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

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....

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.