group of nondescript people standing in a crowd with a few special-looking outliers in the mix

Outliers: The Story of Success

by Malcolm Gladwell

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What is the thesis of the introduction in Outliers: The Story of Success?

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Gladwell states his thesis in the first chapter of Outliers. He says that so-called "outliers" are "the beneficiaries of hidden advantages and extraordinary opportunities and cultural legacies that allow them to learn and work hard and make sense of the world in ways others cannot." This runs counter to an assumption we make as a society—that highly successful people got that way through hard work or genius alone. In reality, hard work and genius are simply not enough. Gladwell does not dismiss either of these factors. In fact, he claims that great musicians, athletes, and so on became that way through 10,000 hours of work. But they also benefited from other factors beyond their control. Many were born into fortuitous circumstances. Others lived in societies and communities that were culturally supportive of their efforts. Still others had families that were able to support their efforts financially. The point is that they weren't born geniuses, and there are many hurdles that did not exist for them that others had to face. As Gladwell says, "no one ever makes it alone."

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The thesis in the Introduction is that one has to look beyond an individual to a person's community to understand the functioning of that individual. In the Introduction, Gladwell writes about a town in Pennsylvania called Roseto that was founded in the late 1800s by Italians from a town of the same name. A doctor named Stewart Wolf studied the town because it was an outlier in terms of health. No one in the town under 55 died of heart disease, and the rate of heart disease for men over 65 was half the national average. In addition, suicide and addiction were unknown in the town. The death rate overall was 30-35% lower than what the researchers expected (page 7). After looking at several variables that might explain why the health statistics of the town made it an outlier, Wolf determined that it was because the town had a close social network. Many generations lived together, and the town had an egalitarian spirit and many civic organizations. In other words, the answer to why individuals lived so long could be found in the community around them. Gladwell's intent in Outliers is to explain why individuals who achieve success do so by looking at the communities around them. 

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Outliers: The Story of Success is popular nonfiction book written in 2008 by Canadian journalist Malcolm Gladwell. It attempts to explain people who have been extraordinarily successful, or ones who might be what statisticians call "outliers."

The statistical definition of an outlier found in the National Institute of Standards and Technology Engineering Statistics Handbook is:

An outlier is an observation that lies an abnormal distance from other values in a random sample from a population. ... This definition leaves it up to the analyst (or a consensus process) to decide what will be considered abnormal. Before abnormal observations can be singled out, it is necessary to characterize normal observations.

In statistics, outliers are often discarded from data sets. For example, if one is surveying age distributions in humans, and you have 2 or 3 people reported as over 300 years old, but the rest of the ages congregate between 0 one 115, the odds are that the numbers over 300 are errors in data entry or people trolling the survey.

Gladwell, however, sees apparent "outliers" or people who are extraordinarily successful as a product of a combination of hidden advantages and hard work. The thesis he states in his introduction is that apparent "outliers," such as successful athletes and entrepreneurs, are not the product of some mysterious innate genius but rather a combination of of situational advantage (such as being born at a certain time of year or in a certain period of history) and hard work. In other words, his "outliers" only appear to be statistical outliers but instead are actually simply the far end of what statisticians call a "normal distribution." This means that rather than their being inexplicable, they actually provide models that ordinary people can emulate.

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