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Statistics Help

Blog posts and articles offering tips and advice about statistics and data analysis, especially for improving quality.

As someone who has collected and analyzed real data for a living, the idea of using simulated data for a Monte Carlo simulation sounds a bit odd. How can you improve a real product with simulated data? In this post, I’ll help you understand the methods behind Monte Carlo simulation and walk you through a simulation example using Companion by Minitab. Companion by Minitab is a software platform that... Continue Reading
Grocery shopping. For some, it's the most dreaded household activity. For others, it's fun, or perhaps just a “necessary evil.” Personally, I enjoy it! My co-worker, Ginger, a content manager here at Minitab, opened my eyes to something that made me love grocery shopping even more: she shared the data behind her family’s shopping trips. Being something of a data nerd, I really geeked out over the... Continue Reading

7 Deadly Statistical Sins Even the Experts Make

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If you regularly perform regression analysis, you know that R2 is a statistic used to evaluate the fit of your model. You may even know the standard definition of R2: the percentage of variation in the response that is explained by the model. Fair enough. With Minitab Statistical Software doing all the heavy lifting to calculate your R2 values, that may be all you ever need to know. But if you’re... Continue Reading
Everyone who analyzes data regularly has the experience of getting a worksheet that just isn't ready to use. Previously I wrote about tools you can use to clean up and eliminate clutter in your data and reorganize your data.  In this post, I'm going to highlight tools that help you get the most out of messy data by altering its characteristics. Know Your Options Many problems with data don't become... Continue Reading
In Part 1 of this blog series, I compared Six Sigma to a diamond because both are valuable, have many facets and have withstood the test of time. I also explained how the term “Six Sigma” can be used to summarize a variety of concepts, including philosophy, tools, methodology, or metrics. In this post, I’ll explain short/long-term variation and between/within-subgroup variation and how they help... 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
In my last post, I wrote about making a cluttered data set easier to work with by removing unneeded columns entirely, and by displaying just those columns you want to work with now. But too much unneeded data isn't always the problem. What can you do when someone gives you data that isn't organized the way you need it to be?   That happens for a variety of reasons, but most often it's because the... Continue Reading
B'gosh n' begorrah, it's St. Patrick's Day today! The day that we Americans lay claim to our Irish heritage by doing all sorts of things that Irish people never do. Like dye your hair green. Or tell everyone what percentage Irish you are. Despite my given name, I'm only about 15% Irish. So my Irish portion weighs about 25 pounds. It could be the portion that hangs over my belt due to excess potatoes... Continue Reading
In its industry guidance to companies that manufacture drugs and biological products for people and animals, the Food and Drug Administration (FDA) recommends three stages for process validation: Process Design, Process Qualification, and Continued Process Verification. In this post, we we will focus on that third stage. Stage 3: Continued Process Verification Per the FDA guidelines, the goal of... Continue Reading
People can make mistakes when they test a hypothesis with statistical analysis. Specifically, they can make either Type I or Type II errors. As you analyze your own data and test hypotheses, understanding the difference between Type I and Type II errors is extremely important, because there's a risk of making each type of error in every analysis, and the amount of risk is in your control.    So if... Continue Reading
Welcome to the Hypothesis Test Casino! The featured game of the house is roulette. But this is no ordinary game of roulette. This is p-value roulette! Here’s how it works: We have two roulette wheels, the Null wheel and the Alternative wheel. Each wheel has 20 slots (instead of the usual 37 or 38). You get to bet on one slot. What happens if the ball lands in the slot you bet on? Well, that depends... Continue Reading
Like many, my introduction to 17th-century French philosophy came at the tender age of 3+. For that is when I discovered the Etch-a-Sketch®, an entertaining ode to Descartes' coordinate plane. Little did I know that the seemingly idle hours I spent doodling on my Etch-a-Sketch would prove to be excellent training for the feat that I attempt today: plotting an Empirical Cumulative Distribution... Continue Reading
A recent discussion on the Minitab Network on LinkedIn pertained to the I-MR chart. In the course of the conversation, a couple of people referred to it as "The Swiss Army Knife of control charts," and that's a pretty great description. You might be able to find more specific tools for specific applications, but in many cases, the I-MR chart gets the job done quite adequately. When you're... Continue Reading
Right now I’m enjoying my daily dose of morning joe. As the steam rises off the cup, the dark rich liquid triggers a powerful enzyme cascade that jump-starts my brain and central nervous system, delivering potent glints of perspicacity into the dark crevices of my still-dormant consciousness. Feels good, yeah! But is it good for me? Let’s see what the studies say… Drinking more than 4 cups of coffee... Continue Reading
Statistics can be challenging, especially if you're not analyzing data and interpreting the results every day. Statistical software makes things easier by handling the arduous mathematical work involved in statistics. But ultimately, we're responsible for correctly interpreting and communicating what the results of our analyses show. The p-value is probably the most frequently cited statistic. We... 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
by Rehman Khan, guest blogger There are many articles giving Minitab tips already, so to be different I have done mine in the style of my books, which use example-based learning. All ten tips are shown using a single example. If you don’t already know these 10 tips you will get much more benefit if you work along with the example. You don’t need to download any files to work along—although, if you... 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
Genichi Taguchi is famous for his pioneering methods of robust quality engineering. One of the major contributions that he made to quality improvement methods is Taguchi designs. Designed experiments were first used by agronomists during the last century. This method seemed highly theoretical at first, and was initially restricted to agronomy. Taguchi made the designed experiment approach more... Continue Reading
In its industry guidance to companies that manufacture drugs and biological products for people and animals, the Food and Drug Administration (FDA) recommends three stages for process validation. While my last post covered statistical tools for the Process Design stage, here we will focus on the statistical techniques typically utilized for the second stage, Process Qualification. Stage 2: Process... Continue Reading