Quotes About Outliers

Even within the West, Americans are more extreme outliers than Europeans, and within the United States, the educated upper middle class (like my Penn sample) is the most unusual of all.

people who grow up in Western, educated, industrial, rich, and democratic (WEIRD) societies are statistical outliers on many psychological measures, including measures of moral psychology

Finally, power-law distributions have "thick tails," meaning that they have a nonnegligible number of extreme values. You will never meet a 20-foot man, or see a car driving down the freeway at 500 miles per hour. But you could conceivably come across a city of 14 million, or a book that was on the bestseller list for 10 years, or a moon crater big enough to see from the earth with the naked eye—or a war that killed 55 million people.

That's how the Law of Large Numbers works: not by balancing out what's already happened, but by diluting what's already happened with new data, until the past is so proportionally negligible that it can safely be forgotten.

It was one of almost 20 global mass extinctions in the history of complex life, a list that includes 5 cataclysmic outliers, when the planet nearly died

We should not be focusing on quick solutions. The really important concern for policymakers everywhere is to prevent disasters - that is, the outlier events that matter the most.

The inability to predict outliers implies the inability to predict the course of history

after the event you start predicting the possibility of other outliers happening locally, that is, in the process you were just surprised by, but not elsewhere. After

Outliers are increasingly unlikely. You

growth in society may not come from raising the average the Asian way, but from increasing the number of people in the "tails," that small, very small number of risk takers crazy enough to have ideas of their own

There are two possible ways to approach phenomena. The first is to rule out the extraordinary and focus on the "normal." The examiner leaves aside "outliers" and studies ordinary cases. The second approach is to consider that in order to understand a phenomenon, one needs first to consider the extremes—particularly if, like the Black Swan, they carry an extraordinary cumulative effect.

whatever they are guessing has about a 2 percent chance to fall outside their range.

Take a population of 10 people, 9 having a net worth of $ 30,000 and 1 having a net worth of $ 1,000. The average net worth is $ 27,100 and 9 out of 10 people will have above average wealth.

There have always been, and will always be, those who exist on the fringe of reason

The mean, or average, turns out to have some problems in that regard, namely, that it is prone to distortion by "outliers," which are observations that lie farther from the center.

For distributions without serious outliers, the median and the mean will be similar.

once the propagation mechanism was in place, it would have exerted selective pressure to make some outliers in the population more innovative. This is because innovations would only be valuable if they spread rapidly. In this respect, we could say mirror neurons served the same role in early hominin evolution as the Internet, Wikipedia, and blogging do today. Once the cascade was set in motion, there was no turning back from the path to humanity.

It's unfair but true: youth is attractive, curvy women are attractive, outliers who look a bit different to everybody else are attractive.

If the BDS Movement was isolated to a few tenured college outliers, that would be easy enough to handle. Unfortunately, it is not.

I suppose the suspicion is that our common past can only warrant a common future if we are willing to rid ourselves of the outliers.

sometimes it pays to model the outliers, not flatten them into averages. This isn't limited to business.

Averages are useful because many traits, behaviors, and outcomes are distributed in a bell-shaped curve, with most results clustered around the middle and a much smaller group of outliers at the high and low ends.

In fiction you're not often writing about the typical; you are interested in outliers, the points of interest. Part of it comes from feeling I was the only Asian or person of colour... another part comes from my personality: I'm an introvert, and my usual survival mode in a large group is to stand by a wall and watch everybody.

So we pour in data from the past to fuel the decision-making mechanisms created by our models, be they linear or nonlinear. But therein lies the logician's trap: past data from real life constitute a sequence of events rather than a set of independent observations, which is what the laws of probability demand.[...]It is in those outliers and imperfections that the wildness lurks.