Chance News 73: Difference between revisions

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“Our culture encodes a strong bias either to neglect or ignore variation.  We tend to focus instead on measures of central tendency, and as a result we make some terrible mistakes, often with considerable practical import.”  (Stephen Jay Gould, cited p. 11)<br>
“Our culture encodes a strong bias either to neglect or ignore variation.  We tend to focus instead on measures of central tendency, and as a result we make some terrible mistakes, often with considerable practical import.”  (Stephen Jay Gould, cited p. 11)<br>
“Plans based on <i>average</i> assumptions are wrong on <i>average</i>.”  (Savage, p. 11)
 
Savage, p. 11
“Plans based on <i>average</i> assumptions are wrong on <i>average</i>.”  (Savage, p. 11)<br>
</div align=right>
“Far better an approximate answer to the right question, which is often vague, than the exact answer to the wrong question, which can always be made precise.” (John W. Tukey, cited p. 38)<br>
“Far better an approximate answer to the right question, which is often vague, than the exact answer to the wrong question, which can always be made precise.”
“I have found that teaching probability and statistics is easy.  The hard part is getting people to learn the stuff.” (Savage, p. 49)<br>
<div align=right>
“Statisticians often describe a numerical uncertainty using the Red Words, RANDOM VARIABLE, but I will stick with ‘uncertain number.’  ….  [S]top thinking of uncertainties as single numbers and begin thinking of them as shapes, or distributions.  ….  If you think of an uncertain number as a bar graph, you will not be seriously misled.” (Savage, p. 59ff)<br>
John W. Tukey, cited, p. 38
“When Max Henrion [CEO at Lumina Decision Systems and adjunct professor at Carnegie Mellon] studied physics as an undergraduate at Cambridge University, he reports ‘My professors drummed into me that any number is worthless unless you report the uncertainty attached to it.’  Then as a PhD student in policy analysis at Carnegie Mellon in the 1970s he noticed that ‘analysts in public policy and business usually ignored that principal – even though their numbers were generally many orders of magnitude more uncertain than the physicists’." (Savage, p. 339)<br>
</div align=right>
“Joe Berkson, a statistician at the Mayo Clinic, developed his own criterion, which he termed the IOT Test, or Inter Ocular Trauma Test, requiring a graph that hit you between the eyes.” (Savage, p. 325)<br>
“I have found that teaching probability and statistics is easy.  The hard part is getting people to learn the stuff.”
<div align=right>
Savage, p. 49
</div align=right>
“Statisticians often describe a numerical uncertainty using the Red Words, RANDOM VARIABLE, but I will stick with ‘uncertain number.’  ….  [S]top thinking of uncertainties as single numbers and begin thinking of them as shapes, or distributions.  ….  If you think of an uncertain number as a bar graph, you will not be seriously misled.”
<div align=right>
Savage, p. 59ff
</div align=right>
“When Max Henrion [CEO at Lumina Decision Systems and adjunct professor at Carnegie Mellon] studied physics as an undergraduate at Cambridge University, he reports ‘My professors drummed into me that any number is worthless unless you report the uncertainty attached to it.’  Then as a PhD student in policy analysis at Carnegie Mellon in the 1970s he noticed that ‘analysts in public policy and business usually ignored that principal – even though their numbers were generally many orders of magnitude more uncertain than the physicists’."
<div align=right>
Savage, p. 339
</div align=right>
“Joe Berkson, a statistician at the Mayo Clinic, developed his own criterion, which he termed the IOT Test, or Inter Ocular Trauma Test, requiring a graph that hit you between the eyes.”
<div align=right>
Savage, p. 325
</div align=right>


See [http://www.causeweb.org/wiki/chance/index.php/Chance_News_52#The_Fl Chance News 52] for a review of <i>The Flaw of Averages</i> by Prof. Laurie Snell.<br><br>
See [http://www.causeweb.org/wiki/chance/index.php/Chance_News_52#The_Fl Chance News 52] for a review of <i>The Flaw of Averages</i> by Prof. Laurie Snell.<br><br>

Revision as of 12:16, 16 May 2011

Quotations

From The Flaw of Averages, by Sam L. Savage, Wiley, 2009:

“Our culture encodes a strong bias either to neglect or ignore variation. We tend to focus instead on measures of central tendency, and as a result we make some terrible mistakes, often with considerable practical import.” (Stephen Jay Gould, cited p. 11)

“Plans based on average assumptions are wrong on average.” (Savage, p. 11)
“Far better an approximate answer to the right question, which is often vague, than the exact answer to the wrong question, which can always be made precise.” (John W. Tukey, cited p. 38)
“I have found that teaching probability and statistics is easy. The hard part is getting people to learn the stuff.” (Savage, p. 49)
“Statisticians often describe a numerical uncertainty using the Red Words, RANDOM VARIABLE, but I will stick with ‘uncertain number.’ …. [S]top thinking of uncertainties as single numbers and begin thinking of them as shapes, or distributions. …. If you think of an uncertain number as a bar graph, you will not be seriously misled.” (Savage, p. 59ff)
“When Max Henrion [CEO at Lumina Decision Systems and adjunct professor at Carnegie Mellon] studied physics as an undergraduate at Cambridge University, he reports ‘My professors drummed into me that any number is worthless unless you report the uncertainty attached to it.’ Then as a PhD student in policy analysis at Carnegie Mellon in the 1970s he noticed that ‘analysts in public policy and business usually ignored that principal – even though their numbers were generally many orders of magnitude more uncertain than the physicists’." (Savage, p. 339)
“Joe Berkson, a statistician at the Mayo Clinic, developed his own criterion, which he termed the IOT Test, or Inter Ocular Trauma Test, requiring a graph that hit you between the eyes.” (Savage, p. 325)

See Chance News 52 for a review of The Flaw of Averages by Prof. Laurie Snell.

From Picturing the Uncertain World, by Howard Wainer, Princeton, 2009:

“[O]n average Bill Gates and I can afford a new Rolls and a winter home in Provence.”


Submitted by Margaret Cibes

Forsooth

What's in a name?

Peter, Deborah popular names for CEOs
VPR News Morning Edition, 29 April 2011

"If your name is Peter or Deborah, you're more likely to be a CEO. That's what the social networking site LinkedIn found." You can listen to the rest of this Vermont Public Radio broadcast here.

The story was featured in a variety of news outlets:

Discussion Question
A tweeted comment on this site says: "Great analysis, although this can be explained mostly by the age group ..." What are the implications of this? How might you explore them?

Submitted by Jeanne Albert

Scaling the normal curve

Picturing the Uncertain World
by Howard Wainer, Princeton, 2009, p. 171.

This book is a collection of articles that Wainer had authored/co-authored in Chance (2000-2007), American Scientist (2007), and American Statistician (1996).

In Chapter 16, "Galton's Normal," Wainter gives an example of the relative heights of the points on a standard normal curve and of why our sketches of normal curves do not, and cannot, come close to accurate scale drawings.

He calculates that, even if the height at z = 13 were only 1 mm, then the height of the normal curve at the center, z = 0, would be about 5 x 10^30 km, or 5.3 x 10^17 light years. This is equivalent to a height that would be 3.4 million times larger than the universe. (His figures check out.)

Even if the height were 1 mm at z = 6, the height at z = 0 would be 66 km. Thus it still could not be drawn to scale.

Submitted by Margaret Cibes