​​​​​​Get Your Hands Dirty With Data​​

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​​​​​The Idea: If the best training is hands-on training … how do we improve our training on data analytics? Teach yourself statistics.​​​​​​

Yikes, you say. Seriously, you say? Tha​t's pretty daunting. Yes, but stay with me:​​

"… for most people, the gulf between recognizing the importance of data and actually beginning to analyze it is massive. How do those without extensive training in statistics equip themselves with the skills necessary to thrive (or even just survive) in our age of 'big data'?" Walter Frick writes in a Harvard Business Review blog post.

The 2012 U.S. presidential election elevated the visibility of the statisticians behind the campaign scene, crunching data to predict election outcomes at the most granular level. Nate Silver emerged as the pre-eminent guru in the field. His FiveThirtyEight blog in The New York Times was a must-read for campaign staff and political junkies. The FiveThirtyEight blog recently moved to ESPN and ABC News.

Nate Silver is the man when it comes to data modeling.

HBR's Frick recently had a conversation with Silver; the main point of their discussion: "Far from counseling that everyone must major in statistics, in the edited conversation he advises students and executives alike to roll up their sleeves — no matter their statistical literacy — and get their hands dirty with data."

OK, you say: I'm in. But where to begin? How do I increase my statistical literacy?

The Execution: Have you heard of Khan Academy? Its mission: "A free world-class education for anyone anywhere." If your math and stats brain has gone a bit fuzzy, this is a no-cost, at-your-own-pace way to refocus it. An amazing resource for learners, Khan Academy could be an answer to the age-old internal audit dilemma of how to provide the relevant, just-in-time training our teams — and ourselves — need and demand at a cost that fits into our budgets.

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