EVERYBODY LIES by Seth Stephens-Davidowitz (2017)
 -Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are

Read by . . : Tim Andres Pabon
Publisher . : Harer Audio (2017)
ISBN . . . .: B06XCYD5KG 1538416883 9781538416884
Format. . . : MP3. 5 tracks.
Size: . . . : 421 MB
Bitrate . . : 128 kbps (Stereo, CBR, 44.1 kHz)
Source . . .: MP3 CD (3 hrs)
Genre . . . : Social Science Popular Culture Data Mining Computers
Abridged . .: Abridged

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 Links: 
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Description:

Blending the informed analysis of The Signal and the Noise with the instructive iconoclasm of Think Like a Freak, a fascinating, illuminating, and witty look at what the vast amounts of information now instantly available to us reveal about ourselves and our world - provided we ask the right questions.

By the end of an average day in the early 21st century, human beings searching the Internet will amass eight trillion gigabytes of data. This staggering amount of information - unprecedented in history - can tell us a great deal about who we are - the fears, desires, and behaviors that drive us and the conscious and unconscious decisions we make. From the profound to the mundane, we can gain astonishing knowledge about the human psyche that less than 20 years ago seemed unfathomable.

Everybody Lies offers fascinating, surprising, and sometimes laugh-out-loud insights into everything from economics to ethics to sports to race to sex, gender, and more, all drawn from the world of big data. What percentage of white voters didn't vote for Barack Obama because he's black? Does where you go to school effect how successful you are in life? Do parents secretly favor boy children over girls? Do violent films affect the crime rate? Can you beat the stock market? How regularly do we lie about our sex lives, and who's more self-conscious about sex, men or women?
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Seth Stephens-Davidowitz received a Ph.D. in economics from Harvard in 2013. His work focuses on using big-data sources to uncover previously hidden behaviors and attitudes. He is at work on a book based on his research. He is a former quantitative analyst at Google