Tips and Techniques for Statistics and Quality Improvement

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

Kevin Rudy

I write about how statistics can be used to help understand sports, but these techniques and tools have applications in quality improvement and any other endeavor that involves the analysis of data.
Kevin Rudy

There may not be a situation more perilous than being a character on Game of Thrones. Warden of the North, Hand of the King, and apparent protagonist of the entire series? Off with your head before the end of the first season! Last male heir of a royal bloodline? Here, have a pot of molten gold poured on your head! Invited to a wedding? Well, you probably know what happens at weddings in the show. 

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Predictions can be a tricky thing. Consider trying to predict the number rolled by 2 six-sided dice. We know that 7 is the most likely outcome. We know the exact probability each number has of being rolled. If we rolled the dice 100 times, we could calculate the expected value for the number of times each value would be rolled. However, even with all that information, we can't definitively predict the value of an...

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In week 16 of the 2016 NFL season, the Cleveland Browns were able to avoid going into the history books as only the second team to finish the season 0-16. They claimed their first and only win of the season after San Diego missed a last-second field goal. While they came very close to going winless, the statistics paint a very different picture of the odds of that occurrence. 

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The college football season is here, and this raises a very important question:

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The Olympic games are about to begin in Rio de Janeiro. Over the next 16 days, more than 11,000 athletes from 206 countries will be competing in 306 different events. That's the most events ever in any Olympic games. It's almost twice as many events as there were 50 years ago, and exactly three times as many as there were 100 years ago.

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When you perform a statistical analysis, you want to make sure you collect enough data that your results are reliable. But you also want to avoid wasting time and money collecting more data than you need. So it's important to find an appropriate middle ground when determining your sample size.

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For hundreds of years, people having been improving their situation by pulling themselves up by their bootstraps. Well, now you can improve your statistical knowledge by pulling yourself up by your bootstraps. Minitab Express has 7 different bootstrapping analyses that can help you better understand the sampling distribution of your data. 

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When it comes to statistical analyses, collecting a large enough sample size is essential to obtaining quality results. If your sample size is too small, confidence intervals may be too wide to be useful, linear models may lack necessary precision, and control charts may get so out of control that they become self-aware and rise up against humankind.

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Probability. It's really the heart and soul of most statistical analyses. Anytime you get a p-value, you're dealing with a probability. The probability is telling you how likely it was (or will be) for an event to occur. It has numerous applications across a wide variety of areas. But today I want to focus on the probability of a specific event.

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What is an interaction? It’s when the effect of one factor depends on the level of another factor. Interactions are important when you’re performing ANOVA, DOE, or a regression analysis. Without them, your model may be missing an important term that helps explain variability in the response!

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