Blog posts and articles with tips for doing ANOVA (Analysis of Variance), especially for quality improvement initiatives.

Back when I was an undergrad in statistics, I unfortunately spent an entire semester of my life taking a class, diligently crunching numbers with my TI-82, before realizing 1) that I was actually in an Analysis of Variance (ANOVA) class, 2) why I would want to use such a tool in the first place, and 3) that ANOVA doesn’t necessarily tell you a thing about variances. Fortunately, I've had a lot more... Continue Reading
By Matthew Barsalou, guest blogger A problem must be understood before it can be properly addressed. A thorough understanding of the problem is critical when performing a root cause analysis (RCA) and an RCA is necessary if an organization wants to implement corrective actions that truly address the root cause of the problem. An RCA may also be necessary for process improvement projects; it is... Continue Reading
As Halloween approaches, you are probably taking the necessary steps to protect yourself from the various ghosts, goblins, and witches that are prowling around. Monsters of all sorts are out to get you, unless they’re sufficiently bribed with candy offerings! I’m here to warn you about a ghoul that all statisticians and data scientists need to be aware of: phantom degrees of freedom. These phantoms... Continue Reading
In Part 5 of our series, we began the analysis of the experiment data by reviewing analysis of covariance and blocking variables, two key concepts in the design and interpretation of your results. The 250-yard marker at the Tussey Mountain Driving Range, one of the locations where we conducted our golf experiment. Some of the golfers drove their balls well beyond this 250-yard maker during a few of... Continue Reading
In Part 3 of our series, we decided to test our 4 experimental factors, Club Face Tilt, Ball Characteristics, Club Shaft Flexibility, and Tee Height in a full factorial design because of the many advantages of that data collection plan. In Part 4 we concluded that each golfer should replicate their half fraction of the full factorial 5 times in order to have a high enough power to detect... Continue Reading
With Speaker John Boehner resigning, Kevin McCarthy quitting before the vote for him to be Speaker, and a possible government shutdown in the works, the Freedom Caucus has certainly been in the news frequently! Depending on your political bent, the Freedom Caucus has caused quite a disruption for either good or bad.  Who are these politicians? The Freedom Caucus is a group of approximately 40... Continue Reading
You've collected a bunch of data. It wasn't easy, but you did it. Yep, there it is, right there...just look at all those numbers, right there in neat columns and rows. Congratulations. I hate to ask...but what are you going to do with your data? If you're not sure precisely what to do with the data you've got, graphing it is a great way to get some valuable insight and direction. And a good graph to... Continue Reading
Repeated measures designs don’t fit our impression of a typical experiment in several key ways. When we think of an experiment, we often think of a design that has a clear distinction between the treatment and control groups. Each subject is in one, and only one, of these non-overlapping groups. Subjects who are in a treatment group are exposed to only one type of treatment. This is the... Continue Reading
Ever use dental floss to cut soft cheese? Or Alka Seltzer to clean your toilet bowl? You can find a host of nonconventional uses for ordinary objects online. Some are more peculiar than others. Ever use ordinary linear regression to evaluate a response (outcome) variable of counts?  Technically, ordinary linear regression was designed to evaluate a a continuous response variable. A continuous... Continue Reading
To make objective decisions about the processes that are critical to your organization, you often need to examine categorical data. You may know how to use a t-test or ANOVA when you’re comparing measurement data (like weight, length, revenue, and so on), but do you know how to compare attribute or counts data? It easy to do with statistical software like Minitab.  One person may look at this bar... Continue Reading
Just 100 years ago, very few statistical tools were available and the field was largely unknown. Since then, there has been an explosion of tools available, as well as ever-increasing awareness and use of statistics.   While most readers of the Minitab Blog are looking to pick up new tools or improve their use of commonly-applied ones, I thought it would be worth stepping back and talking about one... Continue Reading
If you've read the first two parts of this tale, you know it started when I published a post that involved transforming data for capability analysis. When an astute reader asked why Minitab didn't seem to transform the data outside of the capability analysis, it revealed an oversight that invalidated the original analysis.  I removed the errant post. But to my surprise, the reader who helped me... Continue Reading
The line plot is an incredibly agile but frequently overlooked tool in the quest to better understand your processes. In any process, whether it's baking a cake or processing loan forms, many factors have the potential to affect the outcome. Changing the source of raw materials could affect the strength of plywood a factory produces. Similarly, one method of gluing this plywood might be better... Continue Reading
In my previous post, I showed you that the coefficients are different when choosing (-1,0,1) vs (1,0) coding schemes for General Linear Model (or Regression).  We used the two different equations to calculate the same fitted values. Here I will focus on showing what the different coefficients represent.  Let's use the data and models from the last blog post: We can display the means for each level... Continue Reading
Since Minitab 17 Statistical Software launched in February 2014, we've gotten great feedback from many people have been using the General Linear Model and Regression tools. But in speaking with people as part of Minitab's Technical Support team, I've found many are noticing that there are two coding schemes available with each. We frequently get calls from people asking how the coding scheme you... 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
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
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
In technical support, we often receive questions about Gage R&R and how Minitab calculates the amount of variation that is attributable to the various sources in a measurement system. This post will focus on how the variance components are calculated for a crossed Gage R&R using the ANOVA table, and how we can obtain the %Contribution, StdDev, Study Var and %Study Var shown in the Gage R&R output. ... Continue Reading