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Naked Statistics: Stripping the Dread from the Data
 
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Naked Statistics: Stripping the Dread from the Data [Format Kindle]

Charles Wheelan
5.0 étoiles sur 5  Voir tous les commentaires (1 commentaire client)

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Descriptions du produit

Présentation de l'éditeur

“Brilliant, funny . . . the best math teacher you never had.”—San Francisco Chronicle


Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called “sexy.” From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.

For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions.


And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.


Détails sur le produit

  • Format : Format Kindle
  • Taille du fichier : 1470 KB
  • Nombre de pages de l'édition imprimée : 304 pages
  • Editeur : W. W. Norton & Company; Édition : 1 (31 décembre 2012)
  • Vendu par : Amazon Media EU S.à r.l.
  • Langue : Anglais
  • ISBN-10: 039334777X
  • ISBN-13: 978-0393347777
  • ASIN: B007Q6XLF2
  • Synthèse vocale : Activée
  • X-Ray :
  • Moyenne des commentaires client : 5.0 étoiles sur 5  Voir tous les commentaires (1 commentaire client)
  • Classement des meilleures ventes d'Amazon: n°4.860 dans la Boutique Kindle (Voir le Top 100 dans la Boutique Kindle)
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Commentaires client les plus utiles
5.0 étoiles sur 5 A GREAT TEACHER 4 mars 2013
Format:Format Kindle
My first contact with maths in elementary school was are disaster: WIsh I had met with the author at the time. He is definitely a wonderful teacher, the kind who makes you feel smart. This book about statistics reads like a thriller. And the anecdote about the high school student who received coupons for pregnancy items from a big retailer is Hollywood stuff.
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Commentaires client les plus utiles sur Amazon.com (beta)
Amazon.com: 4.4 étoiles sur 5  212 commentaires
112 internautes sur 120 ont trouvé ce commentaire utile 
4.0 étoiles sur 5 Interesting; should entice those who think they don't like stats 14 janvier 2013
Par Anne Swan - Publié sur Amazon.com
Format:Relié|Achat vérifié
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 internautes sur 51 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Interesting and Useful - 9 janvier 2013
Par Loyd E. Eskildson - Publié sur Amazon.com
Format:Relié
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.
21 internautes sur 22 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 The Only Explanation of the Monty Hall Problem I Have Actually Understood 20 janvier 2013
Par takingadayoff - Publié sur Amazon.com
Format:Relié
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.
29 internautes sur 32 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Wonderful Book on Statistics for the Non-Expert 10 janvier 2013
Par Book Fanatic - Publié sur Amazon.com
Format:Relié
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!
10 internautes sur 10 ont trouvé ce commentaire utile 
3.0 étoiles sur 5 "Statistics is like a high caliber gun, very useful in the right hands but potentially disastrous if misused" 8 septembre 2013
Par Neuron - Publié sur Amazon.com
Format:Relié
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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