Tips and Techniques for Statistics and Quality Improvement

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

Greg Kinsey, Vice President at Hitachi, is the Keynote speaker at the new Minitab Insights Zurich and Minitab Insights Dublin Conferences next October and November. The conferences will bring together data-driven leaders from across European manufacturing to explore the new strategies, methods and tools for innovation and performance. Learn why you need to hear Greg’s view on the Future of Operational Excellence – and...

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Falk Huettman is a professor of wildlife ecology at the Institute of Arctic Biology, Biology and Wildlife Department at the University of Alaska Fairbanks. He uses machine learning extensively in his research.

How accurate is the location of an endangered Aleutian shield-fern specimen collected in Alaska in 1982? Research institutions and museums seek to provide the most accurate data possible to record the past and ...

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Bill Kahn runs the statistical modeling group for consumer banking at Bank of America. His team builds hundreds of models using a broad range of statistical and machine learning techniques. These models help ensure financial stability for individuals, enterprises, and communities throughout the country. Over the past few decades, Bill has led statistics groups at several Fortune 500 financial service, consulting, and...

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Machine learning as a tool in your analytical toolkit can help accelerate the discovery of insights in data that can create a more efficient manufacturing process and drive innovation. 

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Adam Russell is a Global Operations Master Black Belt, Tate & Lyle.

Tate & Lyle deploys Continuous Improvement (CI) tools, including Minitab and Salford Predictive Modeler (SPM), to address challenging engineering and manufacturing problems. Our company operates large-scale, continuous flow processes serving the Food & Beverage industry.

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The potential benefit of the data stored on servers is huge. Banks, insurance companies, telecom companies, manufacturers — in fact organizations from across all industries need to make good use of the data they own to improve their operations, better understand their customers and find competitive advantage.

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As we collect more and more observational data from our processes, we may need new tools to provide meaningful insights into this information. You can add modern-day machine learning techniques alongside traditional statistical tools to analyze, improve and control your processes.

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The convergence of the widespread deployment of low-cost sensors, cloud and greater compute power has brought together a multitude of connected devices which can monitor, collect, exchange, analyze and deliver insight like never before. Industry 4.0 (or Industrial Internet of Things) is transforming industries. This is especially true within manufacturing where many organizations are making investments into ‘smart...

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