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Topics: Statistics, Scientific method, Hal Varian Pages: 4 (981 words) Published: January 24, 2014
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Article| McKinsey Global Institute
MBAs can't afford to end their math education with calculus
March 12, 2013 | byJames Manyika and Michael Chui
From financial transactions to consumer purchases to political polling, a torrent of data now flows into every area of the global economy.

Yet that river of information is meaningless without a workforce that can harness and analyze it.

The effective use of big data will increasingly determine whether companies—and the US—can compete.

But our education and training programs haven’t adapted to develop the skills big data demands. US students are shuttled along a familiar path in mathematics: first stop algebra, then geometry and trigonometry, and finally, the ultimate destination, calculus. This time-honored curriculum seems increasingly out of touch in a world that is flooded with noisy and voluminous data. The majority of students need to be immersed in the more practical discipline of statistics, which has greater relevance for the jobs being generated by a digital economy.

Consider the teams of medical researchers running clinical trials or analyzing the outcomes of patients after a therapy has been made widely available: they have to select the parameters to study, assess the results, and draw the right conclusions about a drug’s effectiveness and safety. Online advertisers trying to micro-target consumers must be able to detect patterns in the massive amount of clickstream data they gather from the Web. Risk managers on Wall Street, retail buyers choosing this season’s merchandise, environmental scientists, sports analysts, and military strategists all rely on the ability to synthesize data and predict outcomes.

The key to making sense of all the data now at our...
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