Predictive analytics

Eric Siegel

at 250 WPM

5h 38m

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12

days at 30 min/day

338

total minutes

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Predictive analytics

by Eric Siegel

2013

Wiley & Sons, Incorporated, John

338

9781299192706

Description

You have been predicted -- by companies, governments, law enforcement, hospitals, and universities. Their computers say, "I knew you were going to do that!" These institutions are seizing upon the power to predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats financial risk, fortifies healthcare, conquers spam, toughens crime fighting, and boosts sales. How? Prediction is powered by the world's most potent, booming unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive analytics unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future -- lifting a bit of the fog off our hazy view of tomorrow -- means pay dirt. In this rich, entertaining primer, former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they are even aware of it themselves. Why early retirement decreases life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death, including one health insurance company. How U.S. Bank, European wireless carrier Telenor, and Obama's 2012 campaign calculated the way to most strongly influence each individual. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths -- how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide who stays in prison and who goes free. What's predicted by the BBC, Citibank, ConEd, Facebook, Ford, Google, IBM, the IRS, Match.com, MTV, Netflix, Pandora, PayPal, Pfizer, and Wikipedia. A truly omnipresent science, predictive analytics affects everyone, every day. Although largely unseen, it drives millions of decisions, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. Predictive analytics transcends human perception. This book's final chapter answers the riddle: What often happens to you that cannot be witnessed, and that you can't even be sure has happened afterward -- but that can be predicted in advance? Whether you are a consumer of it -- or consumed by it -- get a handle on the power of Predictive Analytics.

Frequently Asked Questions

How many pages are in Predictive analytics?

This edition of Predictive analytics has approximately 338 pages. Please note, this is an estimate and the exact page count can vary between hardcover, paperback, and e-book versions.

How long does it take to read Predictive analytics?

For most readers, Predictive analytics typically takes between 7h 3m and 4h 42m to complete. This is based on the book's length of approximately 84,500 words and common reading speeds.

Here's a detailed breakdown: • Continuous reading at 250 WPM: approximately 5h 38m of focused reading • Casual reading (30 minutes/day): you could finish in roughly 12 days • Estimated word count: 84,500 words

Your individual reading time will vary based on your personal reading pace, the amount of daily reading time, and your familiarity with the subject matter.

What is the word count of Predictive analytics?

The estimated word count for Predictive analytics is approximately 84,500 words. This figure is calculated using industry-standard methods that consider genre-specific word density patterns, typical formatting and layout characteristics, and standard words-per-page ratios for published books.

This is an approximation — actual word count may vary based on font size, formatting, edition, and the presence of illustrations or charts.

Who is the author of Predictive analytics?

Predictive analytics was written by Eric Siegel.

When was Predictive analytics published?

The publication date for this specific edition is 2013. The original work may have been published on a different date.