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Statistics

Blog posts and articles about statistical principles in quality improvement methods like Lean and Six Sigma.

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 multifaceted Editor menu in Minitab Statistical Software is just as essential. Minitab’s Dynamic Editor Menu Whether you’re... Continue Reading
It's a very exciting time at Minitab's offices around the world because we've just announced the availability of Minitab® 18 Statistical Software. Data is everywhere today, but to use it to make sound, strategic business decisions, you need to have tools that turn that data into knowledge and insights. We've designed Minitab 18 to do exactly that.  We've incorporated a lot of new features, made some... Continue Reading

7 Deadly Statistical Sins Even the Experts Make

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by Dan Wolfe, guest blogger How would you measure a hole that was allowed to vary one tenth the size of a human hair? What if the warmth from holding the part in your hand could take the measurement from good to bad? These are the types of problems that must be dealt with when measuring at the micron level. As a Six Sigma professional, that was the challenge I was given when Tenneco entered into... Continue Reading
Control charts are excellent tools for looking at data points that seem unusual and for deciding whether they're worthy of investigation. If you use control charts frequently, then you're used to the idea that if certain subgroups reflect temporary abnormalities, you can leave them out when you calculate your center line and control limits. If you include points that you already know are... Continue Reading
Before cutting an expensive piece of granite for a countertop, a good carpenter will first confirm he has measured correctly. Acting on faulty measurements could be costly. While no measurement system is perfect, we rely on such systems to quantify data that help us control quality and monitor changes in critical processes. So, how do you know whether the changes you see are valid and not just the... Continue Reading
The 1949 film A Connecticut Yankee in King Arthur's Court includes the song “Busy Doing Nothing,” and this could be written about the Null Hypothesis as it is used in statistical analyses.  The words to the song go: We're busy doin' nothin'Workin' the whole day through Tryin' to find lots of things not to do And that summarises the role of the Null Hypothesis perfectly. Let me explain why. What's... Continue Reading
Rare events inherently occur in all kinds of processes. In hospitals, there are medication errors, infections, patient falls, ventilator-associated pneumonias, and other rare, adverse events that cause prolonged hospital stays and increase healthcare costs.  But rare events happen in many other contexts, too. Software developers may need to track errors in lines of programming code, or a quality... Continue Reading
For the majority of my career, I've had the opportunity to speak at conferences and other events somewhat regularly. I thought some of my talks were pretty good, and some were not so good (based on ratings, my audiences didn't always agree with either—but that's a topic for another post). But I would guess that well over 90% of the time, my proposals were accepted to be presented at the... Continue Reading
Users often contact Minitab technical support to ask how the software calculates the control limits on control charts. A frequently asked question is how the control limits are calculated on an I-MR Chart or Individuals Chart. If Minitab plots the upper and lower control limits (UCL and LCL) three standard deviations above and below the mean, why are the limits plotted at values other than 3 times... Continue Reading
As a member of Minitab's Technical Support team, I get the opportunity to work with many people creating control charts. They know the importance of monitoring their processes with control charts, but many don’t realize that they themselves could play a vital role in improving the effectiveness of the control charts.   In this post I will show you how to take control of your charts by using Minitab... Continue Reading
One of the most memorable presentations at the inaugural Minitab Insights conference reminded me that data analysis and quality improvement methods aren't only useful in our work and businesses: they can make our home life better, too.  The presenter, a continuous improvement training program manager at an aviation company in the midwestern United States, told attendees how he used Minitab... Continue Reading
One highlight of writing for and editing the Minitab Blog is the opportunity to read your responses and answer your questions. Sometimes, to my chagrin, you point out that we've made a mistake. However, I'm particularly grateful for those comments, because it permits us to correct inadvertent errors.  I feared I had an opportunity to fix just such an error when I saw this comment appear on one of... Continue Reading
"Data! Data! Data! I can't make bricks without clay."  — Sherlock Holmes, in Arthur Conan Doyle's The Adventure of the Copper Beeches Whether you're the world's greatest detective trying to crack a case or a person trying to solve a problem at work, you're going to need information. Facts. Data, as Sherlock Holmes says.  But not all data is created equal, especially if you plan to analyze as part of... Continue Reading
As someone who has collected and analyzed real data for a living, the idea of using simulated data for a Monte Carlo simulation sounds a bit odd. How can you improve a real product with simulated data? In this post, I’ll help you understand the methods behind Monte Carlo simulation and walk you through a simulation example using Companion by Minitab. Companion by Minitab is a software platform that... Continue Reading
Choosing the right type of subgroup in a control chart is crucial. In a rational subgroup, the variability within a subgroup should encompass common causes, random, short-term variability and represent “normal,” “typical,” natural process variations, whereas differences between subgroups are useful to detect drifts in variability over time (due to “special” or “assignable” causes). Variation within... Continue Reading
Have you ever tried to install ventilated shelving in a closet?  You know: the heavy-duty, white- or gray-colored vinyl-coated wire shelving? The one that allows you to get organized, more efficient with space, and is strong and maintenance-free? Yep, that’s the one. Did I mention this stuff is strong?  As in, really hard to cut?  It seems like a simple 4-step project. Measure the closet, go the... Continue Reading
Grocery shopping. For some, it's the most dreaded household activity. For others, it's fun, or perhaps just a “necessary evil.” Personally, I enjoy it! My co-worker, Ginger, a content manager here at Minitab, opened my eyes to something that made me love grocery shopping even more: she shared the data behind her family’s shopping trips. Being something of a data nerd, I really geeked out over the... Continue Reading
If you regularly perform regression analysis, you know that R2 is a statistic used to evaluate the fit of your model. You may even know the standard definition of R2: the percentage of variation in the response that is explained by the model. Fair enough. With Minitab Statistical Software doing all the heavy lifting to calculate your R2 values, that may be all you ever need to know. But if you’re... Continue Reading
In Parts 1 and 2 of Gauging Gage we looked at the numbers of parts, operators, and replicates used in a Gage R&R Study and how accurately we could estimate %Contribution based on the choice for each.  In doing so, I hoped to provide you with valuable and interesting information, but mostly I hoped to make you like me.  I mean like me so much that if I told you that you were doing... Continue Reading
Earlier, I wrote about the different types of data statisticians typically encounter. In this post, we're going to look at why, when given a choice in the matter, we prefer to analyze continuous data rather than categorical/attribute or discrete data.  As a reminder, when we assign something to a group or give it a name, we have created attribute or categorical data.  If we count something, like... Continue Reading