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Quality Improvement

Blog posts and articles about using statistics and data analysis to improve quality through methodologies such as Lean and Six Sigma.

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

7 Deadly Statistical Sins Even the Experts Make

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Step 3 in our DOE problem solving methodology is to determine how many times to replicate the base experiment plan. The discussion in Part 3 ended with the conclusion that our 4 factors could best be studied using all 16 combinations of the high and low settings for each factor, a full factorial. Each golfer will perform half of the sixteen possible combinations and each golfer’s data could stand as... Continue Reading
I read trade publications that cover everything from banking to biotech, looking for interesting perspectives on data analysis and statistics, especially where it pertains to quality improvement. Recently I read a great blog post from Tony Taylor, an analytical chemist with a background in pharmaceuticals. In it, he discusses the implications of the FDA's updated guidance for industry analytical... Continue Reading
Step 1 in our DOE problem-solving methodology is to use process experts, literature, or past experiments to characterize the process and define the problem. Since I had little experience with golf myself, this was an important step for me. This is not an uncommon situation. Experiment designers often find themselves working on processes that they have little or no experience with. For example, a... Continue Reading
You run a capability analysis and your Cpk is bad. Now what? First, let’s start by defining what “bad” is. In simple terms, the smaller the Cpk, the more defects you have. So the larger your Cpk is, the better. Many practitioners use a Cpk of 1.33 as the gold standard, so we’ll treat that as the gold standard here, too. Suppose we collect some data and run a capability analysis using Minitab Statisti... Continue Reading
As we broke for lunch, two participants in the training class began to discuss, debate, and finally fight over a fundamental task in golf—how to drive the ball the farthest off the tee. Both were avid golfers and had spent a great deal of time and money on professional instruction and equipment, so the argument continued through the lunch hour, with neither arguer stopping to eat. Several other... Continue Reading
Whatever industry you're in, you're going to need to buy supplies. If you're a printer, you'll need to purchase inks, various types of printing equipment, and paper. If you're in manufacturing, you'll need to obtain parts that you don't make yourself.  But how do you know you're making the right choice when you have multiple suppliers vying to fulfill your orders?  How can you be sure you're... 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
The difference between defects and defectives lets you answer questions like whether to use a P chart or a U chart in Minitab, so it’s a handy difference to be able to explain. Of course, if you’ve explained it enough times—or if someone’s explained it to you enough times—the whole thing can get a little tired. Fortunately, a new explanation of defects and defectives is one more way we... Continue Reading
Kappa statistics are commonly used to indicate the degree of agreement of nominal assessments made by multiple appraisers. They are typically used for visual inspection to identify defects. Another example might be inspectors rating defects on TV sets: Do they consistently agree on their classifications of scratches, low picture quality, poor sound?  Another application could be patients examined... Continue Reading
Before I joined Minitab, I worked for many years in Penn State's College of Agricultural Sciences as a writer and editor. I frequently wrote about food science and particularly food safety, as I regularly needed to report on the research being conducted by Penn State's food safety experts, and also edited course materials and bulletins for professionals and consumers about ensuring they had safe... Continue Reading
When data are collected in subgroups, it’s easy to understand how the variation can be calculated within each of the subgroups based the subgroup range or the subgroup standard deviation. When data is not collected in subgroups (so the subgroup size is 1), it may be a little less intuitive to understand how within-subgroup standard deviation is calculated.  How does Minitab Statistical Softwarecalcu... Continue Reading
I recently fielded an interesting question about the probability and survival plots in Minitab Statistical Software's Reliability/Survival menus: Is there a one-to-one match between the confidence interval points on a probability plot and the confidence interval points on survival plot at a specific percentile? Now, this may seem like an easy question, given that the probabilities on a survival plot... Continue Reading
All processes have some variation. Some variation is natural and nothing to be concerned about. But in other cases, there is unusual variation that may need attention.  By graphing process data against an upper and a lower control limit, control charts help us distinguish natural variation from special cause variation that we need to be concerned about. If a data point falls outside the limits on... 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
It’s usually not a good idea to rely solely on a single statistic to draw conclusions about your process. Do that, and you could fall into the clutches of the “duck-rabbit” illusion shown here: If you fix your eyes solely on the duck, you’ll miss the rabbit—and vice-versa. If you're using Minitab Statistical Software for capability analysis, the capability indices Cp and Cpk are good examples of... Continue Reading
A while back, I offered an overview of process capability analysis that emphasized the importance of matching your analysis to the distribution of your data. If you're already familiar with different types of distributions, Minitab makes it easy to identify what type of data you're working with, or to transform your data to approximate the normal distribution. But what if you're not so great with... Continue Reading
The Cp and Cpk are well known capability indices commonly used to ensure that a process spread is as small as possible compared to the tolerance interval (Cp), or that it stays well within specifications (Cpk). Yet another type of capability index exists: the Cpm, which is much less known and used less frequently. The main difference between the Cpm and the other capability indices is that the... Continue Reading
The two previous posts in this series focused on manipulating data using Minitab’s calculator and the Data menu. In this third and final post, we continue to explore helpful features for working with text data and will focus on some new features in Minitab 17.2’s Editor menu. Using the Editor Menu  The Editor menu is unique in that the options displayed depend on what is currently active... Continue Reading