Numbersense: How to Use Big Data to Your Advantage
Language: English
Published by McGraw-Hill Education, 2013
- First Edition
- Hardcover
- Used
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- Title
- Numbersense: How to Use Big Data to Your Advantage
- Author
- Fung, Kaiser
- Publisher
- McGraw-Hill Education
- Publication year
- 2013
- Condition
- Very Good
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0071799664
- ISBN 13
- 9780071799669
- Edition
- 1st Edition.
- Item weight
- 0.939 pounds
- Dimensions
- N/A
We live in a world of Big Data--and it's getting biggerevery day. Virtually every choice we make hinges on how someone generates data . . . and how someone else interprets it--whether we realize it or not.
Where do you send your child for the best education?Big Data. Which airline should you choose to ensure a timely arrival? Big Data. Who will you vote for in the next election? Big Data.
The problem is, the more data we have, the more difficult it is to interpret it. From world leaders to average citizens, everyone is prone to making critical decisions based on poor data interpretations.
In Numbersense, expert statistician Kaiser Fungexplains when you should accept the conclusions of the Big Data "experts"--and when you should say, "Wait . . . what?" He delves deeply into a wide range of topics, offering the answers to important questions, such as:
- How does the college ranking system really work?
- Can an obesity measure solve America's biggest healthcare crisis?
- Should you trust current unemployment data issued by the government?
- How do you improve your fantasy sports team?
- Should you worry about businesses that track your data?
Don't take for granted statements made in the media, by our leaders, or even by your best friend. We're on information overload today, and there's a lot of bad information out there.
Numbersense gives you the insight into how BigData interpretation works--and how it too often doesn't work. You won't come away with the skills of a professional statistician. But you will have a keen understanding of the data traps even the best statisticians can fall into, and you'll trust the mentalalarm that goes off in your head when something just doesn't seem to add up.
Praise for Numbersense
"Numbersense correctly puts the emphasis not on the size of big data, but on the analysis of it. Lots of fun stories, plenty of lessons learned―in short, a great way to acquire your own sense of numbers!"
Thomas H. Davenport, coauthor of Competing on Analytics and President’s Distinguished Professor of IT and Management, Babson College
"Kaiser’s accessible business book will blow your mind like no other. You’ll be smarter, and you won’t even realize it. Buy. It. Now."
Avinash Kaushik, Digital Marketing Evangelist, Google, and author, Web Analytics 2.0
"Each story in Numbersense goes deep into what you have to think about before you trust the numbers. Kaiser Fung ably demonstrates that it takes skill and resourcefulness to make the numbers confess their meaning."
John Sall, Executive Vice President, SAS Institute
"Kaiser Fung breaks the bad news―a ton more data is no panacea―but then has got your back, revealing the pitfalls of analysis with stimulating stories from the front lines of business, politics, health care, government, and education. The remedy isn’t an advanced degree, nor is it common sense. You need Numbersense."
Eric Siegel, founder, Predictive Analytics World, and author, Predictive Analytics
"I laughed my way through this superb-useful-fun book and learned and relearned a lot. Highly recommended!"
Tom Peters, author of In Search of Excellence
"Synopsis" may belong to another edition of this title.
About the Author
KAISER FUNG is a professional statistician with over a decade of experience applying statistical methods to marketing and advertising businesses. He is an adjunct professor at New York University teaching practical statistics. He is the creator of the popular Junk Charts blog and the author of the acclaimed Numbers Rule Your World.
"About the title" may belong to another edition of this title.
Better World Books: West
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