Summary Of How To Lie With Statistics By Darrell Huff

If you want to outsmart a crook, learn his tricks—Darrell Huff explains exactly how in the classic How to Lie with Statistics. From distorted graphs and biased samples to misleading averages, there are countless statistical dodges that lend cover to anyone with an ax to grind or a product to sell. With abundant examples and illustrations, Darrell Huff’s lively and engaging primer clarifies the basic principles of statistics and explains how they’re used to present information in honest and not-so-honest ways. Now even more indispensable in our data-driven world than it was when first published, How to Lie with Statistics is the book that generations of readers have relied on to keep from being fooled.

Learn to identify how companies use statistics to deceive and manipulate the public. Today our news is bombarded with statistical information. We are given averages, percentages, and more, and are simply expected to trust these numbers without question. H.G. Wells understood the importance of understanding this information by stating, “Statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write.” Unfortunately, many in society don’t have a strong sense of statistical thinking, and writers take advantage of this by using the necessary vocabulary and numbers to dupe their readers. At first glance, numbers seem credible and trustworthy, but if you take a deeper look, you might find that there is more than meets the eye. Throughout How to Lie With Statistics, Darrell Huff shares the tricks writers use in statistics to their advantage. As you read, you’ll learn when it is statistically safest to drive, how to create the best sample in a study, and why counting all the beans is simply too hard. Do you want more free book summaries like this? Download our app for free at https://www.QuickRead.com/App and get access to hundreds of free book and audiobook summaries. DISCLAIMER: This book summary is meant as a preview and not a replacement for the original work. If you like this summary please consider purchasing the original book to get the full experience as the original author intended it to be. If you are the original author of any book on QuickRead and want us to remove it, please contact us at [email protected].

Here, by popular demand, is the updated edition to Joel Best's classic guide to understanding how numbers can confuse us. In his new afterword, Best uses examples from recent policy debates to reflect on the challenges to improving statistical literacy. Since its publication ten years ago, Damned Lies and Statistics has emerged as the go-to handbook for spotting bad statistics and learning to think critically about these influential numbers.

This edition updates benchmarks, includes a new chapter on rhetoric, updated a few examples, and thoroughly updated the bibliography.

* Our summary is short, simple and pragmatic. It allows you to have the essential ideas of a big book in less than 30 minutes. *By reading this summary, you will learn how to defend yourself against the misused statistics that litter our daily lives. *You will also learn : the importance of statistical samples; to be wary of missing data; how to identify misleading graphs; how to manipulate statistical jargon to your advantage; what questions to ask yourself to avoid falling into the trap set by certain statistics. *Statistics are very useful, but they can be misused to sell a product, convince voters, or attract attention. For example, a local newspaper, with its focus on crime, may make its readers believe that they live in a dangerous place, and a study explaining that after ingesting a certain medication, colds tend to disappear, may make people buy a product that is as effective as no treatment at all! Statistics have the devious advantage of appearing factual, which is what makes them attractive, but in the mouth of a dishonest person, they can fool even the most discerning readers. This book serves not as an instruction manual for crooks, but as a self-defense manual for their potential victims: honest people. *Buy now the summary of this book for the modest price of a cup of coffee!

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.

Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong. Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics. You'll find advice on: –Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan –How to think about p values, significance, insignificance, confidence intervals, and regression –Choosing the right sample size and avoiding false positives –Reporting your analysis and publishing your data and source code –Procedures to follow, precautions to take, and analytical software that can help Scientists: Read this concise, powerful guide to help you produce statistically sound research. Statisticians: Give this book to everyone you know. The first step toward statistics done right is Statistics Done Wrong.