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Statistics Help

Blog posts and articles that offer tips about the statistics used in lean and six sigma quality improvement projects.

Do you recall my “putting the cart before the horse” analogy in part 1 of this blog series? The comparison is simple. We all, at times, put the cart before the horse in relatively innocuous ways, such as eating your dessert before you’ve eaten your dinner, or deciding what to wear before you’ve been invited to the party. But performing some tasks in the wrong order, such as running a statistical... Continue Reading
Analysis of variance (ANOVA) can determine whether the means of three or more groups are different. ANOVA uses F-tests to statistically test the equality of means. In this post, I’ll show you how ANOVA and F-tests work using a one-way ANOVA example. But wait a minute...have you ever stopped to wonder why you’d use an analysis of variance to determine whether means are different? I'll also show how... Continue Reading

7 Deadly Statistical Sins Even the Experts Make

Do you know how to avoid them?

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In statistics, t-tests are a type of hypothesis test that allows you to compare means. They are called t-tests because each t-test boils your sample data down to one number, the t-value. If you understand how t-tests calculate t-values, you’re well on your way to understanding how these tests work. In this series of posts, I'm focusing on concepts rather than equations to show how t-tests work.... Continue Reading
Did you know about the Minitab Network group on LinkedIn? It’s the one managed by Eston Martz, who also edits the Minitab blog. I like to see what the members are talking about, which recently got me into some discussions about Raman spectroscopy data. Not having much experience with Raman spectroscopy data, I thought I’d learn more about it and found the RRUFFTM Project. The idea is that if you... Continue Reading
T-tests are handy hypothesis tests in statistics when you want to compare means. You can compare a sample mean to a hypothesized or target value using a one-sample t-test. You can compare the means of two groups with a two-sample t-test. If you have two groups with paired observations (e.g., before and after measurements), use the paired t-test. How do t-tests work? How do t-values fit in? In this... Continue Reading
Five-point Likert scales are commonly associated with surveys and are used in a wide variety of settings. You’ve run into the Likert scale if you’ve ever been asked whether you strongly agree, agree, neither agree or disagree, disagree, or strongly disagree about something. The worksheet to the right shows what five-point Likert data look like when you have two groups. Because Likert item data are... Continue Reading
You have a column of categorical data. Maybe it’s a column of reasons for production downtime, or customer survey responses, or all of the reasons airlines give for those riling flight delays. Whatever type of qualitative data you may have, suppose you want to find the most common categories. Here are three different ways to do that: 1. Pareto Charts Pareto Charts easily help you separate the vital... Continue Reading
I’ve written about R-squared before and I’ve concluded that it’s not as intuitive as it seems at first glance. It can be a misleading statistic because a high R-squared is not always good and a low R-squared is not always bad. I’ve even said that R-squared is overrated and that the standard error of the estimate (S) can be more useful. Even though I haven’t always been enthusiastic about... Continue Reading
In statistics, there are things you need to do so you can trust your results. For example, you should check the sample size, the assumptions of the analysis, and so on. In regression analysis, I always urge people to check their residual plots. In this blog post, I present one more thing you should do so you can trust your regression results in certain circumstances—standardize the continuous... Continue Reading
If you need to assess process performance relative to some specification limit(s), then process capability is the tool to use. You collect some accurate data from a stable process, enter those measurements in Minitab, and then choose Stat > Quality Tools > Capability Analysis/Sixpack or Assistant > Capability Analysis. Now, what about sorting the data? I’ve been asked “why does Cpk change when I... Continue Reading
In the world of linear models, a hierarchical model contains all lower-order terms that comprise the higher-order terms that also appear in the model. For example, a model that includes the interaction term A*B*C is hierarchical if it includes these terms: A, B, C, A*B, A*C, and B*C. Fitting the correct regression model can be as much of an art as it is a science. Consequently, there's not always a... Continue Reading
If you perform linear regression analysis, you might need to compare different regression lines to see if their constants and slope coefficients are different. Imagine there is an established relationship between X and Y. Now, suppose you want to determine whether that relationship has changed. Perhaps there is a new context, process, or some other qualitative change, and you want to determine... Continue Reading
When you work in data analysis, you quickly discover an irrefutable fact: a lot of people just can't stand statistics. Some people fear the math, some fear what the data might reveal, some people find it deadly dull, and others think it's bunk. Many don't even really know why they hate statistics—they just do. Always have, probably always will.  Problem is, that means we who analyze data need to com... Continue Reading
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
Control charts are a fantastic tool. These charts plot your process data to identify common cause and special cause variation. By identifying the different causes of variation, you can take action on your process without over-controlling it. Assessing the stability of a process can help you determine whether there is a problem and identify the source of the problem. Is the mean too high, too low,... Continue Reading
Easy access to the right tools makes any task easier. That simple idea has made the Swiss Army knife essential for adventurers: just one item in your pocket gives you instant access to dozens of tools when you need them.   If your current adventures include analyzing data, the Editor menu in Minitab 17 is just as essential. Minitab’s Dynamic Editor Menu Any job goes more smoothly when you have easy... 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 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
While most of us work in Minitab Statistical Software using our preferred language, some need to share Minitab project files or present the results in a different language. Others among us just want to play around with the languages because playing around with Minitab is fun! Thankfully, Minitab offers our statistical softwarein eight languages, including English, French, German, Japanese, Korean,... 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