We live in a world of Big Data–and it’s getting bigger every 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. From world leaders to average citizens, everyone is prone to making critical decisions based on poor data interpretations.
In Numbersense, expert statistician Kaiser Fung explains when readers should accept the conclusions of the Big Data “experts”–and when they 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 current unemployment data issued by the government be trusted?
- How do you improve your fantasy sports team?
- Should you worry about businesses that track your data?
Readers shouldn’t take for granted statements made in the media, by leaders, or even by their best friend. Everyone is on information overload today, and there’s a lot of bad information out there.
Numbersense gives readers the insight into how Big Data interpretation works–and how it too often doesn’t work. They won’t come away with the skills of a professional statistician, but they will have a keen understanding of the data traps even the best statisticians can fall into, and they’ll trust the mental alarm that goes off in their head when something just doesn’t seem to add up.
About the Author:
Kaiser Fung (New York City) is a professional statistician with over a decade of experience applying statistical methods to marketing and advertising businesses. He holds an MBA from Harvard Business School, in addition to degrees from Princeton and Cambridge Universities. He is a statistician for Sirius XM Radio. His acclaimed blog, Junk Charts (junkcharts.typepad.com), pioneered the critical examination of data and graphics in the mass media. He is also an adjunct professor at New York University teaching practical statistics.
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