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Guidance and results for the data-rich, yet information-poor.

How Much Do You Need to Know About Statistics?

StatisticsThis is another question that came up in TMA’s free “Data Mining, Failure to Launch” webinar Q&A. “On a scale of 1-10, how important is the knowledge of statistics to a businessperson who wants to use data analytics?”

Having a basic knowledge of statistics is certainly helpful. For example, you need to understand what a “correlation” is. Every bit of knowledge certainly helps. The TMA course, “Transforming Data to Decisions” is meant to help people get a basic understanding of the statistics that they’d need to know.

But the truth is, most people just aren’t that comfortable with statistics, including people who have launched highly successful predictive modeling and data analytics projects for their organizations. These people had a different focus: asking the right kinds of question and looking for the right kind of help.

Ultimately, on a scale of 1-10, you might need a “3” in your level of statistics sophistication. Most modern software will handle the rest with very little difficulty, which is why you don’t need to hire a PhD or be a PhD to launch a successful predictive analytics project.

You do, however, need a “10” in understanding what you are trying to accomplish. You need a 10 in strategy and decision making. You need to be a superstar at identifying opportunities and business problems that data mining can solve for you.

This is really the difference between tactics and strategy. Tactics is all about building accurate models. But strangely enough, no model is as accurate as it could be–models that deliver a high ROI may only be “close enough.” Strategy, by contrast, is all about setting the correct target.

It’s the difference between knowing how to build a piano and knowing how to play a piano. Building models is nice, but playing those models correctly? That’s where the real money is.

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