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Weibull Analysis

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

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
We all seem to have our favorite statistical or quality improvement tool. Jim Frost wrote a tribute to regression analysis. Dawn Keller seems to enjoy control charts. Eston Martz discusses reliability analysis and the Weibull distribution pretty regularly. So, I started thinking … what’s my favorite quality tool? I’ve always been drawn to process mapping, or what's sometimes referred to as ‘flow... 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 reflecting the uncertainty in the data. I found a chart that lets me know the number of babies born to "spontaneous labor" by... 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
What, it’s still not March? Blasted February, why won't you just end already! Oh well, at least it gives us time for some more data analysis. In my last post, I used Minitab’s Fitted Line Plot to create a regression model that predicted the probability of a home team winning a basketball game based on the difference in ranks between the two teams. This model had an r-squared value of 95.2%, which... Continue Reading
Manufacturers need to make items that meet a customer’s standards, or they’ll soon be out of business. That’s why quality engineers devote a good deal of time to making sure that processes are able to meet those standards.  The first step is to make sure your process is stable. After all, you can’t predict the performance of an unstable process. But you can predict and improve on a stable process.  I... Continue Reading