Difference between revisions of "Chance News 64"

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<b>"The Power of Lucky Charms"</b><br>
<b>"The Power of Lucky Charms"</b><br>
Several research results[http://online.wsj.com/article/SB10001424052748703648304575212361800043460.html?KEYWORDS=Carl+Bialik] about the effect of beliefs about luck on performance are summarized by Carl Bialik, who indicates that a new research report on this topic is expected in June. For a critique of Bialik's article and that June report, see [http://www.causeweb.org/wiki/chance/index.php/Chance_News_63#Lucky_charms_and_disappointing_journalism Lucky charms and disappointing journalism].  For a related online blog by Bialik, with references to even more studies, see [http://blogs.wsj.com/numbersguy/mathematicians-take-on-luck-930/ "Mathematicians Take On Luck"].<br>
Several research results[http://online.wsj.com/article/SB10001424052748703648304575212361800043460.html?KEYWORDS=Carl+Bialik] about the effect of beliefs about luck on performance are summarized by Carl Bialik, who indicates that a new research report on this topic is expected in June. For a critique of Bialik's article and that June report, see [http://www.causeweb.org/wiki/chance/index.php/Chance_News_63#Lucky_charms_and_disappointing_journalism Lucky charms and disappointing journalism] in Chance News 63.  For a related online blog by Bialik, with references to even more studies, see [http://blogs.wsj.com/numbersguy/mathematicians-take-on-luck-930/ "Mathematicians Take On Luck"].<br>
<b>“Piano stairs”</b><br>
<b>“Piano stairs”</b><br>

Revision as of 17:57, 24 May 2010


We tolerate the pathologies of quantification — a dry, abstract, mechanical type of knowledge — because the results are so powerful. Numbering things allows tests, comparisons, experiments. Numbers make problems less resonant emotionally but more tractable intellectually. In science, in business and in the more reasonable sectors of government, numbers have won fair and square.
--Gary Wolf

Writing in The data-driven life, New York Times, 26 April 2010

Submitted by Bill Peterson

The skepticism that people like Gregg [US Senator from NH] apply to statistics, if applied to other sciences, would get them lumped with the anti-vaccinationists and the homeopaths.
--Jordan Ellenberg

Writing in The census will be wrong. We could fix it. Washington Post, 1 May 2010
(This article was recommended by Laura Chihara on the Isolated Statisticians list.)

In the world of cancer research, there is something called a Kaplan-Meier curve, which tracks the health of patients in the trial of an experimental drug. In its simplest version, it consists of two lines. The first follows the patients in the “control arm,” the second the patients in the “treatment arm.” …. Seven years ago … a team presented the results of a colorectal-cancer drug trial at the annual meeting of the American Society of Clinical Oncology …. The lead … researcher took the audience through one slide after another … laying out the design and scope of the study, until he came to the crucial moment: the Kaplan-Meier. At that point, what he said became irrelevant. The members of the audience saw daylight between the two lines, for a patient population in which that almost never happened, and they leaped to their feet and gave him an ovation. Every drug researcher in the world dreams of standing in front of thousands of people at ASCO and clicking on a Kaplan-Meier like that.
--Malcolm Gladwell

Writing in “The Treatment”, The New Yorker, May 17, 2010 (Full text may require subscription.)

See a Vanderbilt PowerPoint[1] addressing the purpose and method of the Kaplan-Meier method/chart of survival analysis.

Submitted by Margaret Cibes


Pitching is 80% of the game. The other half is hitting and fielding.
--former Yankee Mickey Rivers

Quoted in “Is Greinke the Unluckiest Pitcher Ever?” The Wall Street Journal, May 5, 2010

See more great quotes online at "Mickey Rivers' Words of Wisdom About Baseball".

Submitted by Margaret Cibes

Odds are, it’s wrong--Part II

An entry in Chance News 63 presented a Science News article by Tom Siegfried. The article, which focuses on statistics used in the medical field, may be found here and is worth some elaboration; be sure to read the comments reacting to what Siegfried writes. There you will find mention of circumcision, condoms, defense of statistics in medicine, praise for the author, condemnation of the author--and somehow, reference to Scott Reuben, who faked data for Pfizer and Merck (see Serious medical fraud in Chance News 45).

Siegfried’s main contention is that despite its prevalence in the medical sphere (and dominance elsewhere as well), Fisher’s p-value approach is inadequate and misleading at best. Because of this “p-value mania,” Siegfried quotes two researchers who claim “that in modern [medical] research, false findings may be the majority or even the vast majority of published research claims,” and “There are more false claims made in the medical literature than anybody appreciates,” respectively.

Criticism of p-value is hardly new. Put “criticism of p-value” into a browser and you will get 4,520,000 hits, many of which are more informative than Siegfried’s article. Try The P-value, devalued from the International Journal of Epidemiology as an example.


1. To see why critics of p-value say it is the wrong-way round, consider Prob ( brown eyes | Costa Rican) and Prob (Costa Rican | brown eyes). Compare with Prob (data | Null Hypothesis is true) and Prob (Null Hypothesis is true | data). For an interesting illustration of the difference between these conditional probabilities regarding the O.J. Simpson murder case see Steven Strogatz’s NYT article (25 April 2010).

2. Critics of p-value say that the above #1 is not strong enough of a criticism because p-value deals not with “data” that actually occurred but with “data at least this extreme.” Why is this a potent criticism?

3. Siegfried rightfully refers to “randomized, controlled clinical trials that test drugs for their ability to cure or their power to harm” as the “gold standard” for medical research. “Such trials assign patients at random to receive either the substance being tested or a placebo.” However, see Judson’s NYT article, Enhancing the Placebo (3 May 2010), which discusses how non-placebo a placebo can be. What does this do to clinical trials and the gold standard?

4. Siegfried suggests that Bayesian inference is preferable to the frequentist p-value approach of Fisher. If this is so, why is it that p-value approach is so dominant, long after Fisher himself died?

Submitted by Paul Alper

Health insurers finagling fees?

“For WellPoint, Math Error Spurs More Scrutiny”
by Avery Johnson, The Wall Street Journal, May 5, 2010

The health insurer WellPoint, an affiliate of Anthem Blue Cross, has decided to withdraw its request for up to a 39% price increase on individual plans in California.

The decision followed an actuarial consultant’s report about math errors in the company’s calculations. Alleged mistakes included overestimating future medical costs and double-counting the effect of aging on its policyholders.

The overestimation is thought to be related to a new requirement that health insurers spend “80% of their premium revenues on healthcare for plans that cover individuals and small businesses, and 85% for policies with large employers.”[2]

Health and Human Services Secretary Kathleen Sebelius has asked a nation-wide review of the health-related data on which costs are based, and she noted that $250 million has been allocated to states for that purpose.

Submitted by Margaret Cibes

Girls becoming less careful drivers

“Do Girls Speed More Than Boys?”
by Joseph B. White and Anjali Athavaley, The Wall Street Journal, May 5, 2010

Allstate Foundation has sponsored a survey that found that young women are not necessarily more responsible than young men – at least in their driving habits. An Allstate spokesman stated, “It would be fair to say the gap is closing,” although “teenage girls continue to be a better risk than boys.”

The data came from online interviews with 1,063 teens across the country in May 2009. About half of the girls felt that they are more likely to drive 10 mph over the speed limit or to phone/text while driving, compared to fewer than 40% of boys for each activity.

State Farm, the nation’s largest insurance company, charges 40% more for teenage boys than girls, down from a 1985 gap of 61%. While the company is raising the rates for teenage female drivers, it says that it is raising them based on claims experience and other factors, not these survey results.

For the current report, see “Shifting Teen Attitudes: 2009 State of Teen Driving”. For 2005 report, see “Chronic - A Report on the State of Teen Driving”. Unfortunately, neither the questionnaires, nor any raw data, appears to be available online.


1. What additional information about the survey would you like to know in order to draw any conclusion about the driving habits of all teenage girls and boys across the country?

2. Do you believe that self-reporting by teenagers, in general is reliable? Would you expect a difference in relying on teen boys’ versus teen girls’ responses?

3. In the article, Progressive Direct quoted 6-month premiums for a boy and a girl in identical situations, including one speeding ticket apiece in the last 3 years, at $2,938 and $2,627, respectively. By what percent does the boy’s Progressive premium exceed the girl’s Progressive premium? How does it compare with Allstate’s 40% figure? Can you think of any reason(s) for the reported disparity?

4. The article referred to girls as becoming more “aggressive” drivers. If this is true, can you think of any reason(s) for this?

Submitted by Margaret Cibes

Black swan author linked to black swan event

“Did a Big Bet Help Trigger ‘Black Swan’ Stock Swoon?”
by Scott Patterson and Tom Lauricella, The Wall Street Journal, May 10, 2010

On May 6 the Dow Jones Industrial average fell nearly 1,000 points in less than half an hour.[3]. The decline was initially attributed to a trading error in which a Citigroup trader incorrectly keyed in a “b” instead of an “m” for an intended $16 million trade of Proctor & Gamble stock. (This was referred to as a "fat finger" trading error in another article.) It was later reported by Reuters [4] that the rumor was untrue.

Apparently one of the key factors in the May 6 stock-market “collapse” was a large trade by Universa Investments during a day when “all varieties of financial markets were deeply unsettled.” Ironically, Universa is a hedge fund advised by the author of The Black Swan: The Impact of the Highly Improbable.

The trade by Universa, a hedge fund advised by Nassim Taleb … led traders on the other side of the transaction … to do their own selling to offset some of the risk …. The working theory among traders and others involved in the exchange meltdown is that the "Black Swan"-linked fund may have contributed to a "Black Swan" moment, a rare, unforeseen event that can have devastating consequences.

Submitted by Margaret Cibes

If you take away my time for your research, you owe me ten bucks

$63,000 worth of abusive research . . . or just a really stupid waste of time? Andrew Gelman on his Statistical Modeling, Casual Inference, and Social Science blog.

Two researchers, Katherine L. Milkman of the University of Pennsylvania and Modupe N. Akinola of Columbia University, wanted to use email to find out patterns in the responsiveness of professors to a request for their time. They sent out emails to 6,300 professors asking for an appointment for help in one of two possible time frames. When the professors responded, they recorded the results and then canceled the request for the appointment. Later they sent an email explaining that the original request was part of a research study.

One of the people who received this request, Andrew Gelman, did not take kindly to being part of a research study without first getting his consent and asked on his blog for $10 compensation. Later, he softened his anger about the research.

The Chronicle of Higher Education has a story on this research and the fuss it created in the academic community, though you may need a subscription to read the full article.


1. This research involved deception. Do you feel that deception should ever be allowed in ethical research. If so, under what conditions?

2. The study did not provide informed consent prior to getting subject participation in the study. Did that make the study unethical?

3. What would be the appropriate response to a subject who protested that he/she did not wish to participate in the research?

4. Is there a different way this study could have been conducted that would have avoided this controversy?

Submitted by Steve Simon

Miscellaneous studies

“Beer and Mosquitoes”
Research based on 43 West African men and 4,300 mosquitoes concluded that “mosquitoes preferred the odor of beer drinkers to outdoor air by a margin of nearly 2 to 1.”
For a brief summary of results, see this topic[5] as one section of Jeremy Singer-Vine’s May 4 summary of current research projects, a regular feature of The Wall Street Journal. For the full May 2010 report of results, see “Beer Consumption Increases Human Attractiveness to Malaria Mosquitoes”, which includes an ethics statement, as well as methodology and statistics.

“The Falling Time Cost of College”
Research[6] based on a December 2009 study of the “academic time investment” of full-time U.S. college students for the period 1961-2003 showed a decline from 40 to 27 hours week. The report includes discussions of framing effects, representativeness, and composition effects. The authors have another December 2009 report on this topic, “Leisure College, USA”.

"The Power of Lucky Charms"
Several research results[7] about the effect of beliefs about luck on performance are summarized by Carl Bialik, who indicates that a new research report on this topic is expected in June. For a critique of Bialik's article and that June report, see Lucky charms and disappointing journalism in Chance News 63. For a related online blog by Bialik, with references to even more studies, see "Mathematicians Take On Luck".

“Piano stairs”
Research[8] showed that the redesign of a subway station’s stairs led to more people choosing the stairs than the escalator. Enjoy the YouTube video!

Submitted by Margaret Cibes