Before people jump into using tools, they have to understand the big picture. That’s statistical thinking.

Ever heard the terms “statistical thinking” and “statistical engineering,” but wondered how the two relate?

Roger Hoerl, who wrote the book *Statistical Thinking: Improving Business Performance* with Ron Snee, explains how the two concepts differ and how they work together in a recent Analytically Speaking webcast.

When engineering students take statistics, they often view the discipline as a collection of tools.

“They have a bunch of tools thrown on the table,” says Hoerl. “Here’s regression, here’s design of experiments, here’s hypothesis testing, here’s time series. And then they face a problem, and they have no idea what to do.”

Before people jump into using the tools, they have to understand the big picture. That’s statistical thinking. It’s a philosophy of learning in action based on some fundamental principles.

Essentially, statistical thinking is the careful consideration of what you’re trying to accomplish and how you’ll collect the data, while understanding the process that produces the data.

But there’s still a gap between understanding this philosophy and using the tools, especially for a complex problem that requires more than one tool.

Enter statistical engineering. “It’s a discipline,” Hoerl explains. “It’s the study of how to best utilize statistical thinking methods and tools, and integrate them with other disciplines like computer science to achieve enhanced results.”

Once you’ve adopted the philosophy, know how to attack a problem and are competent with the tools themselves, you’ll have a more holistic strategy for problem solving. Imagine how helpful this in the real world, where textbook problems often don’t apply. Watch the full video.

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