Loading... Naked statistics : stripping the dread from the data (original 2013; edition 2013)by Charles J. Wheelan
Work detailsNaked Statistics: Stripping the Dread from the Data by Charles Wheelan (2013)
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Sign up for LibraryThing to find out whether you'll like this book. No current Talk conversations about this book. I started out strong in this book and then got bogged down toward the end. Part of the problem could have been that I was trying to read quickly to meet a library deadline, instead of taking the time to read this one chapter at a time and ensure I'd fully absorbed the concepts before moving on. It is well written, with clear explanations and plenty of relevant, real-life (and a few occasionally absurd) examples to illustrate how the various formulae and calculations work. Recommended if you've always wondered about the science behind such things as opinion polls, medical studies or Netflix algorithms. Chalres Wheelan is not shy about tackling big jobs. He proved it by writing Naked Economics, a layman's explanation of how the art of economics is supposed to work, a tome for the guys who sat in the back of the Econ 101. The breadth of this book is in some ways not as ambitious, but in many other ways much more ambitious. While statistics does not have the kind of macro ramifications that economics does, the inner owrkings and the detailed in and out of statistics are as complex if not more that economics. What Wheelan attempted to do is to explain the major areas of statistics: descriptive, inferential, regression, the Central Limit theorem, probability, etc in qualitative terms, i.e. he tried to not scare people away with mathemmatics by not having too much mathematics. It is an impossible task. I would say that he was somewhat successful with this tome. He was able, through some interesting examples and excellent story telling skills, to convey the essence of what is important with each of the topics. He was also able to give some taste as to what the statisticians are concerned about in their studies. What he was not able to do was to tell the reader why these things matter quantitatively. It isn't that he was unable to explain the concepts, he did very well on that aspect, but the proof of the pudding is in the tasting, and because of the limits imposed by the nature of this undertaking, the most useful tool in his arsenal, the mathematics was taken away. He could not resort to showing the math and saying: and by this numerical illustration, you can see that... Instead, he used up a lot of pages to get into the deep details of what he had intended, and that is too cumbersome and lumbering for everyone involved. To be sure, he did his best, and his best was quite good. I doubt many could have done better, but by taking the middle route, I can't say that he cleared things up for the layman. It cleared some things up for this knowledgeable amateur, but it also confused me somewhat. Of course, it spurred me to do some auto-didactic work, which is good, I suppose. This is a very lucidly written book that covers the basics of the branch of math known as statistics. It shows the uses and misuses of statistics and some of the essential math behind the applications. Readers will find a discussion of the familiar normal distribution; an explication of the Central Limit Theorem; the formula for calculating the standard error; and a fairly detailed introduction to probability theory. The subject matter never becomes dull in Wheelan’s treatment because of his light sense of humor. For example, when discussing the limits of the validity of regression analysis, he writes: “Here is one of the most important things to remember when doing research that involves regression analysis. Try not to kill anyone.” He then goes on to explain how a mathematically consistent analysis of a large data set by the Harvard Medical School and the Harvard School of Public Health led to the belief that estrogen supplements were beneficial to women over 50 years old. Subsequently, millions of women were prescribed estrogen supplements. But later actual clinical trials involving double blind experiments showed that women taking estrogen had a higher incidence of heart disease, stroke, blood clots, breast cancer and other adverse health outcomes! But having warned the reader not to confuse correlation with causation and that statistical analysis yields probabilistic outcomes rather than certainty, he shows how valuable such analysis can be. He concludes with the admonition to “[g]o forth and use data wisely and well.” Even if you have had a college level course or two in statistics, you will find this book enjoyable and enlightening. (JAB) My interests in Mathematics have been a little above normal for quite some time now. I took up this book to refresh my Statistical knowledge, assuming I knew quite a bit about the subject and boy was I wrong. Charles Wheelan has done an exceptional work in writing this book. The title basically translates to 'Understanding Statistics through its application' which apparently is an amazing way to teach any subject for that matter. I did not know the power of Regression Analysis and the author elucidates it extremely well. Other advanced topics are clarified for the general reader and booby-traps are disclosed so the reader avoids them. All-in-all, great read, thoroughly enjoyed it. no reviews | add a review
References to this work on external resources. Wikipedia in English (2)Amazon.com Product Description (ISBN 0393071952, Hardcover)The best-selling author of Naked Economics defies the odds with a book about statistics that you’ll welcome and enjoy. 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. (retrieved from Amazon Thu, 12 Mar 2015 18:12:33 -0400) Demystifies the study of statistics by stripping away the technical details to examine the underlying intuition essential for understanding statistical concepts. (summary from another edition) |
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Naked Statistics is definitely more fun than a textbook. It starts with the very basic concepts (mean, median and mode) and works its way up to regression analysis. It builds on the concepts learned and applies them to both realistic and fantastic situations (such as bus hunting for terrorists on the hunt for food. Luckily, it just happens to be the International Festival of Sausage, which calms them down nicely). The equations and letters x, y and n are few and far between (but are included in appendices if you want to revisit them).
My favourite part of the book is the examples. Sometimes they are funny (like the International Festival of Sausage), sometimes the examples are ripped straight from the headlines. It shows the science behind the spin of predicting presidential candidates to whether going to a famous college like Harvard means you will earn more (you won’t). If you already question the media when it comes to polls, the chapter on them will be fascinating. It shows how information can be skewed using statistics to get the result you want. A lot of this relies on the samples taken – ‘garbage in, garbage out’ (i.e. if you choose a biased sample, such as supporters at a Trump rally, of course you will get a high percentage voting for him. This sample is not reflective of the entire American population).
The language that Wheelan uses to describe the concepts is easy to read and easy to understand. I had flashbacks of remembering the dry statistics from uni and it was refreshing to read them described in a different way (which was also way more interesting). I didn’t find it patronising, even the mean/median/mode section (when we had this as a 2 hour postgrad lecture, my friends and I spent the time wandering in and out, buying chips and lollies and writing notes to each other because we deemed ourselves above this). I really wish my lecturers had read this book!
However, you don’t need previous knowledge of statistics to enjoy this book. You will find that you’ve been exposed to a lot of these methods in the world around you. I enjoyed this book so much that I’m going to read Wheelan’s Naked Economics, a subject I know less about (but again, need to learn about for work reasons). I’m sure he’s going to make any subject he turns to interesting.
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