Naked Statistics: Stripping the Dread from the Data
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- $12.99
Publisher Description
A New York Times bestseller
"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.
PUBLISHERS WEEKLY
Wheelan (Naked Economics) offers a helping hand and a humorous perspective to everyone who's ever felt confused, lied to, or just plain lost when it comes to statistics, those handy data sets used to determine everything from batting averages and trends on Wall Street to the quality of a school and which door you should pick if you're playing Let's Make a Deal. The author shows how statistics like the mean and the median are used to summarize and find patterns in large collections of data, and in later chapters he consider how statistics are used to assess large-scale economic risk and to find important connections between different sets of data, like those that allow Netflix to offer reasonable movie recommendations. Throughout, Wheelan stresses how statistics "rarely a single right' " answer; indeed, when deployed carelessly or deliberately misused, they can sometimes obscure the truth. Furthermore, the author reminds readers that while data can be used to help make better decisions, "even the most precise measurements or calculations should be checked against common sense." Wheelan's relatively mathless real world examples (he sequesters equations in appendixes) and wry style heavily seasoned with pop culture references make for a fun and illuminating read.
Customer Reviews
Clearly explains the topic
As someone who uses a lot of advanced statistical methods in my profession, I enjoy reading books like this, as they often help me to explain what I am doing to non-scientists. The author is also not a statistician, and that is a good thing, as he approaches the topic from a very practical view-point. His explanations are clear and concise, and technically accurate. It is the best book, by far, for the curious layperson seeking to understand statistics and its use in life.
A few topics were omitted,which puzzle me. Analysis of variance was not covered, which is a shame, especially since it could dove-tail nicely into the discussion around multi-linear regression. More serious was the complete lack of any discussion on Bayesian statistics. As an unabashed Bayesian , I find this to be most unfortunate. There is a huge resurgence in Bayesian methods now, and all serious stats research is Bayesian-based. More importantly, to discuss Bayesian, one must discuss frequentist statistics, including the limitations of the p-value (contrary to what the author would like you to believe, the p-value is not without some serious faults). Here's hoping the author revises the book and includes these important topics, which would improve an already terrific book.
Pure Gold. Useful and entertaining.
Provides a very useful way to consider the mechanics of statistics, but also human factors that can accidentally corrupt the process. In addition to learning the methodology, it provides ways I can communicate the ‘how’ of this to people I present this to. (in ways they understand)
Between “Naked Statistics” and "Data Design: The Visual Display of Qualitative and Quantitative Information” by Jürgen Kai-Uwe Brock, readers who create data analysis and then present it to stakeholders will have a full tool box of incredibly useful info.
Informative but could’ve gone further
The book was very informative in trying to make statistics make sense to those of us who struggle with them. It did a great job explaining, in layman’s terms, how the math relates to the topic being analyzed and how that can benefit or hurt us.
I was hoping for a little more of the math itself since I purchased it to try and get a better grasp on that. It barely touches on some of it while conceding that’s not why the author wrote the book. Either way, it does help explain much of the concepts behind all the research studies we see and hear in the news and social media. Worth the read.