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Naked Statistics: Stripping the Dread from the Data [Englisch] [Gebundene Ausgabe]

Charles Wheelan
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Kurzbeschreibung

5. Februar 2013
The field of statistics is rapidly transforming into a discipline that Hal Varian at Google has called "sexy". And with good reason - from batting averages and political polls to game shows and medical research - the real-world application of statistics is growing by leaps and bounds. In Naked Statistics, Charles Wheelan strips away the arcane and technical details to get at the underlying intuition that is key to understanding the power of statistical concepts. Tackling a wide-ranging set of problems, he demonstrates how statistics can be used to look at questions that are important and relevant to us today. With the trademark wit, accessibility and fun that made Naked Economics a bestseller, Wheelan brings another essential discipline to life with a one-in-a-million statistics book that you will read for pleasure.

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Naked Statistics: Stripping the Dread from the Data + Naked Economics: Undressing the Dismal Science
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Produktinformation

  • Gebundene Ausgabe: 282 Seiten
  • Verlag: Norton & Company (5. Februar 2013)
  • Sprache: Englisch
  • ISBN-10: 0393071952
  • ISBN-13: 978-0393071955
  • Größe und/oder Gewicht: 23,9 x 16,3 x 2,6 cm
  • Durchschnittliche Kundenbewertung: 4.0 von 5 Sternen  Alle Rezensionen anzeigen (1 Kundenrezension)
  • Amazon Bestseller-Rang: Nr. 79.915 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)

Mehr über den Autor

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Produktbeschreibungen

Pressestimmen

"...his [Wheelan's] style is innovative and often witty." New Scientist "...a very well-executed attack on the dread of statistics by Wheelan. He is a likeable assailant, who has employed some clever and interesting examples in his onslaught...you will be enlightened and entertained in equal measure." THE "Charles Wheelan...does something unique here: he makes statistics interesting and fun. His book strips the subject of its complexity to expose the sexy stuff underneath...The results work wonderfully." The Economist "In a world driven by data, uses - and abuses - of statistics are ever increasing. For non-specialists wanting to understand why, this book is not a bad place to start." BBC Focus

Über den Autor und weitere Mitwirkende

Charles Wheelan teaches at Dartmouth College and is the author of the internationally best-selling Naked Economics (ISBN 978 0 393 33764 8).

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0 von 1 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Sehr anregend 17. April 2013
Von HGS
Format:Kindle Edition
Sehr klare und ausgewogene Erklärung wichtiger statistischer Begriffe und Verfahren für fast Jedermann. Etwas geschwätzig. Die Beispiele beziehen sich weitgehend auf US-Verhältnisse mit oft geringer Relevanz für andere Länder. Eine kurze Zusammenfassung der methodischen Teile am Ende und nicht verteilt auf Kapitelanhänge wäre hilfreich.
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Amazon.com: 4.4 von 5 Sternen  190 Rezensionen
108 von 115 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Interesting; should entice those who think they don't like stats 14. Januar 2013
Von Anne Swan - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe|Verifizierter Kauf
Yes, there are lots of "dear reader" type comments throughout the book. Yes, the examples and references are drawn from up-to-the-minute pop culture. And, yes, if you don't know very much about statistics and probability you can learn fairly "painlessly" in this book.

One drawback: you really, really need to read the entire book from start to finish to really understand all of the concepts. This is not a reference book in which you can "jump around" or just go to the parts you have questions about.

It's like being given a prescription for antibiotics; you really need to read every chapter in the book, to "take it all." Concepts build on previous chapters, up to the final chapter. Don't stop or you will miss out!

On the other hand, this is not a book for someone who wants to quickly, at-a-glance understand probability or who wants to get a solid definition of any statistical concept, such as confidence level or regression analysis. It is not specifically a reference book.

I confess, my prejudice is for more concise information without all the "fluff." On the other hand, I work with opinion survey statistics almost every day of my worklife, so I don't need to be lured in with tales of baseball (in which I have no interest) or discussions of what's behind the doors in Let's Make a Deal. (In fact, I have never, ever seen that show.)

However, if you are in business or education or health care and don't have a complete grasp of statistics, I recommend you read this book. If you want to better understand whether you should buy a lottery ticket or buy insurance and you don't understand probability theory, I recommend this book to you. If you read media and want to have a better understanding of polls, scientific experiments, clinical trials and don't understand statistics, then I recommend this book to you.

If this book piques your interest in the topics, I suggest you next obtain a couple of the more traditional, "duller" stat books that you can use as handy references for specific concepts. Of course, if you already have that much interest in stats, you probably already have those books. Or you know where to go online to find reference materials.

There are a few tiny, tiny little things that could have been better. I think he could have included the "name" for symbols, such as sigma when he first introduced them. Also, I don't like the way he would "jump" back and forth on examples.

Overall, I recommend this book.
46 von 51 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Interesting and Useful - 9. Januar 2013
Von Loyd E. Eskildson - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe
Statistics are everywhere; the author's intent is to make them interesting while simplifying the topic. He begins by explaining the mean, how the median is less influenced by outliers, standard deviation (spread), how the weighting of index components affects results, correlation vs. causation, inflation-adjustment, specificity vs. accuracy, the importanace of using the appropriate unit of analysis (eg. people, instead of nations when analyzing the benefits of globalization), statistical vs. operational significance, and how performance data is sometimes manipulated (eg. reclassifying dropouts as something else, holding back students, not operating on the most seriously ill to reduce death rates).

One of the most interesting segments was that explaining the reasoning and high certainty of looking good on blind taste tests using those who previously preferred a competitor's offering (eg. Coke vs. Pepsi, some beers) when there's little discernible difference between the two products. Another was his simple explanation of how random occurrences such as coin flips can make one look superior at the end of a series of selecting those getting heads - when there obviously was no difference; similarly often in eg. mutual fund performance, etc. Still another - pointing out the erroneous possibilities of claiming a DNA match when done on 9 loci (a common method) - supposedly only 1 in 113 billion, vs. the reality of thousands within a single database.

Expected values are another important topic addressed - eg. point-after-touchdown expected results vs. two-point conversions; never buy a lottery ticket or expect to come out ahead (on average) buying product insurance.

Testing for disease doesn't always make sense. Assume HIV/AIDS prevalence in the population of 1:100,000, and that a test generates false positives 1:10,000. The result of extensive testing will be that only 9% of those told they may have the disease actually will have it, lots of needless upsetness and wasted time and effort. Testing at-risk populations (eg. drug users who inject) makes more sense.

Still another very interesting situation explained - the counter-intuitive 'Monty Hall Problem' from 'Let's Make A Deal' - a contesting switching doors after Monty Hall opened one of the two non-winners doubles one's odds of winning. He also explains hos a common misuse of probability helped cause the 'Great Recession' (past data is not necessarily representative of the future), and the logic behind statistical profiling.

Common regression errors - used with nonlinear relationships, correlation not the same causation, reverse causation, multicollinearity, extrapolating beyond the data, too many variables (eg. data mining) finding chance relationships. A real-life example - data showed an apparent beneficial relationship from using hormone replacement for middle-aged women; in reality this wasn't true and thousands of women died.

Bottom-Line: An excellent basic/mid-level introduction to statistical analysis.
29 von 32 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Wonderful Book on Statistics for the Non-Expert 10. Januar 2013
Von Book Fanatic - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe
This is a really good book that does exactly what it says - stripping the dread from the data. The author's purpose is to explain basic statistical concepts to the intelligent layman without too much math. In my opinion he succeeds beautifully.

He writes with quite a sense of humor and uses examples that most people should be familiar with. I really enjoyed this book but I'm interested in means, medians, standard deviations, regression analysis, etc. My wife would be bored stiff reading this book. So even though it is written for the non-expert, you have to have SOME interest in what statistics are all about or you are not going to like this book.

The first chapter is titled "What's the Point?". This chapter explains why we should all care and understand what follows in the book. Fortunately you can see about 1/2 that chapter in Amazon's excellent "Search Inside" feature which is available for this book. I highly recommend you read it. Unfortunately some of the best parts of that chapter are not available.

In any case I highly recommend this book for anyone even remotely interested in understanding statistics. It is invaluable in the modern data-driven world. Well done!
20 von 21 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen The Only Explanation of the Monty Hall Problem I Have Actually Understood 20. Januar 2013
Von takingadayoff - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe
It was worth the price of the book for this alone. All these years I have read and listened to various explanations of the Monty Hall problem, in which a contestant is given the choice of what is behind one of three doors. Behind two doors there are goats, behind one door there's a new car. The contestant chooses Door #1 and Monty Hall, the host of the game show, opens Door #2, revealing a goat. Then he asks the contestant if she wants to change her choice. The intuitive answer is that it makes no difference, but the correct answer is that she should switch. I could never understand why, but author Charles Wheelan has finally convinced me once and for all.

The rest of the book is also good, although I could do without the many sports examples, which were not enlightening since they required knowing (and caring) more about sports than I do. (What is a passer rating, anyway?)

Wheelan explains concepts clearly and tells why statistics and probability matter. So even, if like Wheelan, you never warmed to calculus, you can still exercise your math muscles and decide for yourself whether the latest poll or alarming statistic is credible or just another goat behind the door.
9 von 9 Kunden fanden die folgende Rezension hilfreich
3.0 von 5 Sternen "Statistics is like a high caliber gun, very useful in the right hands but potentially disastrous if misused" 8. September 2013
Von Neuron - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe
This book will not teach you the mathematics behind statistics. This book is about making you understand what you are doing when you are doing statistics. Thus it is a great complement to a university course where you might learn how to plug in numbers in SPSS or MATLAB and get a p-value but don't really understand the assumptions involved and the potential pitfalls that must be considered.
Though I have studied some statistics at university level this book still provided a fresh valuable perspective on many statistical issues. It also gives examples of many, often costly mistakes scientists made in the past using statistics.

The analogy I used in the title (taken from this book), really captures an important aspect of statistics. If used properly statistics can tell us if a medication, or a certain policy is effective. If used improperly, it can lead to erroneous medical advice with fatal consequences, in the literal sense.

I would recommend this book if you are taking statistics but often don't know what you are really doing or how what you are doing relates to real life issues. Alternatively, this book can also be read by people who don't know any statistics but want to understand what it is all about without having to learn to do the actual math. If you are already an advanced student in statistics and know what you are doing (and know what not to do), then this book might not be for you.
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