Tips and Techniques for Statistics and Quality Improvement

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

Imagine your new car breaks down after driving 60 miles. The engine light turns on and your vehicle must now be towed to be serviced. This is not only a warranty issue but also a field problem due to lack of product reliability.

Reliability is defined as the quality of a product over time and statistically speaking it is the probability of a product not to fail during a defined period of time.

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When facing a problem, you've most likely heard the saying "take the bull by the horns." It's often also easier said than done.

COVID-19's economic repercussions have forced businesses worldwide to deal with the phenomenon that occurs in multi-level supply chains where orders at the end of the supply chain, close to the customer, are amplified with each additional supply chain actor. This is called the bullwhip effect.

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Length of stay, defined as the time between hospital admission and discharge measured in days, is an aspect of care that can be costly for most healthcare systems if not approached properly. Optimizing patient flow, on the other hand, facilitates beneficial treatment, minimal waiting, minimal exposure to risks associated with hospitalization, and efficient use of resources such as hospital beds, medical equipment and...

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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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Trying to understand customer or patient behavior can be challenging. Oftentimes, researchers’ use survey data and frequently analyze it using regression in Minitab Statistical Software. But when the outcome variable is categorical rather than quantitative, interpreting the results of a logistic regression is not very straightforward or intuitive.

Another option for analyzing survey data in Minitab? Tap into the...

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When the data science buzz began around a decade ago, creating a predictive model was complicated work that only skilled programmers could accomplish. Today, new tools and new techniques are shifting the focus from programming details to building models that are robust, scalable and focused on creating business value.

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We might not be able to observe the progressive loss of cognitive and intellectual abilities someone with dementia is experiencing from the outside, but healthcare clinicians can detect it when they observe their ability to bathe, groom or dress themselves deteriorate. Minitab consultant  and Insights 2019 speaker David Patrishkoff is researching how to help with the aid of Minitab software. 

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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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You now often see “Machine Learning” appearing along with “Big Data”, “AI” or “Internet of Things” in the discussion of the digital transformation of business.

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Greg Kinsey, Vice President at Hitachi, reveals how creative uses of the DMAIC process with digital transformation are helping factories to unlock the next level of process improvement. Greg is speaking at November's Minitab Insights Europe Conferences event in Dublin. 

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