Chance News 89: Difference between revisions

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'''Discussion'''<br>
'''Discussion'''<br>
What do you think this statistic represents?  Certainly the ''Washington Post'' interpretation (see Forsooth above) is not correct.
What do you think this statistic represents?  Certainly the ''Washington Post'' interpretation (see Forsooth [http://test.causeweb.org/wiki/chance/index.php/Chance_News_89#Forsooth above]) is not correct.


Submitted by Paul Alper
Submitted by Paul Alper

Revision as of 22:24, 28 October 2012

Quotations

"To rephrase Winston Churchill: Polls are the worst form of measuring public opinion — except for all of the others."

--Humphrey Taylor, Chairman of The Harris Poll, Letter to the Editor, New York Times, 24 October 2012

Forsooth

"Picture yourself behind the wheel on a dark and shadowy night, watching the windshield wipers bat away the rain and wondering, 'What are the odds I’m going to hit a deer?' The answer would be one in 102 if you live in Virginia."

Odds of striking deer high in Maryland, Virginia, Washington Post, 25 October 2012

Thanks to Paul Alper for suggesting this story (see more below).

Simpson's paradox on Car Talk

Take Ray out to the ball game...
Car Talk Puzzler, NPR, 22 September 2012

Popeye batted .250 for before the All-Star break, while Bluto batted .300; Popeye batted .375 after the All-Star break, while Bluto batted .400. How did Popeye win his bet that he would have the better average for the season? Statistically minded listeners will quickly recognize this as an instance of Simpson's Paradox. Still, everything sounds like more fun when Tom and Ray discuss it! You can read their solution here.

A famous real-life example of Simpson's Paradox with batting averages can be found here.

Sleep and fat

Your fat needs sleep, too
by Katherine Harmon, Scientific American, 16 October 2012

As described in the article (actually the transcript from a "60-Second Health" podcast--you can also listen at the link above):

Sleep is good for you. Getting by on too little sleep increases the risk for heart disease, stroke, high blood pressure, diabetes and other illnesses. It also makes it harder to lose weight or stay slim because sleep deprivation makes you hungrier and less likely to be active during the day.

Further,

Now, research shows that sleep also affects fat cells. Our fat cells play an important role in regulating energy use and storage, including insulin processing.

The research referred to, a randomized crossover study, can be found in an article by Josiane Broussard et al. Its full title is “Impaired Insulin Signaling in Human Adipocytes After Experimental Sleep Restriction: A Randomized, Crossover Study.” Scientific American says

For the study, young, healthy, slim subjects spent four nights getting eight and a half hours of sleep and four nights getting only four and a half hours of sleep. The difference in their fat cells was startling: after sleep deprivation, the cells became 30 percent less receptive to insulin signals—a difference that is as large as that between non-diabetic and diabetic patients.

Discussion

1. The Scientific American article fails to mention the number of subjects: “1 woman, 6 men” or two more than the number of authors of the study. The lone female, “participant 6,” had four of her sixteen data points missing.

2. The entire study was carried out at one institution. Why might this be a problem?

3. An extended, positive editorial commentary in the Annals of Internal Medicine refers to Aulus Cornelius Celsus who

argued in favor of “restricted sleep” for the treatment of extra weight…it seems that Celsus may have been wrong: He should have argued in favor of “prolonged sleep” for the treatment of extra weight.

Look up who Celsus is and why his pronouncements about medical matters might be suspect. Then determine why the commentator claims that the authors “deserve commendation for a study that is a valuable [statistically sound] contribution” to the role of sleep in human health.

4. As indicated above, each of the subjects were young, healthy and slim. Why is this uniformity good statistically? For inference purposes to a larger population, why is this uniformity not so good statistically?

Submitted by Paul Alper

Sample size criticized

“Tainted Drug Passed Lab Test”
by Timothy W. Martin et al., The Wall Street Journal, October 24, 2012

A recent meningitis outbreak (24 dead, 312 sick) was linked to a Massachusetts pharmacy that had produced a steroid product which was tested by an independent lab in Oklahoma. On May 25, based on a test designed to detect fungi, the lab reported that the samples were “sterile” and contained a level of endotoxins that was well below the allowable amount.

Some experts have criticized the small sample size – 2 five-ml vials out of 6,528.

In the case of the … steroids tainted with fungi, the size of the testing sample indicated in the Oklahoma lab report—two vials—is much smaller than the standard for the USP test the lab said it was performing. Under the USP standard, for a batch of more than 6,000 vials, the lab should have tested at least 20.

A consultant stated that detection of contamination at a 95% confidence level requires testing of 18% of a batch.

Labs are apparently concerned that the strict testing standards are costly and impractical in some cases. They are calling for looser testing standards.

Only 17 states require that compounding pharmacies follow the U.S. Pharamcopeia guidelines, according to a survey conducted this year by Pharmacy Purchasing & Products, a trade publication.

Question

1. In a perfect textbook world, what sample size would you have chosen - out of a population of 6,528 vials of the proposed drug – to test contamination in this case?
2. Would you be willing to use a smaller sample if cost had been a factor in the testing? if some patients had had a pressing need for the drug?
4. Are there any conditions under which you think it might be appropriate to use a sample size of 2 with respect to testing drugs for contamination?

Submitted by Margaret Cibes

Watch out for deer

1-in-80 chance of hitting a deer here
Star Tribune (Minneapolis), 27 October 2012

We read:

Minnesota drivers have a nearly 1-in-80 chance of hitting a deer in the next year, making this the eighth-most likely state for such collisions. Minnesota actually dropped from sixth to eighth in the last year, falling behind Wisconsin, which stayed at No. 7.

The statistics come from an analysis prepared by the State Farm insurance company using Federal Highway Administration data.

South Dakota moved from third to second on the list with 1-in-68 odds. Iowa dropped from No. 2 to No. 3 with 1-in-71.9 chances. West Virginia was No. 1 with odds of 1 in 40.

Given the thousands of motorists, can the deer population really be this high?

Discussion
What do you think this statistic represents? Certainly the Washington Post interpretation (see Forsooth above) is not correct.

Submitted by Paul Alper