Tips and Techniques for Statistics and Quality Improvement

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

Trying to solve a complex problem? You should begin by listing all suspected variables. Then, identify the few critical factors and separate them from the others that are not essential to understanding the cause. Let’s take a look at a very simple graphical tool that is very intuitive, can be used by virtually anyone, and does not require any prior statistical knowledge: the Multi-Vari Chart.

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Whether you're drinking beer, cocktails, wine or water, nothing is more frustrating than sitting at a bar waiting for a bartender to take your order. With the price of a drink (especially where I live in New York City!) costing nearly as much as the hourly wage of each bartender, I’ve always wondered why bars consistently have people waiting.

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How the taste of wine is described often reads like a poem: “full-bodied and rich but not heavy, high in alcohol, yet neither acidic nor tannic, with substantial black cherry flavor despite its delicacy...” Flowers and fruits are commonly used as descriptors, meant to help drinkers understand the flavors in a glass of wine. This poetry reflects that some consider the conversion of fruit to wine be an art form.

Yet...

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Most people who have taken a statistics class, whether it be Six Sigma or a college course or elsewhere, learned about the assumptions from which each test was developed. And boy are there a lot of assumptions!

Chances are a rather large and complicated flowchart was presented to help students navigate to the right hypothesis test – in my original course the chart was so big it had to be printed on 11x17 paper and...

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Choosing the correct linear regression model can be difficult. Trying to model it with only a sample doesn’t make it any easier. In this post, we'll review some common statistical methods for selecting models, complications you may face, and provide some practical advice for choosing the best regression model.

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Great stories others want to hear. Common challenges we have all faced before (or might even be facing right now). Discovering new tools in Minitab software as shared by peers. Engaging walkthroughs of finding insights in your data, and recommendations on how to act on them. All packed into a few days of learning and fun.

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A score by the dominant left foot. Great passes into the penalty area. The 4-4-2 or 4-3-3 formation. The controversial yellow and red cards. The curse of penalties. There is something for everyone to enjoy in this month of world-class football.

According to a recent article on BBC, England has 4% chance to win the World Cup 2018. This is based on calculation using computer simulations.  Points are awarded for each...

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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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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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