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Tips and Techniques for Statistics and Quality Improvement

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

We use statistics to arm ourselves with more information. That information allows us to make more informed decisions. And the sooner we can obtain this information, the better. For example, suppose one of your manufacturing machines starts to malfunction and makes your products out of spec. You don't want to wait until the product reaches customers before you discover this information. Then it's... Continue Reading
Did you ever wonder why statistical analyses and concepts often have such weird, cryptic names? One conspiracy theory points to the workings of a secret committee called the ICSSNN. The International Committee for Sadistic Statistical Nomenclature and Numerophobia was formed solely to befuddle and subjugate the masses. Its mission: To select the most awkward, obscure, and confusing name possible... Continue Reading

7 Deadly Statistical Sins Even the Experts Make

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Control charts are a fantastic tool. These charts plot your process data to identify common cause and special cause variation. By identifying the different causes of variation, you can take action on your process without over-controlling it. Assessing the stability of a process can help you determine whether there is a problem and identify the source of the problem. Is the mean too high, too low,... Continue Reading
Last time I touched on the subject of the greatest Super Bowl quarterback, I promised a multivariate analysis considering several different statistics. Let’s get right to a factor analysis. Getting Ready for Factor Analysis One purpose of factor analysis is to identify underlying factors that you can’t measure directly. These factors explain the variation of many different variables in fewer... Continue Reading
Going into Saturday, Nebraska was 0-5 in games decided by 7 points or less and Michigan State was 4-0 in games decided by 7 points or less. You'll often hear sports analysts use this as proof that one team chokes under the pressure and the other team knows how to win in the clutch. But in reality, the result in close games can have just as much to do with luck as it can skill. Consider the formula... Continue Reading
Don't be a grumpy cat when something on your capability report doesn't smell right. After pressing that OK button to run your analysis, allow your inner cat to understand how and why certain statistics are being used. To help you along, here are some capability issues that customers have brought up recently. Cp is missing You’ve generated a capability analysis report with the Johnson transformation... Continue Reading
By Matthew Barsalou, guest blogger A problem must be understood before it can be properly addressed. A thorough understanding of the problem is critical when performing a root cause analysis (RCA) and an RCA is necessary if an organization wants to implement corrective actions that truly address the root cause of the problem. An RCA may also be necessary for process improvement projects; it is... Continue Reading
I have two young children, and I work full-time, so my adult TV time is about as rare as finding a Kardashian-free tabloid.  So I can’t commit to just any TV show. It better be a good one. I was therefore extremely excited when Netflix analyzed viewer data to find out at what point watchers get hooked on the first season of various shows. Specifically, they identified the episode at which 70% of... Continue Reading
4th and 1. It's a situation where the Big Ten 4th down calculator will never say to kick (unless, of course, it's the end of the game and a field goal will tie or take the lead). But what would it take to have the statistics suggest a punt? The key here is how far the punt travels. Last year the average Big Ten punt traveled about 40 yards. Using this value, in your own territory you'll score... Continue Reading
Easy access to the right tools makes any task easier. That simple idea has made the Swiss Army knife essential for adventurers: just one item in your pocket gives you instant access to dozens of tools when you need them.   If your current adventures include analyzing data, the Editor menu in Minitab 17 is just as essential. Minitab’s Dynamic Editor Menu Any job goes more smoothly when you have easy... Continue Reading
Did you know that November is World Quality Month? The American Society for Quality is once again heading up this year’s festivities. Throughout the month of November, ASQ will be promoting the use of quality tools in businesses, communities, and institutions all over the world. You can check it out at http://asq.org/world-quality-month/. Here at Minitab, we’re also pretty excited about World... Continue Reading
I generally consider myself old-fashioned. I’m not particularly different on Halloween, where I dress up, pass out candy, sit down in front of the television to watch "It’s the Great Pumpkin, Charlie Brown" on ABC, and read Minitab blog posts from Halloweens past. But some younger folks have told me that I’m missing out, so I’m trying to broaden my horizons to include YouTube. I want to use data... Continue Reading
Since it's the Halloween season, I want to share how a classic horror film helped me get a handle on an extremely useful statistical distribution.  The film is based on John W. Campbell's classic novella "Who Goes There?", but I first became  familiar with it from John Carpenter's 1982 film The Thing.   In the film, researchers in the Antarctic encounter a predatory alien with a truly frightening... Continue Reading
As Halloween approaches, you are probably taking the necessary steps to protect yourself from the various ghosts, goblins, and witches that are prowling around. Monsters of all sorts are out to get you, unless they’re sufficiently bribed with candy offerings! I’m here to warn you about a ghoul that all statisticians and data scientists need to be aware of: phantom degrees of freedom. These phantoms... Continue Reading
Nebraska lost another close game, teams continue to incorrectly punt to Ohio State on 4th and short, and Northwestern keeps making terrible 4th down decisions. Another regular week for the Big Ten 4th down calculator. In case you haven't read the earlier entries in this series, I've used Minitab Statistical Software to create a model to determine the correct 4th down decision in Big Ten Conference... Continue Reading
In Part 5 of our series, we began the analysis of the experiment data by reviewing analysis of covariance and blocking variables, two key concepts in the design and interpretation of your results. The 250-yard marker at the Tussey Mountain Driving Range, one of the locations where we conducted our golf experiment. Some of the golfers drove their balls well beyond this 250-yard maker during a few of... Continue Reading
By Matthew Barsalou, guest blogger Teaching process performance and capability studies is easier when actual process data is available for the student or trainee to practice with. As I have previously discussed at the Minitab Blog, a catapult can be used to generate data for a capability study. My last blog on using a catapult for this purspose was several years ago, so I would like to revisit... Continue Reading
People who are ill frequently need medication. But if they miss a dose, or receive the wrong medication—or even get the wrong dose of the right medication—the results can be disastrous.  So medical professionals have a lot at stake in making sure patients get the right medicine, in the right amount, at the right time. But hospitals and other medical facilities are complex systems, and mistakes do... Continue Reading
This week is National Healthcare Quality Week, started by the National Association for Healthcare Quality to increase awareness of healthcare quality programs and to highlight the work of healthcare quality professionals and their influence on improved patient care outcomes. In honor of the celebration, I wanted to point you to a few case studies featuring Minitab customers in the healthcare field... Continue Reading
In Part 3 of our series, we decided to test our 4 experimental factors, Club Face Tilt, Ball Characteristics, Club Shaft Flexibility, and Tee Height in a full factorial design because of the many advantages of that data collection plan. In Part 4 we concluded that each golfer should replicate their half fraction of the full factorial 5 times in order to have a high enough power to detect... Continue Reading