  The descriptions of the success or failure of the lucky charms is, however, an indictment of the way the journalism profession discusses statistics.  Especially because the author, Carl Bialik, unlike most journalists, knows better.  In fact, while his first paragraph tries to draw the reader in with “Can luck really influence the outcome of events,” his second paragraph begins with “They [lucky charms] do (sometimes)” as a means of absolving himself from taking the material seriously.
This is a provocative essay on the limitations of significance testing in scientific research.  The main themes are that it is easy to do the such tests incorrectly, and, even when they are done correctly, they are subject to widespread misinterpretation.


In silly instance after silly unreplicated instance, the article tells us that averages improve or don’t improve with lucky charms present, but never once do we know anything about the variability between the charm holders and those deprived of the lucky charms. 
Submitted by Bill Peterson, based on a suggestion from Scott Pardee


'''Discussion Questions'''
'''Discussion Questions'''


1.  The first example referred to will be published in the June issue of Psychological Science; the study involves 28 German college students whose putting with a “lucky ball” sank “6.4 putts out of 10, nearly two more putts, on average, than those who weren’t told the ball was lucky.”  Evaluate the comment, “but the effect was big enough to be statistically significant.”  What additional statistical information would be necessary to view this study as worthwhile?
1.  (suggested by Bill Jefferys) Box 2, paragraph 1 of the article states "Actually, the P value gives the probability of observing a result if the null hypothesis is true, and there is no real effect of a treatment or difference between groups being tested. A P value of .05, for instance, means that there is only a 5 percent chance of getting the observed results if the null hypothesis is correct." Why is this statement wrong?
 
2. A well known quotation in the field of statistics is “The plural of anecdote is not evidence.”  Read the article and evaluate the anecdotes.
 
3.  Superstition plays a vital part of this article: a motorcyclist who wears “gremlin balls” to “help ward off accidents”; a lucky brown suit “to help the horse he co-owns, Always a Party, win the second race”; after an eclipse, “major  U.S. stock-market indexes typically fall.”  Compare those superstitions with the reading of tea leaves and goat entrails of the middle ages.
 
Submitted by Paul Alper


==Tea party graphics==
==Tea party graphics==

Revision as of 00:55, 4 May 2010

Odds are, it's wrong

Odds are, it's wrong
by Tom Siegfried, Science News, 27 March 2010

This is a provocative essay on the limitations of significance testing in scientific research. The main themes are that it is easy to do the such tests incorrectly, and, even when they are done correctly, they are subject to widespread misinterpretation.

Submitted by Bill Peterson, based on a suggestion from Scott Pardee

Discussion Questions

1. (suggested by Bill Jefferys) Box 2, paragraph 1 of the article states "Actually, the P value gives the probability of observing a result if the null hypothesis is true, and there is no real effect of a treatment or difference between groups being tested. A P value of .05, for instance, means that there is only a 5 percent chance of getting the observed results if the null hypothesis is correct." Why is this statement wrong?

Tea party graphics

A mighty pale tea
by Charles M. Blow, New York Times, 16 April 2010

This article recounts Blow's experience visiting a Tea Party rally as a self-identified "infiltrator." He was interested in assessing the group's diversity. Reproduced below is a portion of a graphic, entitled The many shades of whites, that accompanied the article.

Shades.png

The data are from a recent NYT/CBS Poll.

Submitted by Paul Alper

Retrieved from "https://www.causeweb.org/wiki/chance/index.php?title=Sandbox&oldid=10623"