Free Naked Statistics: Stripping The Dread From The Data Ebooks To Download
Audie Award Finalist, Business/Educational, 2014 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. 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 best seller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.
Audible Audio Edition
Listening Length: 10 hours and 48 minutes
Program Type: Audiobook
Version: Unabridged
Publisher: Audible Studios
Audible.com Release Date: April 23, 2013
Language: English
ASIN: B00CH7FWWU
Best Sellers Rank: #9 in Books > Audible Audiobooks > Science > Mathematics #54 in Books > Science & Math > Mathematics > Applied > Probability & Statistics
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.
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.
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