Weibull Analysis

Blog posts and articles about using Weibull distribution analysis in statistics and quality improvement.

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
With another Halloween almost upon us, here's a look back at some of the posts we've written about this holiday specifically, and about various creepy things in general. I hope that you enjoy this roundup of 13 scary statistics posts...and that they won't keep you up at night! 1. How to Make Minitab Wear a Halloween Costume As Halloween nears, you can customize your Minitab interface to match the... Continue Reading



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I thought 3 posts would capture all the thoughts I had about B10 Life. That is, until this question appeared on the Minitab LinkedIn group: In case you missed it, my first post, How to Calculate B10 Life with Statistical Software, explains what B10 life is and how Minitab calculates this value. My second post, How to Calculate BX Life, Part 2, shows how to compute any BX life in Minitab. But... Continue Reading
Reliability and survival analysis is used most frequently in manufacturing. Companies use these methods to estimate the proportion of units that will fail within, or survive beyond, a given period of time. But could these reliability and survival analysis techniques prove useful in a zombie apocalypse, too? Today's blog post explores that chilling scenario.  Think. This is what Zachary is telling... 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
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
Over the last year or so I’ve heard a lot of people asking, “How can I calculate B10 life in Minitab?” Despite being a statistician and industrial engineer (mind you, one who has never been in the field like the customers asking this question) and having taken a reliability engineering course, I’d never heard of B10 life. So I did some research. The B10 life metric originated in the ball and roller... Continue Reading
Previously, I’ve written about when to choose nonlinear regression and how to model curvature with both linear and nonlinear regression. Since then, I’ve received several comments expressing confusion about what differentiates nonlinear equations from linear equations. This confusion is understandable because both types can model curves. So, if it’s not the ability to model a curve, what isthe... Continue Reading
There is more than just the p value in a probability plot—the overall graphical pattern also provides a great deal of useful information. Probability plots are a powerful tool to better understand your data. In this post, I intend to present the main principles of probability plots and focus on their visual interpretation using some real data. In probability plots, the data density distribution... Continue Reading
We're frequently asked whether Minitab has been validated by the U.S. Food and Drug Administration (FDA) for use in the pharmaceutical and medical device industries. Minitab does extensive testing to validate our software internally, but Minitab’s statistical software is not—and cannot be—FDA-validated out-of-the-box. Nobody's can. It is a common misconception that software vendors can go through a... Continue Reading
Over on the Indium Corporation's blog, Dr. Ron Lasky has been sharing some interesting ideas about using the Weibull distribution in electronics manufacturing. For instance, check out this discussion of how dramatically an early first-failure can affect an analysis of a part or component (in this case, an alloy used to solder components to a circuit board).  This got me thinking again about all the... Continue Reading
  “Shall I compare thee to a standard normal distribution?   Thou art more symmetric and more bell-shaped…”  — Melvin Shakespeare (William’s lesser-known statistician brother) The Greek philosopher Aristotle believed that symmetry was one of the primary elements of the universal ideal of beauty. Over 2000 years later, emerging research seems to bear him out.  Studies suggest we tend to be more... Continue Reading
In college I had a friend who could go anywhere and fit right in. He'd have lunch with a group of professors, then play hacky-sack with the hippies in the park, and later that evening he'd hang out with the local bikers at the toughest bar in the city. Next day he'd play pickup football with the jocks before going to an all-night LAN party with his gamer pals. On an average weekend he might catch... Continue Reading
In my previous post, you learned how to prepare your data for capability analysis in Minitab. Now let's see where we need to go in the statistical software to run the correct Capability Analysis. When it comes to capability analysis, Minitab offers a few different choices. We offer Normal Capability Analysis for when your data follow a normal distribution. If your data follow a different... Continue Reading
Recently I've been refreshing my knowledge of reliability analysis, which is the use of data to assess a product's ability to perform over time. Quality engineers typically use reliability analysis to predict the likelihood that a certain percentage of products will fail over a given amount of time.    Statistical software will do the calculations involved in a reliability analysis, but there's a... Continue Reading
My wife and I are expecting a baby girl soon—very soon, in fact, as in "Will this blog post be published before the baby is born?" soon. The due date given is May 19th, but we stat geeks know that a point estimate just isn't good enough...we want probability intervals that reflect the uncertainty in the data. I found a chart that lets me know the number of babies born to "spontaneous labor" by each... Continue Reading
In my last post, I talked about the danger of excluding interactions between factors in ANOVA and DOE models. Let’s now look at what can happen if you exclude an important factor altogether. Warning: misleading high p-value up ahead... Minitab regularly hosts webinarson different statistical topics. Let’s suppose we want to evaluate if certain webinar topics are more popular than others, so we... Continue Reading
Many statistical analyses require an assumption of normality. In cases when your data are not normal, sometimes you can apply a function to make your data approximately normal so that you can complete your analysis. If you've seen any of the Transformers movies, you know that these extraordinary robots can, with some Hollywood magic, turn themselves into apparently normal items like cars... Continue Reading
In my previous post, we identified the distribution of the body fat data. Today, we're going to explore several benefits of knowing the distribution, with a special emphasis on creating informative graphs! After all, if you are not sure what a specific distribution with such and such parameters looks like, a graph gives you the picture! Using the Distribution Information So far, we have identified... Continue Reading
I love all data, whether it’s normally distributed or downright bizarre. However, many people are more comfortable with the symmetric, bell-shaped curve of a normal distribution. It is not as intuitive to understand a Gamma distribution, with its shape and scale parameters, as it is to understand the familiar Normal distribution with its mean and standard deviation. However, it's a fact of life... Continue Reading