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Wheelan Charles. Naked Statistics. Stripping the Dread from the Data

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Wheelan Charles. Naked Statistics. Stripping the Dread from the Data
W. W. Norton & Company, 2013. — 392 p.
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 bestselling 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 audiobook 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.
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.
What's the point?
Descriptive statistics
Deceptive description
Correlation
Basic Probability
The Monty Hall Problem
Problems with Probability
The Importance of Date
The Central Limit Theorem
Inference
Polling Regression Analysis
Common Regression Mistakes
Program Evaluation
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