dcsimg
 

Tips and Techniques for Statistics and Quality Improvement

Blog posts and articles about using Minitab software in quality improvement projects, research, and more.

It’s safe to say that most people who use statistics are more familiar with parametric analyses than nonparametric analyses. Nonparametric tests are also called distribution-free tests because they don’t assume that your data follow a specific distribution. You may have heard that you should use nonparametric tests when your data don’t meet the assumptions of the parametric test, especially the... Continue Reading
In part 1 of this post, I covered how Six Sigma students at Rose-Hulman Institute of Technology cleaned up and prepared project data for a regression analysis. Now we're ready to start our analysis. We’ll detail the steps in that process and what we can learn from our results. What Factors Are Important? We collected data about 11 factors we believe could be significant: Whether the date of... Continue Reading
Over the weekend Penn State men's basketball coach Pat Chambers had some strong words about a foul that went against his team in a 76-73 loss against Maryland. Chambers called it “The worst call I’ve ever seen in my entire life,” and he wasn’t alone in his thinking. Even sports media members with no affiliation to Penn State agreed with him. This wasn't the first time this season Chambers has... Continue Reading
By Peter Olejnik, guest blogger. Previous posts on the Minitab Blog have discussed the work of the Six Sigma students at Rose-Hulman Institute of Technology to reduce the quantities of recyclables that wind up in the trash. Led by Dr. Diane Evans, these students continue to make an important impact on their community. As with any Six Sigma process, the results of the work need to be evaluated. A... Continue Reading
I left off last with a post outlining how the Six Sigma students at Rose-Hulman were working on a project to reduce the amount of recycling thrown in the normal trash cans in all of the academic buildings at the institution. Using the DMAIC methodology for completing improvement projects, they had already defined the problem at hand: how could the amount of recycling that’s thrown in the normal trash... Continue Reading
If you wanted to figure out the probability that your favorite football team will win their next game, how would you do it?  My colleague Eduardo Santiago and I recently looked at this question, and in this post we'll share how we approached the solution. Let’s start by breaking down this problem: There are only two possible outcomes: your favorite team wins, or they lose. Ties are a possibility,... Continue Reading
I typically attend a few Lean Six Sigma conferences each year, and at each there is at least one session about compensating belts. Any number of ideas exist out there, but they commonly include systems that provide a percentage of savings as a portion of pay or provide a bonus for meeting target project savings. There are always issues with these pay schemes, including the fact that... Continue Reading
The Minitab Fan section of the Minitab blog is your chance to share with our readers! We always love to hear how you are using Minitab products for quality improvement projects, Lean Six Sigma initiatives, research and data analysis, and more. If our software has helped you, please share your Minitab story, too! My LSS coach suggested that I regularly conduct data analysis to refresh my Minitab... Continue Reading
  In my experience, one of the hardest concepts for users to wrap their head around revolves around the Power and Sample Size menu in Minitab's statistical software, and more specifically, the field that asks for the "difference" or "difference to detect."  Let’s start with power. In statistics, the definition of power is the probability that you will correctly reject the null hypothesis when it is... Continue Reading
Recently, Minitab’s Joel Smith posted about his vacation and being pooped on twice by birds. Then guest blogger Matthew Barsalou wrote a wonderful follow-up on the chances of Joel being pooped on a third time. While I cannot comment on how Joel has handled this situation psychologically so far, I can say that if I had been pooped on twice in a short amount of time, I would be wary of our... Continue Reading
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 Devize. What is Devize, you ask? Devize is Minitab's exciting new,... Continue Reading
There’s no shortage of interest this week in whether Tom Brady is the best quarterback to ever play the game of football. As a University of Tennessee alum, I have to recuse myself from that particular debate for lack of objectivity. (Everyone knows Peyton Manning is the best quarterback to ever play the game, right?) But now seems like a good time to look at some numbers that show where Brady... Continue Reading
by Matthew Barsalou, guest blogger.  E. E. Doc Smith, one of the greatest authors ever, wrote many classic books such as The Skylark of Space and his Lensman series. Doc Smith’s imagination knew no limits; his Galactic Patrol had millions of combat fleets under its command and possessed planets turned into movable, armored weapons platforms. Some of the Galactic Patrol’s weapons may be well... Continue Reading
In the past week there has been a big commotion over this article that shows since 2007 the Patriots have fumbled at rate that is extremely lower than the rest of the NFL. Why 2007? Because that’s the year the NFL changed their policies to allow every team to use their own footballs, even when they were playing on the road. So if the Patriots were going to try to gain an advantage by deflating... Continue Reading
In my recent meetings with people from various companies in the service industries, I realized that one of the problems they face is that they were collecting large amounts of "qualitative" data: types of product, customer profiles, different subsidiaries, several customer requirements, etc. As I discussed in my previous post, one way to look at qualitative data is to use different types of... Continue Reading
In several previous blogs, I have discussed the use of statistics for quality improvement in the service sector. Understandably, services account for a very large part of the economy. Lately, when meeting with several people from financial companies, I realized that one of the problems they faced was that they were collecting large amounts of "qualitative" data: types of product, customer... Continue Reading
If you’re not a statistician, looking through statistical output can sometimes make you feel a bit like Alice in Wonderland. Suddenly, you step into a fantastical world where strange and mysterious phantasms appear out of nowhere.   For example, consider the T and P in your t-test results. “Curiouser and curiouser!” you might exclaim, like Alice, as you gaze at your output. What are these values,... Continue Reading
Choosing the correct linear regression model can be difficult. After all, the world and how it works is complex. Trying to model it with only a sample doesn’t make it any easier. In this post, I'll review some common statistical methods for selecting models, complications you may face, and provide some practical advice for choosing the best regression model. It starts when a researcher wants to... Continue Reading
In the State of the Union Address, President Obama said: “No challenge — no challenge — poses a greater threat to future generations than climate change. 2014 was the planet’s warmest year on record. Now, one year doesn’t make a trend, but this does — 14 of the 15 warmest years on record have all fallen in the first 15 years of this century.” This follows the joint announcement by NASA and NOAA on... Continue Reading
You may have been in a situation where you had created a general full factorial design and noticed that your design’s run size was higher than you imagined. (Quick refresher: a general full factorial design is an experimental design where any factor can have more than 2 levels). Determined to minimize the monstrous size of your worksheet, you go back to Stat > DOE > Factorial > Create Factorial... Continue Reading