Tips and Techniques for Statistics and Quality Improvement

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

As we collect more and more observational data from our processes, we might need new tools to provide meaningful insights. You can add modern-day machine learning techniques alongside traditional statistical tools to analyze, improve and control your processes. Let's take a look at an example that starts with binary logistic regression and ends with Classification and Regression Trees (CART®).

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It’s hard for Master Black Belt Brian Mapani to contain himself when he introduces his company and how he found the ingredients for successful continuous improvement. It’s understandable too. They saved $35 million by making a $1 million investment into their Lean Six Sigma program.

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Operational excellence and continuous improvement are critical to organizational success now more than ever. And one of the biggest challenges is getting buy-in from the top. Without validation and reinforcement it’s difficult for initiatives to be taken seriously. Why are key stakeholders holding out? Check out our infographic to learn more.

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Were you one of the 300+ lucky practitioners, data analysts, statisticians, improvement advisers, program managers, engineers, clinical directors, coordinators and quality professionals who attended the 2019 Minitab Insights Global Conference this past fall? 

Don’t worry if you were unable to join — with the help of our expert Jenn Atlas, we’ve rounded up the 5 Key Challenges and Learnings you need to know.

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Did you know that over 790 million gallons of wine were consumed in the US in 2016? That's a lot of wine — roughly 3,950 million bottles of wine to be exact! Wine production shows no signs of slowing down either with the number of US wineries increasing by over 50% since 2009 to a total of 10,043 wineries in 2019, however Italy, France and Spain still take the title of top three wine producing countries globally....

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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 Variability Chart.

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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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Colin Noone reveals that improvement activities have delivered over £2.6bn validated savings over 15 years at Rolls-Royce plc. With over 40 years experience at the power generation engineering company he is enthusiastic to share his takeaways with the Minitab community.

Colin is the company's Global Master Black Belt for Methods & Capability. Next month he is speaking at the Minitab Insights event in the UK, part of...

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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...

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The regulatory authorities worldwide largely driven by the Federal Drugs Administration in the U.S and its European counterpart, are making increasing demands in the interest of patient safety.

Pharmaceutical companies and organizations in the health sector are to apply more complete and complex techniques mainly for process validation but also for the monitoring and the evaluation of the performance of production...

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