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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.

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 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

7 Deadly Statistical Sins Even the Experts Make

Do you know how to avoid them?

Get the facts >
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
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 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
Have you ever wanted to know the odds of something happening, or not happening?  It's the kind of question that students are frequently asked to calculate by hand in introductory statistics classes, and going through that exercise is a good way to become familiar with the mathematical formulas the underlie probability (and hence, all of statistics).  But let's be honest: when class is over, most... 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
T'was the season for toys recently, and Christmas day found me playing around with a classic, the Etch-a-Sketch. As I noodled with the knobs, I had a sudden flash of recognition: my drawing reminded me of the Empirical CDF Plot in Minitab Statistical Software. Did you just ask, "What's a CDF plot? And what's so empirical about it?" Both very good questions. Let's start with the first, and we'll... Continue Reading
The language of statistics is a funny thing, but there usually isn't much to laugh at in the consequences that can follow when misunderstandings occur between statisticians and non-statisticians. We see these consequences frequently in the media, when new studies—that usually contradict previous ones—are breathlessly related, as if their findings were incontrovertible facts. Similar, though less... 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
If you’re familiar with Lean Six Sigma, then you’re familiar with DMAIC. DMAIC is the acronym for Define, Measure, Analyze, Improve and Control. This proven problem-solving strategy provides a structured 5-phase framework to follow when working on an improvement project. This is the first post in a five-part series that focuses on the tools available in Minitab Statistical Software that are most... Continue Reading
Dear Readers, As 2016 comes to a close, it’s time to reflect on the passage of time and changes. As I’m sure you’ve guessed, I love statistics and analyzing data! I also love talking and writing about it. In fact, I’ve been writing statistical blog posts for over five years, and it’s been an absolute blast. John Tukey, the renowned statistician, once said, “The best thing about being a statistician... Continue Reading
This week we’re celebrating the annual Thanksgiving holiday in the United States, which is not only a good time to reflect on the things we’re grateful for, but it’s also a good time to stuff yourself with turkey, mashed potatoes, green bean casserole, and the usual suspects that find their way to the Thanksgiving table! While I’m of course very thankful for my family, friends, home, etc., I’m also... Continue Reading
In this day and age, it’s not uncommon that data entry errors occur in data sets that are so large that looking for and correcting the errors by hand is impractical. Fortunately, Minitab includes tools that make it easy to get your data into shape, so that you can proceed to getting the answers you need. Let’s say, for example, that you were going to look at the Global Wood Density Database. It’s... Continue Reading
At the inaugural Minitab Insights Conference in September, presenters Benjamin Turcan and Jennifer Berner discussed how to present data effectively. Among the considerations they discussed was choosing the right graph. Different graphs are good for different things. Of course, opinions about which graph is best can, and do, differ. Dotplot devotees might decide that they are demonstrably... Continue Reading
In Part 1 of this blog series, I wrote about how statistical inference uses data from a sample of individuals to reach conclusions about the whole population. That’s a very powerful tool, but you must check your assumptions when you make statistical inferences. Violating any of these assumptions can result in false positives or false negatives, thus invalidating your results.  The common data... Continue Reading
Statistical inference uses data from a sample of individuals to reach conclusions about the whole population. It’s a very powerful tool. But as the saying goes, “With great power comes great responsibility!” When attempting to make inferences from sample data, you must check your assumptions. Violating any of these assumptions can result in false positives or false negatives, thus invalidating... Continue Reading