Tips and Techniques for Statistics and Quality Improvement

Blog posts and articles about using Minitab software in quality improvement projects, research, and more.

Editor's note: If you would like to see these tools presented in a webinar, visit our On Demand Webinars and look for "5 Critical Tools for Your Lean Deployment."

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Are you going to be a witch today? Batman? Jedi? You're not alone according to National Retail Federation statistics on top costumes and Halloween spending trends. Last-minute candy shopping? Check out kidzworld.com’s list of the top 10 candies for Halloween.

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On the heels of Healthcare Quality Week last week, we wanted to share our conversation with Dr. Sandy Fogel, the surgical quality officer at Carilion Clinic in Roanoke, VA.

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Wildfires in California have killed at least 40 people and burned more than 217,000 acres in the past few weeks. Nearly 8,000 firefighters are trying to contain the blazes with the aid of more than 800 firetrucks, 70 helicopters and 30 planes.

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Research out of the Juran Institute, which specializes in training, certification, and consulting on quality management globally, reveals that only 30 percent of improvement initiatives succeed 

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Overfitting a model is a real problem you need to beware of when performing regression analysis. An overfit model result in misleading regression coefficients, p-values, and R-squared statistics. Nobody wants that, so let's examine what overfit models are, and how to avoid falling into the overfitting trap.

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Maybe you're just getting started with analyzing data. Maybe you're reasonably knowledgeable about statistics, but it's been a long time since you did a particular analysis and you feel a little bit rusty. In either case, the Assistant menu in Minitab Statistical Software gives you an interactive guide from start to finish. It will help you choose the right tool quickly, analyze your data properly, and even interpret...

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Control charts take data about your process and plot it so you can distinguish between common-cause and special-cause variation. Knowing the difference is important because it permits you to address potential problems without over-controlling your process.  

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In statistics, as in life, absolute certainty is rare. That's why statisticians often can't provide a result that is as specific as we might like; instead, they provide the results of an analysis as a range, within which the data suggest the true answer lies.

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by Matthew Barsalou, guest blogger

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