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Forsooth

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"There are 33 percent more such women in their 20s than men. To help us see what a big difference 33 percent is, Birger invites us to imagine a late-night dorm room hangout that’s drawing to an end, and everyone wants to hook up. 'Now imagine,' he writes, that in this dorm room, 'there are three women and two men.'"

--from the New York Times Book Review

Cited in Imagine 33 percent at Jordan Ellenberg's "Quodmodocumque" blog (20 November 2015).

Submitted by Priscilla Bremser

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“I showed all the data together, which helped disguise the bimodal distribution. Nothing wrong with that. All the data is there. Every piece.... [But then he suggested using] thick and thin lines to try and dress it up, or changing colors to divert attention.”

--Bob Schubert (Takata airbag engineer)

quoted in: Takata emails show brash exchanges about data tampering, New York Times, 4 January 2016

Submitted by Bill Peterson

cancer prevention

Helpless to prevent cancer? Actually, quite a bit Is in your control
By Aooron E. Carroll, TheUpshot blog, New York Times, 5 July 2016

Explaining

We Have Some Serious Explaining to Do
by Rob Santos, AMSTAT News, 1 July 2106

Conflicting polls

Jeff Witmer sent the following to the Isolated Statisticians list:

Confused by contradictory polls? Take a step back

by Nate Cohn, "Upshot" blog, New York Times, 18 July 2016

Algorithms aren't objective

Jo Hardin sent to the Isolated Statiticians.

Not So Standard Deviations

Ice Cream and IQ

Daily Chart: Ice Cream and IQ
The Economist, 1 April 2016

Note the date!

Concussions

In N.F.L., Deeply Flawed Concussion Research and Ties to Big Tobacco
By ALAN SCHWARZ, WALT BOGDANICH and JACQUELINE WILLIAM SMARCH 24, 2016 Continue reading the main storyShare This Page

Tests for gerrymandering

Let math save our democracy
by Sam Wang, New York Times, 5 December 2015

How gerrymandered is your Congressional district?
by Christopher Ingraham, Washington Post,15 May 2014

appeal to isoperimetric inequality: in the plane, a circle maximizes the area of a closed curve with a fixed perimeter.

How to rig an election
Economist, 25 April 2002

Subtitled: "In a normal democracy, voters choose their representatives. In America, it is rapidly becoming the other way around."

"Worst of all is the state's extraordinary 17th District, which is a crab (see chart). Though most of it lies in the western part of the state, two claws stretch out towards the eastern part to grab Democratic cities in order to make the surrounding 18th and 19th districts more reliably Republican."

"as used to be said of the old Texas 6th (which was a road from Houston to Dallas), that you could kill most of the constituents by driving down the road with the car doors open."

Diet science

Are fats unhealthy? The battle over dietary guidelines
by Aaron E. Carroll, “Upshot” blog, New York Times, 12 October 2015.

Related “Upshot”: Behind new dietary guidelines, better science, February 23, 2015

Chance of gun death

http://www.nytimes.com/2015/12/05/upshot/in-other-countries-youre-as-likely-to-be-killed-by-a-falling-object-as-a-gun.html?rref=upshot&module=Ribbon&version=context&region=Header&action=click&contentCollection=The%20Upshot&pgtype=Multimedia

Earthquake prediction

Why a 99.9% earthquake prediction is 100% controversial
by Rong-Gong Lin II, Los Angeles Times, 23 October 2015

"This report

Donnellan added that the USGS' 85% probability and her 99.9% chance still favored a big earthquake in the next three years.

"If an earthquake happens in three years, we're both right," Donnellan said.

USGS https://www.facebook.com/USGeologicalSurvey/posts/955479124498071:0 responded]

Simulating the lottery

Here’s $100. Can you win $1.5 billion at Powerball?
by Jan Schleuss, Los Angeles Times, 8 January 2016 (updated 12 Jan 2016)

By Wednesday January 13 of this year, the Powerball jackpot had reached $1.6 billion, making it the largest lottery jackpot in history. There were three winners that day. This article, published the week before as the prize was still growing, was one of many examples in the popular press intended to inform people how remote the chance of winning (1 in 292,201,338 ) really was. It includes an online tool that allows the user to select their lucky numbers, and then observe their fate over the course of 50 simulated drawings, which is $100 worth of plays. Here's the message I got after one try. No jackpot, but my minor prizes were automatically invested in more tickets.

You've played the lottery 54 times over about 6 months and spent $108, but won $8. You're in the hole $100. So why not throw some more money at that problem? [The options offered are to bet $100, $1000, or your whole paycheck.]

By contrast, the New York Times tried to explain the hopelessness in prose [1] (NYT, 12 January 2016). The article lists some time-honored comparisons: the 1 in 1.19 million chance that a US resident will be hit by lightning in a year and the 1 in 12,500 chance that an amateur golfer will make a hole-in-one.

For a fresher perspective, see Ron Wasserstein's excellent piece A statistician’s view: What are your chances of winning the Powerball lottery? (thisoriginally appeared in the Huffington Post on 16 May 2013, and was updated 7 January 2016).

Followup

More than half of Powerball tickets sold this time will be duplicates
by Matt Rocheleau, Boston Globe, 13 January 2016.

This article appeared on the morning of the drawing. It noted that of the 440 million tickets had been sold the previous Saturday. This is more than enough to cover every possible number combination

Some math doodles

<math>P \left({A_1 \cup A_2}\right) = P\left({A_1}\right) + P\left({A_2}\right) -P \left({A_1 \cap A_2}\right)</math>

<math>\hat{p}(H|H)</math>

<math>\hat{p}(H|HH)</math>

Accidental insights

My collective understanding of Power Laws would fit beneath the shallow end of the long tail. Curiosity, however, easily fills the fat end. I long have been intrigued by the concept and the surprisingly common appearance of power laws in varied natural, social and organizational dynamics. But, am I just seeing a statistical novelty or is there meaning and utility in Power Law relationships? Here’s a case in point.

While carrying a pair of 10 lb. hand weights one, by chance, slipped from my grasp and fell onto a piece of ceramic tile I had left on the carpeted floor. The fractured tile was inconsequential, meant for the trash.

As I stared, slightly annoyed, at the mess, a favorite maxim of the Greek philosopher, Epictetus, came to mind: “On the occasion of every accident that befalls you, turn to yourself and ask what power you have to put it to use.” Could this array of large and small polygons form a Power Law? With curiosity piqued, I collected all the fragments and measured the area of each piece.

Piece	Sq. Inches	% of Total
1	43.25	31.9%
2	35.25	26.0%
3	23.25	17.2%
4	14.10	10.4%
5	7.10	5.2%
6	4.70	3.5%
7	3.60	2.7%
8	3.03	2.2%
9	0.66	0.5%
10	0.61	0.5%

The data and plot look like a Power Law distribution. The first plot is an exponential fit of percent total area. The second plot is same data on a log normal format. Clue: Ok, data fits a straight line. I found myself again in the shallow end of the knowledge curve. Does the data reflect a Power Law or something else, and if it does what does it reflect? What insights can I gain from this accident? Favorite maxims of Epictetus and Pasteur echoed in my head: “On the occasion of every accident that befalls you, remember to turn to yourself and inquire what power you have to turn it to use” and “Chance favors only the prepared mind.”

My “prepared” mind searched for answers, leading me down varied learning paths. Tapping the power of networks, I dropped a note to Chance News editor Bill Peterson. His quick web search surfaced a story from Nature News on research by Hans Herrmann, et. al. Shattered eggs reveal secrets of explosions. As described there, researchers have found power-law relationships for the fragments produced by shattering a pane of glass or breaking a solid object, such as a stone. Seems there is a science underpinning how things break and explode; potentially useful in Forensic reconstructions. Bill also provided a link to a vignette from CRAN describing a maximum likelihood procedure for fitting a Power Law relationship. I am now learning my way through that.

Submitted by William Montante

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