From the bestselling author of Blink and The Tipping Point, Malcolm Gladwell's Outliers: The Story of Success overturns conventional wisdom about genius to show us what makes an ordinary person an extreme overachiever. Why do some people achieve so much more than others? Can they lie so far out of the ordinary? In this provocative and inspiring book, Malcolm Gladwell looks at everyone from rock stars to professional athletes, software billionaires to scientific geniuses, to show that the story of success is far more surprising, and far more fascinating, than we could ever have imagined. He reveals that it's as much about where we're from and what we do, as who we are - and that no one, not even a genius, ever makes it alone. Outliers will change the way you think about your own life story, and about what makes us all unique. 'Gladwell is not only a brilliant storyteller; he can see what those stories tell us, the lessons they contain' Guardian 'Malcolm Gladwell is a global phenomenon ... he has a genius for making everything he writes seem like an impossible adventure' Observer 'He is the best kind of writer - the kind who makes you feel like you're a genius, rather than he's a genius' The Times
In order to READ Online or Download Outliers ebooks in PDF, ePUB, Tuebl and Mobi format, you need to create a FREE account. We cannot guarantee that Outliers book is in the library, But if You are still not sure with the service, you can choose FREE Trial service. READ as many books as you like (Personal use).
The problem of outliers is one of the oldest in statistics, and during the last century and a half interest in it has waxed and waned several times. Currently it is once again an active research area after some years of relative neglect, and recent work has solved a number of old problems in outlier theory, and identified new ones. The major results are, however, scattered amongst many journal articles, and for some time there has been a clear need to bring them together in one place. That was the original intention of this monograph: but during execution it became clear that the existing theory of outliers was deficient in several areas, and so the monograph also contains a number of new results and conjectures. In view of the enormous volume ofliterature on the outlier problem and its cousins, no attempt has been made to make the coverage exhaustive. The material is concerned almost entirely with the use of outlier tests that are known (or may reasonably be expected) to be optimal in some way. Such topics as robust estimation are largely ignored, being covered more adequately in other sources. The numerous ad hoc statistics proposed in the early work on the grounds of intuitive appeal or computational simplicity also are not discussed in any detail.
From the New York Times bestselling author of Reconstructing Amelia comes a fast-paced teen series where one girl learns that in a world of intrigue, betrayal, and deeply buried secrets, it is vital to trust your instincts. It all starts with a text: Please, Wylie, I need your help. Wylie hasn’t heard from Cassie in over a week, not since their last fight. But that doesn’t matter. Cassie’s in trouble, so Wylie decides to do what she has done so many times before: save her best friend from herself. This time it’s different, though. Instead of telling Wylie where she is, Cassie sends cryptic clues. And instead of having Wylie come by herself, Jasper shows up saying Cassie sent him to help. Trusting the guy who sent Cassie off the rails doesn’t feel right, but Wylie has no choice but to ignore her gut instinct and go with him. But figuring out where Cassie is goes from difficult to dangerous, fast. As Wylie and Jasper head farther and farther north into the dense woods of Maine, Wylie struggles to control her growing sense that something is really wrong. What isn’t Cassie telling them? And could finding her be only the beginning? In this breakneck tale, New York Times bestselling author Kimberly McCreight brilliantly chronicles a fateful journey that begins with a single decision—and ends up changing everything.
An outlier is something or someone that lies outside of the main group that it’s a part of. In this collection of short stories, the outliers are people who don’t fit into our consensus reality. They’re anomalies, weirdos, individuals whose experiences are vastly different from the rest of us. And yet, they are us in their humanity, their emotions, and in their curiosity that asks, What if? The stories begin with a novella in which a paranormal investigator looks into a bizarre story about a secret federal law enforcement team that pursues their cases while out-of-body. It ends with the story of a First Lady who hold seances in the White House. In between are more tales of outliers, more strangeness. Included in this collection: Spinning Out, a Novella Rivereños The Unit A Very Thin, Thin Line A Gambler’s Superstition The Works Devil’s Chair Wild Card Portal
In today's hyper-connected society, understanding the mechanisms of trust is crucial. Issues of trust are critical to solving problems as diverse as corporate responsibility, global warming, and the political system. In this insightful and entertaining book, Schneier weaves together ideas from across the social and biological sciences to explain how society induces trust. He shows the unique role of trust in facilitating and stabilizing human society. He discusses why and how trust has evolved, why it works the way it does, and the ways the information society is changing everything.
A statistical technique and the necessary computer program for editing multivariate data are presented. The technique is particularly useful when large quantities of data are collected and the editing must be performed by automatic means. One task in the editing process is the identification of outliers, or observations which deviate markedly from the rest of the sample. A statistical technique, and the related computer program, for identifying the outliers in univariate data was presented in NASA TN D-5275. The current report is a multivariate analog which considers the statistical linear relationship between the variables in identifying the outliers. The program requires as inputs the number of variables, the data set, and the level of significance at which outliers are to be identified. It is assumed that the data are from a multivariate normal population and the sample size is at least two greater than the number of variables. Although the technique has been used primarily in editing biodata, the method is applicable to any multivariate data encountered in engineering and the physical sciences. An example is presented to illustrate the technique.
The problem of monitoring atmospheric radionuclides over time is investigated. Such monitoring is desirable for both natural and anthropogenic radionuclides. The statistical problem is one of testing for a time series outlier, and the problem is complicated by the fact that often several observations may be missing. In fact it may be the case that several missing observations may occur immediately prior to a data value that is to be tested as an outlier. Evans (1996) proposes an exponentially weighted moving average (EWMA) approach for detecting these outliers. The EWMA approach is one that is quite popular in practice, but it is restricted to some extent by the fact that it is based on the assumption that the autoregressive integrated moving average model, ARIMA(0,1,1), is a good fit to the data. Evans presents simulation results based on simulated radionuclide data obtained from a model that he fit to Kuwait Be7 data consisting of a sinusoidal component with long period plus an autoregressive component. One problem with Evans' approach is that false alarm rates tend to be high when the data value to be tested as an outlier is preceded by a string of missing observations. In this paper we describe several alternative approaches for outlier detection, and we compare these with the Evans method using a simulation study. In this study, outlier detection capabilities are compared in the case in which no data are missing immediately prior to the data value to be tested as an outlier as well as in the more difficult case in which several data values are missing immediately prior to this value. Our results indicate that an autoregressive-based procedure suggested here has much better control over the false alarm rates than does the Evans procedure, and it has detection capability that is comparable to and sometimes better than that obtained by the Evans approach.
The nail-bitingly tense sequel to THE OUTLIERS by New York Times bestselling author Kimberly McCreight. “Wylie, trust your instincts.? The line goes dead...