THE SIGNAL AND THE NOISE: WHY SO MANY PREDICTIONS FAIL--BUT SOME DONT PDF, EPUB, EBOOK Nate Silver | 560 pages | 03 Feb 2015 | Penguin Books | 9780143125082 | English | United States The Signal and the Noise: Why So Many Predictions Fail—But Some Don't by Nate Silver Please note that the tricks or techniques listed in this pdf are either fictional or claimed to work by its creator. We do not guarantee that these techniques will work for you. Some of the techniques listed in The Signal and the Noise: Why So Many Predictions Fail - But Some Dont may require a sound knowledge of Hypnosis, users are advised to either leave those sections or must have a basic understanding of the subject before practicing them. DMCA and Copyright : The book is not hosted on our servers, to remove the file please contact the source url. If you see a Google Drive link instead of source url, means that the file witch you will get after approval is just a summary of original book or the file has been already removed. Loved each and every part of this book. I will definitely recommend this book to non fiction, science lovers. Your Rating:. Your Comment:. As a devotee of , website and especially podcasts, I was looking forward to this book. I wanted to love it. It was enjoyable, certainly, and I learned a few things. But after opening the door, it Nate Silver. He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the election. Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Most predictions fail, often at great cost to society, because most of us have a poor understanding of probability and uncertainty. Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. In keeping with his own aim to seek truth from data, Silver visits the most successful forecasters in a range of areas, from hurricanes to baseball to global pandemics, from the poker table to the stock market, from Capitol Hill to the NBA. The Signal and the Noise: Why So Many Predictions Fail-but Some Don't - Nate Silver - Google книги What patterns have they unraveled? And are their forecasts really right? He explores unanticipated commonalities and exposes unexpected juxtapositions. And sometimes, it is not so much how good a prediction is in an absolute sense that matters but how good it is relative to the competition. In other cases, prediction is still a very rudimentary—and dangerous—science. Silver observes that the most accurate forecasters tend to have a superior command of probability, and they tend to be both humble and hardworking. They distinguish the predictable from the unpredictable, and they notice a thousand little details that lead them closer to the truth. Because of their appreciation of probability, they can distinguish the signal from the noise. Four stars, without hesitation. The problem is that some chapters — including baseball, terrorists, and the last several — were dull. Either too long or too scattered or just not interesting. Again, this was the unanimous opinion among my group. Nate Silver is a wunderkind polymath, who has scored resounding successes in statistical applications to baseball, poker, and, most recently and most impressively, politics. He emphasizes that huge bunches of data are the tools needed for predictions and that there are huge bunches of data out there. He calmly points out that some things are predictable and are predicted, using various methods with resultant various success. Some things that are predictable are not predicted accurately, exactly because the wrong tools or approaches are used. He equally argues that some things are not predictable, and when predicted, have, predictably, low success. Poor predictors often share the characteristics of ignorance of facts, inappropriate application of basic probability analyses, and, especially, overconfidence. Forecasts are made more inaccurate by overfitting — confusing noise for signal. His grasp of applied math and statistics is refreshing. His application — although, perhaps not the explanation - of Bayes theorem is lucid. His writing style is casual, more impressive considering the subject material. As has been noted by others, the number of typographical errors is unacceptable. An even greater editorial error is letting the author ramble on again, in some chapters. Liberal use of both a sharp red pencil and an X-Acto knife would have improved this book. So, overall, I really liked some parts. This is why I gave the book a 4-star review. Most of my book group ended up awarding only 3-stars. But, overall, after a few strong opening innings, the precision of text and purpose waned. View all 15 comments. Jan 01, Ted rated it it was amazing Shelves: math , americana. Presidential elections. I was following the writing on the site right up to the night of the election. And on election day, the article which pointed out early signs that Hillary could be in trouble was so accurate that I had given up for her before 10 pm that evening. And, despite any negative impressions I may leave below about any issues I previously had with Silver's writing, or his style, the last few years, in which he's developed his own web site, together with the interactions he's had will the commenters and other statisticians that he's hired, have made his writing a model of clearness and conciseness. He also nowadays is very careful to refrain from making rash statements about probabilities, usually listing many reasons why the "odds" being quoted could be risky bets. Anyway - before Silver's election triumphs he was known to a less wide, but no less fervid, audience as a sabermetrician who, starting in , contributed predicted statistical ranges of performance for major league baseball players to the Baseball Prospectus. In The Signal and the Noise , Silver discusses issues related to these foundations of his reputation in the second and third chapters. On balance I found the book, in terms of insights offered and simple interest, much closer to the political chapter than the baseball chapter — thus the high rating. This impressed me as an attempt possibly at the urging of an editor? To be fair, Silver does have a habit of putting comments in addition to source information in his footnotes. Where I believe he often errs is in not needing a source for a statement that is pretty non-controversial; in these cases the comment could just be inserted into the text and the footnote dispensed with. But Big Data is only briefly mentioned in the book, and is brought up again in the Conclusion in a correspondingly unenlightening manner. The difficulty in handling large amounts of data is separating the signal from the noise. The theme, expressed in this manner, is handled more or less brilliantly throughout. Once past the Introduction, the book immediately improved. Silver seemed to quickly find his comfort level in treating one area after another in which we attempt to make predictions, with varying success. The great majority of the chapters I found very interesting. Silver writes well, and can clearly get across his points. He shows convincingly I think how these fields differ from one another, and how the problems they have with making successful predictions and forecasts vary from field to field, depending on a variety of elements. I approached the chapter on climate prediction with some trepidation, wondering if Silver was going to somehow take the position that it was all baloney. So he feels there is a case to be made for some skepticism regarding the accuracy of the models, and thus of the forecasts being produced by the models. Most of us realize that because of the catastrophic consequences of these very unlikely events, buying insurance is rational. That is his interest in, and application of, Bayesian reasoning or inference. Silver is quite obviously much taken with this, and he does a good job in my opinion of explaining it. In almost every chapter following this he refers to the way that Bayesian reasoning can be used to strengthen forecasting and to overcome some of the difficulties of predicting in that area. View all 13 comments. Apr 18, David rated it it was amazing Shelves: economics , geology , science , environment , mathematics , meteorology. This is a fantastic book about predictions. I enjoyed every page. The book is filled to the brim with diagrams and charts that help get the points across. The book is divided into two parts. The first part is an examination of all the ways that predictions go wrong. The second part is about how applying Bayes Theorem can make predictions go right. The book focuses on predictions in a wide variety of topics; economics, the stock market, politics, baseball, basketball, weather, climate, earthquakes This is a fantastic book about predictions. The book focuses on predictions in a wide variety of topics; economics, the stock market, politics, baseball, basketball, weather, climate, earthquakes, chess, epidemics, poker, and terrorism! Each topic is covered lucidly, in sufficient detail, so that the reader gets a good grasp of the problems and issues for predictions. There are so many fascinating insights, I can only try to convey a few. At the present time, it is impossible to predict earthquakes, that is, to state ahead of time when and where a certain magnitude earthquake will occur. But it is possible to forecast earthquakes in a probabilistic sense, using a power law.