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How To Lie With Statistics

Author : Darrell Huff
ISBN : 0393070875
Genre : Mathematics
File Size : 35.47 MB
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Over Half a Million Copies Sold--an Honest-to-Goodness Bestseller Darrell Huff runs the gamut of every popularly used type of statistic, probes such things as the sample study, the tabulation method, the interview technique, or the way the results are derived from the figures, and points up the countless number of dodges which are used to full rather than to inform.
Category: Mathematics

How To Take A Chance

Author : Darrell Huff
ISBN : STANFORD:20500885198
Genre : Chance
File Size : 74.86 MB
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Category: Chance

More Damned Lies And Statistics

Author : Joel Best
ISBN : 0520930029
Genre : Social Science
File Size : 64.32 MB
Format : PDF, ePub, Docs
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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.
Category: Social Science

An Introduction To Statistical Learning

Author : Gareth James
ISBN : 9781461471387
Genre : Mathematics
File Size : 20.92 MB
Format : PDF, Mobi
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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
Category: Mathematics

The Elements Of Statistical Learning

Author : Trevor Hastie
ISBN : 9780387216065
Genre : Mathematics
File Size : 37.48 MB
Format : PDF
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During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.
Category: Mathematics

An Introduction To Statistical Methods And Data Analysis

Author : R. Lyman Ott
ISBN : 9781305465527
Genre : Mathematics
File Size : 65.56 MB
Format : PDF
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Ott and Longnecker's AN INTRODUCTION TO STATISTICAL METHODS AND DATA ANALYSIS, Seventh Edition, provides a broad overview of statistical methods for advanced undergraduate and graduate students from a variety of disciplines who have little or no prior course work in statistics. The authors teach students to solve problems encountered in research projects, to make decisions based on data in general settings both within and beyond the university setting, and to become critical readers of statistical analyses in research papers and news reports. The first eleven chapters present material typically covered in an introductory statistics course, as well as case studies and examples that are often encountered in undergraduate capstone courses. The remaining chapters cover regression modeling and design of experiments. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Category: Mathematics

Weaponized Lies

Author : Daniel J. Levitin
ISBN : 9781524742225
Genre : Social Science
File Size : 56.97 MB
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Previously Published as A Field Guide to Lies We’re surrounded by fringe theories, fake news, and pseudo-facts. These lies are getting repeated. New York Times bestselling author Daniel Levitin shows how to disarm these socially devastating inventions and get the American mind back on track. Here are the fundamental lessons in critical thinking that we need to know and share now. Investigating numerical misinformation, Daniel Levitin shows how mishandled statistics and graphs can give a grossly distorted perspective and lead us to terrible decisions. Wordy arguments on the other hand can easily be persuasive as they drift away from the facts in an appealing yet misguided way. The steps we can take to better evaluate news, advertisements, and reports are clearly detailed. Ultimately, Levitin turns to what underlies our ability to determine if something is true or false: the scientific method. He grapples with the limits of what we can and cannot know. Case studies are offered to demonstrate the applications of logical thinking to quite varied settings, spanning courtroom testimony, medical decision making, magic, modern physics, and conspiracy theories. This urgently needed book enables us to avoid the extremes of passive gullibility and cynical rejection. As Levitin attests: Truth matters. A post-truth era is an era of willful irrationality, reversing all the great advances humankind has made. Euphemisms like “fringe theories,” “extreme views,” “alt truth,” and even “fake news” can literally be dangerous. Let's call lies what they are and catch those making them in the act.
Category: Social Science

Damned Lies And Statistics

Author : Joel Best
ISBN : 9780520953512
Genre : Social Science
File Size : 27.76 MB
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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.
Category: Social Science

All Of Statistics

Author : Larry Wasserman
ISBN : 9780387217369
Genre : Mathematics
File Size : 86.78 MB
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Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Category: Mathematics

The R Book

Author : Michael J. Crawley
ISBN : 9781118448960
Genre : Mathematics
File Size : 74.52 MB
Format : PDF, ePub
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Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research. This edition: Features full colour text and extensive graphics throughout. Introduces a clear structure with numbered section headings to help readers locate information more efficiently. Looks at the evolution of R over the past five years. Features a new chapter on Bayesian Analysis and Meta-Analysis. Presents a fully revised and updated bibliography and reference section. Is supported by an accompanying website allowing examples from the text to be run by the user. Praise for the first edition: ‘…if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.’ (The American Statistician, August 2008) ‘The High-level software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book…’ (Professional Pensions, July 2007)
Category: Mathematics