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An ideal process for the popularization of statistical analysis includes many steps and is far from linear. One example of what such a process might look like is shown above. The popularizer carefully interviews primary researchers, or writes thoughtfully about his or her own work; seeks out and questions authoritative secondary sources; circles back to clarify points with the original researchers; ponders the evidence; crafts a story; works both alone and with a trustworthy editor to revise and shape the piece; and only then delivers it to the public.

The process changes dynamically in response to discoveries the popularizer makes, new questions he or she uncovers, and complications that pop up along the way. A more ideal process for science writing as shown in the illustration above will likely look much messier—but it offers the promise of better results. If he feels he is surrounded by economists more exceptional and brilliant than he is, he may let their assertions stand without challenge.

Maintain checks and balances: A solid collaboration requires each side to check and balance the other side.

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The most controversial statements are the most likely to be mistaken; if such assertions go unchallenged, you will have little more than a series of press releases linked by gung-ho commentary and eye-popping headlines. Hiring a meticulous editor who can evaluate the technical arguments is another way to avoid embarrassing mistakes. Just like good science, good writing takes time. Remembering this can help hedge against the temptation to streamline arguments or narrow the pool of sources, even in the face of deadlines.

One can be an outsider within such institutions, of course. But much of his economics is mainstream. And his statistical methods are conventional which, we hasten to add, is not a bad thing at all! Often such problems have not been extensively studied or even been noticed by others, and in these cases one is hard-pressed to identify any consensus or conventional wisdom.

Chapter one of SuperFreakonomics , for instance, can be viewed either as a clear-eyed quantitative examination of the economics of prostitution, or as an unquestioning acceptance of conventional wisdom about gender roles. Use latitude responsibly: When a statistician criticizes a claim on technical grounds, he or she is declaring not that the original finding is wrong but that it has not been convincingly proven. Researchers—even economists endorsed by Steven Levitt—can make mistakes. It may be okay to overlook the occasional mistake in the pursuit of the larger goal of understanding the world.

But unquestioning trust in friends and colleagues combined with the desire to be counterintuitive appear in several cases to have undermined their work. They—and anyone who wishes to convey economics and statistics to a popular audience—just need to take the next step and avoid, in any given example, privileging one story over all other possibilities. This may require Levitt to be more skeptical of the research of his friends and colleagues, and Dubner to be more skeptical of Levitt. We encourage them to revisit these modern-day classics with a skeptical and inquiring mind. And we hope that future works in the pop-statistics genre will continue to impart a sense of the fun and importance of statistical reasoning, while more clearly recognizing the uncertainty and complexity inherent in scientific study of the world.

View the discussion thread. Skip to main content. Login Register. Freakonomics: What Went Wrong? Page 6 DOI: Illustration by Tom Dunne. But this leads to an eye-catching piece of wisdom: The fact that so many World Cup players have early birthdays, the authors write, may be bad news if you are a rabid soccer mom or dad whose child was born in the wrong month.

But keep practicing: a child conceived on this Sunday in early May would probably be born by next February, giving you a considerably better chance of watching the World Cup from the family section. Unless you are a big, big believer in astrology, it is hard to argue that someone is 50 percent better at hitting a big-league curveball simply because he is a Leo rather than a Cancer.

According to his rather conservative estimate, at least 5 of those 30 are almost certainly involved in terrorist activities. Bibliography Das Gupta, M.

Short Essay Questions

Population and Development Review — DiNardo, J. Freakonomics: Scholarship in the service of storytelling. American Law and Economics Review — Dubner, S. A star is made: The birth-month soccer anomaly.

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  • The search for million missing women. Slate, May Kahneman, D. Judgment under uncertainty: Heuristics and biases. Science — Levitt, S.


    An academic does the right thing. Freakonomics blog , May Comment on Raymond T. New York: William Morrow. Oster, E. Hepatitis B and the case of the missing women.


    Journal of Political Economy — Pierrehumbert, R. An open letter to Steve Levitt. Most other cheating brought to his attention was ignored, which frustrated most TAs to no end. Since I teach graduate courses, it's a little different.

    Essay Ssmple: Freakonomics Summary

    Yes, they still cheat, but it's more like a liberal use of Control C, Control V, sans citation. Only once have I encountered a paper completely lifted. Turnitin picked it right up and the student admitted it right away. What surprised me was how he stressed that this act did NOT reflect on his integrity and character. First time offender, according to the university, and he had a previous master's degree from the same institution.

    As a visiting professor, I was a little hesitant about reporting him, but I would not be able to sleep at night with a clear conscious and in my own grad program, I would have been dismissed if I had done something that egregious. But as Daniel states, it's a lot of work and it cost me hours of time during finals week to sort this out. Perhaps you shouldn't give multiple-choice exams that are easy for people to cheat on? Don't complain that your house gets robbed if you leave your front door open. Free response questions that require students to show their work or significant amounts of writing are much much harder for students to cheat on.

    Moreover it is completely possible to design exams that allow students to come prepared with "cheat sheets" or open books. After all, classes should be teaching critical thinking skills, not rote memorization. I had one professor who would give "open everything" tests although no internet and no collaboration. He said that he conducted an analysis of that method with traditional ones and determined that he could achieve equivalent assessment while offering more challenging questions and generating less student stress.

    Infinitesimal does not mean not possible. Wouldn't the number of identical answers go up the better the grade? Were the wrong answers identical? Report them. Yes, it may take time, might not work, and may result in some damaged teacher-student relationships - but if they DID cheat, they need to face the consequences of their actions.

    I've seen too many students escape unscathed from these kinds of behaviours - other students don't want to 'rat' them out, professors turn a blind eye. What happens as a result? Undeserving students receive top marks while students who actually put effort into studying and worked honestly for their grades get knocked down. Furthermore, cheating students who don't get caught will probably repeat it again - on their next exam or later on once they enter the workforce. Even if the students aren't "convicted", the accusation and defending process alone may be enough to deter them from making similar ill judgements in the future.

    What to Do With Cheating Students? - Freakonomics Freakonomics

    Are the odds so odd if the distribution of answers is not random? I teach English at a large state university. The process for reporting plagiarism is incredibly onerous and adds a significant burden of time to the faculty's grading load. The incentive to such a process results in ignoring the cheaters although I can't stomach doing so; I always report plagiarism.