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Statistics

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

The first summer blockbuster of 2015 was released two weeks ago—The Avengers: Age of Ultron. The first Avengers film featured a pretty well known cast of superheroes (if, of course, you’re a superhero fan). However, in the 40-year run of the Avengers comic book, that team has evolved to keep the material fresh and to allow some characters to go their solo ways. I want to use Minitab's statistical... Continue Reading
In previous posts, I discussed the results of a recycling project done by Six Sigma students at Rose-Hulman Institute of Technology last spring. (If you’re playing catch up, you can read Part I and Part II.) The students did an awesome job reducing the amount of recycling that was thrown into the normal trash cans across all of the institution’s academic buildings. At the end of the spring... Continue Reading
By Erwin Gijzen, Guest Blogger In my previous post, we assessed the out-of-spec level for a process with capability analysis and visualized process variability using a control chart. Our goal is to reduce variability, but when a process has a multitude of categorical and continuous variables, identifying root causes can be a huge challenge. Analyzing covariance—using the statistical technique... Continue Reading
by Erwin Gijzen, Guest Blogger People who work in quality improvement know that the root causes of quality issues are hard to find. A typical production process can contain hundreds of potential causes. Additionally, companies often produce products with multiple quality requirements, such as dimensions, surface appearance, and impact resistance. With so many variables, it’s no wonder many companies... Continue Reading
by Matthew Barsalou, guest blogger.  The old saying “if it walks like a duck, quacks like a duck and looks like a duck, then it must be a duck” may be appropriate in bird watching; however, the same idea can’t be applied when observing a statistical distribution. The dedicated ornithologist is often armed with binoculars and a field guide to the local birds and this should be sufficient. A... Continue Reading
This week I'm at the American Society for Quality's World Conference on Quality and Improvement in Nashville, TN. The ASQ conference is a great opportunity to see how quality professionals are tackling problems in every industry, from beverage distribution to banking services.  Given my statistical bent, I like to see how companies apply tools like ANOVA, regression, and especially... 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
Banned! In February 2015, editor David Trafimow and associate editor Michael Marks of the Journal of Basic and Applied Social Psychology declared that the null hypothesis statistical testing procedure is invalid. They promptly banned P values, confidence intervals, and hypothesis testing from the journal. The journal now requires descriptive statistics and effect sizes. They also encourage large... 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
As a Minitab trainer, one of the most common questions I get from training participants is "what should I do when my data isn’t normal?" A large number of statistical tests are based on the assumption of normality, so not having data that is normally distributed typically instills a lot of fear. Many practitioners suggest that if your data are not normal, you should do a nonparametric version of... Continue Reading
The NBA playoffs are under way, and all eyes are on LeBron James to see if he can finally bring a championship to Cleveland. But one could argue that there is even a bigger storyline going on: whether Tim Duncan can equal Michael Jordan’s six NBA Championships. Duncan is currently in his 18th season in the NBA, and he is still playing at a very high level. Yet, he’s never in the conversation when... Continue Reading
Many of the things you need to monitor can be measured in a concrete, objective way, such as an item's weight or length. But, many important characteristics are more subjective, such as the collaborative culture of the workplace, or an individual's political outlook. A survey is an excellent way to measure these kinds of characteristics. To better understand a characteristic, a researcher asks... 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
A few times a year, the Bureau of Labor Statistics (BLS) publishes a Spotlight on Statistics Article. The first such article of 2015 recently arrived, providing analysis of trends in long-term unemployment.  Certainly an interesting read on its own, but some of the included data gives us a good opportunity to look at how thought can improve your regression analysis. Fortunately, Minitab Statistical... Continue Reading
In 1898, Russian economist Ladislaus Bortkiewicz published his first statistics book entitled Das Gesetz der keinem Zahlen, in which he included an example that eventually became famous for illustrating the Poisson distribution. Bortkiewicz researched the annual deaths by horse kicks in the Prussian Army from 1875-1984. Data was recorded from 14 different army corps, with one being the Guard... Continue Reading
As a member of Minitab's Technical Support team, I get the opportunity to work with many people using DOE (Design of Experiments). People often will call after they've already chosen their design, run the experiment, and identified the important factors in their process. But now what? They have to find the best settings, but with several factors and responses, what should they do? "I wish I had a... Continue Reading
In this series of posts, I show how hypothesis tests and confidence intervals work by focusing on concepts and graphs rather than equations and numbers.   Previously, I used graphs to show what statistical significance really means. In this post, I’ll explain both confidence intervals and confidence levels, and how they’re closely related to P values and significance levels. How to Correctly... Continue Reading
To choose the right statistical analysis, you need to know the distribution of your data. Suppose you want to assess the capability of your process. If you conduct an analysis that assumes the data follow a normal distribution when, in fact, the data are nonnormal, your results will be inaccurate. To avoid this costly error, you must determine the distribution of your data. So, how do you determine... Continue Reading
Imagine that you are watching a race and that you are located close to the finish line. When the first and fastest runners complete the race, the differences in times between them will probably be quite small. Now wait until the last runners arrive and consider their finishing times. For these slowest runners, the differences in completion times will be extremely large. This is due to the fact that... Continue Reading
This is a companion post for a series of blog posts about understanding hypothesis tests. In this series, I create a graphical equivalent to a 1-sample t-test and confidence interval to help you understand how it works more intuitively. This post focuses entirely on the steps required to create the graphs. It’s a fairly technical and task-oriented post designed for those who need to create the... Continue Reading