Waubonsee Community College

Naked statistics, stripping the dread from the data, Charles Wheelan

Label
Naked statistics, stripping the dread from the data, Charles Wheelan
Language
eng
Bibliography note
Includes bibliographical references (pages 261-267) and index
Illustrations
illustrations
Index
index present
Literary Form
non fiction
Main title
Naked statistics
Nature of contents
bibliography
Oclc number
783162698
Responsibility statement
Charles Wheelan
Sub title
stripping the dread from the data
Summary
The field of statistics is rapidly transforming into a discipline that Hal Varian at Google has called "sexy". And with good reason; from batting averages and political polls to game shows and medical research, the real-world application of statistics is growing by leaps and bounds. In this book the author demystifies the study of statistics by stripping away the arcane and technical details to get at the underlying intuition that is key to understanding the power of statistical concepts. Tackling a wide-ranging set of problems, he demonstrates how statistics can be used to look at questions that are important and relevant to us today
Table Of Contents
Why I hated calculus but love statistics -- What's the point? -- Descriptive statistics : Who was the best baseball player of all time? -- Deceptive description : "He's got a great personality!" and other true but grossly misleading statements -- Correlation : How does Netflix know what movies I like? -- Basic probability : Don't buy the extended warranty on your $99 printer -- The Monty Hall problem -- Problems with probability : How overconfident math geeks nearly destroyed the global financial system -- The importance of data : "Garbage in, garbage out" -- The central limit theorem : The Lebron James of statistics -- Inference : Why my statistics professor thought I might have cheated -- Polling : How we know that 64 percent of Americans support the death penalty (with a sampling error (plus or minus) 3 percent) -- Regression analysis : The miracle elixir -- Common regression mistakes : The mandatory warning label -- Program evaluation : Will going to Harvard change your life? -- Conclusion : Five questions that statistics can help answer -- Appendix : Statistical software
Classification
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