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.

From “one of the great (greatest?) contemporary popular writers on economics” (Tyler Cowen) comes a smart, lively, and encouraging rethinking of how to use statistics. Today we think statistics are the enemy, numbers used to mislead and confuse us. That’s a mistake, Tim Harford says in The Data Detective. We shouldn’t be suspicious of statistics—we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often “the only way of grasping much of what is going on around us.” If we can toss aside our fears and learn to approach them clearly—understanding how our own preconceptions lead us astray—statistics can point to ways we can live better and work smarter. As “perhaps the best popular economics writer in the world” (New Statesman), Tim Harford is an expert at taking complicated ideas and untangling them for millions of readers. In The Data Detective, he uses new research in science and psychology to set out ten strategies for using statistics to erase our biases and replace them with new ideas that use virtues like patience, curiosity, and good sense to better understand ourselves and the world. As a result, The Data Detective is a big-idea book about statistics and human behavior that is fresh, unexpected, and insightful.

How statistical data is used, misused, and abused every day to fool us: “A very entertaining book about a very serious problem.” —Robert J. Shiller, winner of the Nobel Prize in Economics and author of Irrational Exuberance Did you know that baseball players whose names begin with “D” are more likely to die young? That Asian Americans are most susceptible to heart attacks on the fourth day of the month? That drinking a full pot of coffee every morning adds years to your life, but one cup a day increases your pancreatic cancer risk? These “facts” have been argued with a straight face by credentialed researchers and backed up with reams of data and convincing statistics. As Nobel Prize–winning economist Ronald Coase cynically observed, “If you torture data long enough, it will confess.” Lying with statistics is a time-honored con. In Standard Deviations, economics professor Gary Smith walks us through the various tricks and traps that people use to back up their own crackpot theories. Sometimes, the unscrupulous deliberately try to mislead us. Other times, the well-intentioned are blissfully unaware of the mischief they are committing. Today, data is so plentiful that researchers spend precious little time distinguishing between good, meaningful indicators and total rubbish. Not only do others use data to fool us, we fool ourselves. Drawing on breakthrough research in behavioral economics and using clear examples, Standard Deviations demystifies the science behind statistics and makes it easy to spot the fraud all around us. “An entertaining primer . . . packed with figures, tables, graphs and ludicrous examples from people who know better (academics, scientists) and those who don’t (political candidates, advertisers).” —Kirkus Reviews (starred review)

In this sequel to the acclaimed Damned Lies and Statistics, which the Boston Globe said "deserves a place next to the dictionary on every school, media, and home-office desk," Joel Best continues his straightforward, lively, and humorous account of how statistics are produced, used, and misused by everyone from researchers to journalists. Underlining the importance of critical thinking in all matters numerical, Best illustrates his points with examples of good and bad statistics about such contemporary concerns as school shootings, fatal hospital errors, bullying, teen suicides, deaths at the World Trade Center, college ratings, the risks of divorce, racial profiling, and fatalities caused by falling coconuts. More Damned Lies and Statistics encourages all of us to think in a more sophisticated and skeptical manner about how statistics are used to promote causes, create fear, and advance particular points of view. Best identifies different sorts of numbers that shape how we think about public issues: missing numbers are relevant but overlooked; confusing numbers bewilder when they should inform; scary numbers play to our fears about the present and the future; authoritative numbers demand respect they don’t deserve; magical numbers promise unrealistic, simple solutions to complex problems; and contentious numbers become the focus of data duels and stat wars. The author's use of pertinent, socially important examples documents the life-altering consequences of understanding or misunderstanding statistical information. He demystifies statistical measures by explaining in straightforward prose how decisions are made about what to count and what not to count, what assumptions get made, and which figures are brought to our attention. Best identifies different sorts of numbers that shape how we think about public issues. Entertaining, enlightening, and very timely, this book offers a basis for critical thinking about the numbers we encounter and a reminder that when it comes to the news, people count—in more ways than one.

* 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!

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.