# Chance News 32: Difference between revisions

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Carl Bialik writes a column called "The Numbers Guy" for the ''Wall Street Journal'' where he "examines the way numbers are used, and abuse". He also has a [http://blogs.wsj.com/numbersguy/Blog Blog] where he discusses his articles and readers comment on them. In the December 3, 2007, of the ''Wall Street Journal'' The Numbers Guy's [http://online.wsj.com/article/SB119698695198016514.html column] was titled "Is a Carl Doomed to be a C Student?, We Don't Think So". Here the Numbers Guy discussed a study purporting to show a Name-Letter-Effect that Paul Alper discussed [http://chance.dartmouth.edu/chancewiki/index.php/Chance_News_31#Name-Letter-Effect here] in Chance News 31. As the Numbers Guy's title suggests, he shares Alper's skepticism of the results of the study. | Carl Bialik writes a column called "The Numbers Guy" for the ''Wall Street Journal'' where he "examines the way numbers are used, and abuse". He also has a [http://blogs.wsj.com/numbersguy/Blog Blog] where he discusses his articles and readers comment on them. In the December 3, 2007, of the ''Wall Street Journal'' The Numbers Guy's [http://online.wsj.com/article/SB119698695198016514.html column] was titled "Is a Carl Doomed to be a C Student?, We Don't Think So". Here the Numbers Guy discussed a study purporting to show a Name-Letter-Effect that Paul Alper discussed [http://chance.dartmouth.edu/chancewiki/index.php/Chance_News_31#Name-Letter-Effect here] in Chance News 31. As the Numbers Guy's title suggests, he shares Alper's skepticism of the results of the study. | ||

Bialik also has a discussion of the media's used of the phrase “statistical ties” or “statistical dead heats” which have been used in The Wall Street Journal, The New York | Bialik also has a discussion of the media's used of the phrase “statistical ties” or “statistical dead heats” which have been used in The Wall Street Journal, The New York Times, CNN, and other media in reporting on the Republican and Democratic contests. He comments that statisticians do not like these terms and explain why. | ||

===DISCUSSION=== | ===DISCUSSION=== | ||

(1) What do you think the the reporters mean by the expressions statistical ties and statistical | (1) What do you think the the reporters mean by the expressions statistical ties and statistical | ||

dead heats mean? | dead heats mean? | ||

## Revision as of 23:15, 9 December 2007

## Quotation

You can prove any silly hypothesis by running a statistical test on tons of data.

Jim Albert

The Numbers Guy

Wall Street Journal. 7 December, 2007

## Forsooth

The following Forsooths are from the Dec 2007 issue of RSS NEWS.

The methodology behind the ICS survey is flawed. There were only 2000 respondents, a small number for any statistical survey, who were asked to nominate which firms of services they used and how that rated them.

The Times

22 Octobeer 2007

Presenter:

'In statistics, in data which are binomially distributed, individual values may be placed in one of two mutually exclusive categories such that the sum of the probabilities of occurring in the categories is what value?'

Answer given: 'Unity'

Presenter:

'No, it's one, or a hundred percent'

University ChallengeBBC2

22 October 2007

This Forsooth was suggested by Paul Alper

The fact is, analysts say, that for all that it has a secular constitution, Turkey remains a relatively conservative country. The word atheist has only recently appeared in Turkish, but "godless" still remains an insult here. "Only 2% of the people we interviewed said they didn't believe in God", says Ali Carkoglu, co-author of a 2006 study of religious attitudes.

"Given that we had a 2% margin of error that could mean nobody", he added. "In any case it takes considerable courage for a Turk to admit to a stranger that they are atheists."

*The London Independent*

30 November 2007

In Chance News 31 we had the forsooth:

Of Italy's 151 Series A players, 52 are non-white, with Inter fielding, 19,

Juventus 12, AC Milan 13, AS Roma 12 and Udinese 10. Messina has eight.The Times

30 November 2005

Marcello Pagano comments that in Italy there is a saying: L'aritmetica non è un'opinione

## Math too hard for this lottery

John Haigh, author of one of our favorite chance books:"Taking Chances: winning with probability" suggested this item.

The following story appeared in the December issue of the London Mathematical Society Newsletter.

From the Manchester Evening News 3 Nov 2007

A Lottery scratchcard – the Cool Cash game – was taken out of shops yesterday after some players failed to grasp whether or not they had won.

To qualify for a prize, users had to scratch away a window to reveal a temperature lower than the figure displayed on each card. As the game had a winter theme, the temperature was usually below freezing. But the concept of comparing negative numbers proved too difficult for some. Camelot received dozens of complaints on the first day from players who could not understand how, for example, –5 is higher than –6.

Tina Farrell, from Levenshulme, called Camelot after failing to win with several cards. The 23-year-old, who said she had left school without a maths GCSE, said: "On one of my cards it said I had to find temperatures lower than –8. The numbers I uncovered were –6 and –7 so I thought I had won, and so did the woman in the shop. But when she scanned the card the machine said I hadn't. I phoned Camelot and they fobbed me off with some story that –6 is higher – not lower – than –8 but I’m not having it. I think Camelot are giving people the wrong impression – the card doesn’t say to look for a colder or warmer temperature, it says to look for a higher or lower number. Six is a lower number than 8. Imagine how many people have been misled."

A Camelot spokeswoman said the game was withdrawn after reports that some players had not understood the concept.

Submitted by Laurie Snell

## David Kendall 1918-2007

The London Mathematical December Newsletter also reported the sad news that David Kendall, one of this centuries greatest probabilist, has died at age 90. You can read about his contributions in the Times of London's Obituary .

## What do economists know that lawyers don't

Does Death Penalty Save Lives? A New Debate Adam Liptak, The New York Times, November 18, 2007.

Recently a dozen or so studies by economists have shown that the death penalty has a deterrent effect. In one study, each execution was estimated to save five lives.

To economists, it is obvious that if the cost of an activity rises, the amount of the activity will drop.

The legal profession is not so sure.

But not everyone agrees that potential murderers know enough or can think clearly enough to make rational calculations. And the chances of being caught, convicted, sentenced to death and executed are in any event quite remote. Only about one in 300 homicides results in an execution.

The modles used by economists are typically a multiple linear regression model with adjustment for key covariates.

The studies try to explain changes in the murder rate over time, asking whether the use of the death penalty made a difference. They look at the experiences of states or counties, gauging whether executions at a given time seemed to affect the murder rate that year, the year after or at some other later time. And they try to remove the influence of broader social trends like the crime rate generally, the effectiveness of the criminal justice system, economic conditions and demographic changes.

Can you use a regression model here? The answers vary.

Critics say the larger factors are impossible to disentangle from whatever effects executions may have. They add that the new studies’ conclusions are skewed by data from a few anomalous jurisdictions, notably Texas, and by a failure to distinguish among various kinds of homicide.

The recent studies are, some independent observers say, of good quality, given the limitations of the available data. “These are sophisticated econometricians who know how to do multiple regression analysis at a pretty high level,” Professor Weisberg of Stanford said. The economics studies are, moreover, typically published in peer-reviewed journals, while critiques tend to appear in law reviews edited by students. The available data is nevertheless thin, mostly because there are so few executions.

There is additional commentary about death penalty deterrence on the Freakonomics blog.

### Questions

1. The bulk of executions in the United States have occurred in Texas. Why might this clustering of executions raise difficulty for the regression model?

2. Can a regression model remove the effect of all of the potential confounding variables that also influence crime rate? Can they remove enough of the effect of confounding to provide a plausible answer?

3. At the end of the Times article, a researcher speculates on how random assignment could allow a caerful study of the deterrence effect of the death penalty. What would a randomized study of death penalty effects look like? What are some of the practical and ethical barriers to such a study?

Submitted by Steve Simon

## The Numbers Guy

Carl Bialik writes a column called "The Numbers Guy" for the *Wall Street Journal* where he "examines the way numbers are used, and abuse". He also has a Blog where he discusses his articles and readers comment on them. In the December 3, 2007, of the *Wall Street Journal* The Numbers Guy's column was titled "Is a Carl Doomed to be a C Student?, We Don't Think So". Here the Numbers Guy discussed a study purporting to show a Name-Letter-Effect that Paul Alper discussed here in Chance News 31. As the Numbers Guy's title suggests, he shares Alper's skepticism of the results of the study.

Bialik also has a discussion of the media's used of the phrase “statistical ties” or “statistical dead heats” which have been used in The Wall Street Journal, The New York Times, CNN, and other media in reporting on the Republican and Democratic contests. He comments that statisticians do not like these terms and explain why.

### DISCUSSION

(1) What do you think the the reporters mean by the expressions statistical ties and statistical dead heats mean?

(2) Why do you think Statisticians do not like these terms?

Submitted by Laurie Snell