Everydata: The Misinformation Hidden in the Little Data You Consume Every Day – John H. Johnson, Mike Gluck

Review From User :

Mark Twain said there are three types of lies in the world: Lies, Damn lies, and Statistics. This book explores that quote a bit farther--what exactly makes statistics a lie Is there a time when they are not lies Of course. Are there times when they are intentional lies Oh my yes. Are there times when they are unintentionally misleading Most of the time, it seems. This book documents the different ways that a stat can go astray, what that means in your every day life, and how you can avoid these traps in consuming or creating your own statistics.

I am absolutely not a math person. I can't math. Don't be scared by the idea of statistics--there is not a single concept in this book that couldn't be easily understood by a high school student. They take complex concepts and make them into a fun, readable, and easily-applied set of rules and thoughts. The real-world examples are current, well considered, and do a great job of illustrating each point. I especially liked the sum-up at the end of every chapter, and the big sum-up at the end of the book.

We are constantly bombarded by data, every day, every minute. This book promises to make you a smart consumer of that data, and I think it lives up to that promise very well.


While everyone is talking about “big data,” the truth is that understanding the “little data” – the stats that underlie newspaper headlines, stock reports, weather forecasts, and so on – is what helps you make smarter decisions at work, at home, and in every aspect of your life.
Expand text… The average person consumes approximately 30 gigabytes of data every single day, but has no idea how to interpret it correctly. Everydata explains, through the eyes of an expert economist and statistician, how to decipher the small bytes of data we consume in a day.

Everydata is filled with countless examples of people misconstruing data – with results that range from merely frustrating to catastrophic:

– The space shuttle Challenger exploded in part because the engineers were reviewing a limited sample set.
– Millions of women avoid caffeine during pregnancy because they interpret correlation as causation.
– Attorneys faced a $1 billion jury verdict because of outlier data.

Each chapter highlights one commonly misunderstood data concept, using both realworld and hypothetical examples from a wide range of topics, including business, politics, advertising, law, engineering, retail, parenting, and more. You’ll find the answer to the question – “Now what?” – along with concrete ways you can use this information to immediately start making smarter decisions, today and every day.

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