Chance News 50
Swine flu pandemonium III
"Fourth Connecticut Resident With Swine Flu Dies" by Arielle Levin Becker, The Hartford Courant, June 19, 2009
See Chance News 49  for two earlier stories about the second and third cases of swine flu in Connecticut.
A fourth Connecticut death has been "linked" to swine flu.
The person was between 40 and 49 years old and had underlying medical conditions that increased the risk for serious illness from flu, the state Department of Public health said.
To date there have been 767 confirmed cases of swine flu, 28 of the cases had been hospitalized, and 19 of the hospitalized were from the largest cities. All four deaths occurred in people with other medical problems who were hospitalized at the time of death.
Here is the data to date about Connecticut deaths from swine flu:
1 death – 395 confirmed cases – June 4
2 deaths – 637 confirmed cases – June 11
3 deaths – 693 confirmed cases – June 15
4 deaths – 767 confirmed cases – June 17
1. Would you advise Connecticut residents to move out of large cities to avoid swine flu? Could the victims have been identified as being from the largest cities because they died in large city hospitals, as opposed to having resided in large cities?
2. Would you advise Connecticut residents with swine flu to avoid hospitals?
Submitted by Margaret Cibes
Role of luck in golf
"Winning a Major May Just Be a Matter of Luck", by Jason Turbow, The Wall Street Journal, June 19, 2009
Using data from every PGA leadership board from 1998 to 2001, two business professors, from University of North Carolina and Dartmouth, have used "cubic spline functions" to try to explain the role of luck in professional golf.
"If being on the leaderboard at the end of a tournament was due entirely to skill, we would see the same names every week," said [the Dartmouth researcher]."
Their model aims to predict an individual's score in a tournament based on an estimate of the person's "intrinsic skill level independent of variables like course difficulty and variations over time." A golfer with a higher tournament score than predicted was considered to have had good luck; one with a lower score was considered to have had bad luck.
[I]n all the events the researchers studied, Mr. Woods was the only golfer to win a tournament despite suffering from negative luck.
The brief article includes a table  of expected score, actual score, and "luck factor" for players Tiger Woods, Ernie Els, Vijay Singh, Phil Mickelson, Sergio Garcia, and Jim Furyk, in the 2000 U.S. Open.
Submitted by Margaret Cibes
Baseball: More education, more victories?
"Who Has the Brainiest Team in Baseball?", by Jason Turbow, The Wall Street Journal, June 16, 2009
The author studied "30 team media guides" to try to determine whether there is "a correlation between education and victories" in professional baseball. He compared team standings with players' and managers' undergraduate degrees. He found that only about two dozen major league players or managers had undergraduate degrees.
[T]hree "All-Brains" division leaders -- Oakland, Arizona and Washington -- are in last place in real life, while Texas and the Dodgers were last in their divisions in smarts but first in the standings.
Two bloggers  wrote:
(1) "[A]re these results really surprising? The best teams are the best teams because they have more good players than the other teams. Good players are likely to have been A) so talented at baseball as to have little incentive to work hard at school and B) so dedicated to the sport that academics would have suffered. If you're a marginal major league talent like Breslow, it makes sense to get a degree with better earnings potential. Not so for the Alex Rodriguezes [sic] and Barry Bondses [sic] of the world."
(2) "How about instead of looking at university experience, check out something that almost every player (from the U.S., at least) would have: SAT scores. Surely there is the occasional ballplayer with a stratospheric score who still opts for baseball over college."
Submitted by Margaret Cibes
Keeping up with the Joneses by lowering utility bills
“Greening With Envy”, by Bonnie Tsui, The Atlantic, August 2009
Robert Cialdini, a social psychologist at Arizona State University, tested 4 different hotel reuse-towels signs to test how well guests responded:
The first sign had the traditional message, asking guests to “do it for the environment.” The second asked guests to “cooperate with the hotel” and “be our partner in this cause” (12 percent less effective than the first). The third stated that the majority of guests in the hotel reused towels at least once during their stay (18 percent more effective). The last message was even more specific: it said that the majority of guests “in this room” had reused their towels. It produced a 33 percent increase in response behavior over the traditional message.
As the chief scientist for Positive Energy, Cialdini is now applying what he learned to encouraging utility consumers to conserve energy by letting them know how much energy they use relative to their neighbors. Based on his software’s analysis of a neighborhood’s energy usage, a utility company can send monthly bills to consumers with information about how a particular consumer’s usage compared to that of his/her neighbors. For example, a consumer who used “58 percent less electricity” might receive a row of smiley faces, while one who used “39 percent more” might receive no smiley faces, a notice that it cost him/her $741 extra, and tips for improvement.
people who received personalized “compared with your neighbors” data on their statements reduced their energy use by more than 2 percent over the course of a year. … [W]ith the pilot sample of 35,000 homes, it’s the equivalent of taking 700 homes off the grid. And the cost to the utility is minor: for every dollar a utility spends on a solar power plant, it produces 3 to 4 kilowatt-hours; for every dollar a utility spends on the energy reports, it saves 10 times that.
Submitted by Margaret Cibes
A Probability puzzle
Find three random variables X, Y, Z, each uniformly distributed on [0, 1], such that their sum is constant. (Since each random variable has expectation 1 the sum must in fact be 3.)
To better understand this puzzle, consider the case of two random variables X and Y with X a random choice on 0 to 1 and Y = 1- X. Then the sum of X and Y is the constant 1.
Comment: This puzzle is due to Thomas Colhurst
Submitted by Laurie Snell
The Ted talks
At the Ted talks website we read:
Each year, the world's leading thinkers and doers gather in for an event many describe as the highlight of their year. Attendees have called it "The ultimate brain spa," "Davos for optimists" and "A four-day journey into the future, in the company of those creating it." This event is called TED, and it's truly a conference like no other.
"It was incredible." Malcolm Gladwell "A mind-opening experience." Amy Tan "One of the highlights of my entire life." Billy Graham "I've never experienced anything remotely like it." Jeffrey Katzenberg
"The combined IQ of the attendees is incredible." Bill Gates
Of course we are interested in statstics or probability talks. A statistic talk was given by Hans Rosling. We read:
Even the most worldly and well-traveled among us will have their perspectives shifted by Hans Rosling. A professor of global health at Sweden’s Karolinska Institute, his current work focuses on dispelling common myths about the so-called developing world, which (he points out) is no longer worlds away from the west. In fact, most of the third world is on the same trajectory toward health and prosperity, and many countries are moving twice as fast as the west did.
What sets Rosling apart isn’t just his apt observations of broad social and economic trends, but the stunning way he presents them. Guaranteed: You’ve never seen data presented like this. in Rosling’s hands, data sings. Trends come to life. And the big picture — usually hazy at best — snaps into sharp focus.
We did indeed find his talk amazing;
We found a Ted talk on probability by Peter Donnelly. About whom we read:
Oxford mathematician Peter Donnelly reveals the common mistakes humans make in interpreting statistics -- and the devastating impact these errors can have on the outcome of criminal trials.
Peter begins with a couple of jokes:
Statistans are people who like figures but do not have the personality to become accountants
How do you tell the introverted statistician from the extroverted statistician? The extroverted statistician is the one who looks at the other persons shoe.]
How do you tell the introverted statistician from the extroverted statistician? An extroverted statistician is one who looks at the other person's shoes.
Fraud in Iranian election?
The devil is in the digits
Washington Post, 20 June 2009
Bernd Beber and Alexandra Scacco
Beber and Scacco are doctoral students in political science at Columbia University. In this article they argue that certain patterns in the reported electoral totals from this month's Iranian presidential elections give strong indications of tampering. Iran's Ministry of the Interior released data for 29 provinces, and the authors examined vote totals for the four main candidates, Ahmadinejad, Mousavi, Karroubi and Mohsen Rezai. Among these 116 numbers, the authors focused on the last two digits, which they assert should be uniformly distributed. However, they report two statistical irregularities. Regarding the final digit, they write
We find too many 7s and not enough 5s in the last digit. We expect each digit (0, 1, 2, and so on) to appear at the end of 10 percent of the vote counts. But in Iran's provincial results, the digit 7 appears 17 percent of the time, and only 4 percent of the results end in the number 5. Two such departures from the average -- a spike of 17 percent or more in one digit and a drop to 4 percent or less in another -- are extremely unlikely. Fewer than four in a hundred non-fraudulent elections would produce such numbers.
Next, they considered the last two digits together, and asked how many of the pairs contain non-adjacent digits (e.g., 32 has adjacent digits while 35 has non-adjacent digits). They report that only 62% of the pairs had non-adjacent digits, compared with the 70% that would be expected for random digits.
Further background information from Pollster.com is available here.
More to follow...
Submitted by Bill Peterson, based on a posts by Nancy Boynton and others to the Isolated Statisticians mailing list.