Statistics

Blog posts and articles about statistical principles and their application in quality improvement methods such as Lean and Six Sigma.

If you’re a quality improvement expert, you already know that statistics can be a powerful tool in your quest to reduce the cost of poor quality and save money. But statistics might be even more powerful than you think—it may actually have helped someone win a lottery jackpot. According to Business Insider, a former mathematics professor with a Ph.D. in statistics has won the Texas lottery... Continue Reading
Riddle: What two tools in Minitab can be used to perform the same analysis on your data? Well, there are probably a few pairs that can be mentioned, but I am going to focus on Discriminant Analysis and Binary Logistic Regression.These tools can be used to predict group membership.  If we look at exh_mvar.mtw, located in Minitab’s sample data folder, we have the perfect data set to use. Here is a... Continue Reading

7 Deadly Statistical Sins Even the Experts Make

Do you know how to avoid them?

Lately, I've been thinking a lot about the "perfect" proportion. We’re adding a sunroom to our house and debating the best dimensions for the rectangular addition. Naturally, "the golden ratio" is an enticing option. Also called the Divine Proportion, the golden ratio has gotten a lot of buzz over the centuries. Its basis is simple yet profound. Take a line segment and divide it into two segments... Continue Reading
Adhering to the proper assumptions in any statistical analysis is very important. And there seems to be an assumption for everything. For this post, I’d like to clear up some confusion about one particular assumption for assessing normality. A data set is normally distributed when the data itself follows a uni-modal bell-shaped curve that is symmetric about its mean. This graph, created from the... Continue Reading
We humans do have a tendency to succumb to gold rush fever. And this can happen even in the left-brained, rational field of statistics. After we collect our data, it’s difficult to resist the urge to desperately dash for p-values, as if they were 70% off at Macy’s the day after Thanksgiving.But no matter how well-versed you are in statistics, it’s good practice to get into the habit of intuitively... Continue Reading
In an earlier post, I focused on using Minitab to present the coupon data I collected from my e-mail inbox into a bar chart. The bar chart made it easy for me to visually analyze which days of the week are better or worse for receiving the best coupons from my favorite retailers. As a reminder, here’s how I ranked each coupon’s worthiness: Not worth your timeOffering average savings (A “noteworthy”... Continue Reading
It’s summer and maybe you’re traveling to Florida’s coast for a beach vacation (or just wishing you were, like I am)! I got the chance to talk to Dr. Henry Briceño from the Southeast Environmental Research Center (SERC) about how he and his team use statistics to monitor Florida’s water quality. The center’s research projects throughout South Florida have provided a basis for management decisions... Continue Reading
Sometimes, statistical terms can seem like they were zapped down from outer space by sadistic, mealy-mouthed aliens: R-squared adjusted, heteroeskadasticity, 3-parameter Weibull distribution. But not all statistics terminology should leave you feeling woozy and glassy-eyed. Some terms  actually make intuitive sense. Knowing those terms can help you get a handle on output that may seem fuzzy at... Continue Reading
Data collection involves taking measurements, and this seems like a simple thing when the subject is relatively simple.  However, even the simplest of cases has the potential to be messed up.  I found this out the hard way once. I hope sharing it helps you avoid a similar experience. Experienced researchers and quality practitioners know they need to verify that a measurement system provides valid... Continue Reading
We use statistics because it's usually not practical to collect all of the data from an entire population. Instead, we sample the population, and then use statistics for that random sample to draw conclusions about the whole population.Many common statistical procedures require data to be approximately normal -- in other words, to roughly follow the bell curve.  But what happens when you have a... Continue Reading