Explaining Quality Statistics So Your Boss Will Understand: Weighted Pareto Charts

Failure to properly calibrate this machine will result in defective rock and roll. 

In my last post, I imagined using the example of a rock and roll band -- the Zero Sigmas -- to explain Pareto charts to my music-loving but statistically-challenged boss. I showed him how easy it was to use a Pareto chart to visualize defects or problems that occur most often, using the example of various incidents that occurred on the Zero Sigmas last tour.  

The Pareto chart revealed that starting performances late was far and away the Zero Sigmas' most frequent "defect," one that occurred every single night of...

Expanding the Role of Statistics to Areas Traditionally Dominated by Expert Judgment

Should this doctor consult a regression model?

In a previous post, I wrote about how the field of statistics is more important now than ever before due to the modern deluge of data. Because you’re reading Minitab's statistical blog, I’ll assume that we’re in agreement that statistics allows you to use data to understand reality. However, I’d also bet that you’re picturing important but “typical” statistical studies, such as studies where Six Sigma analysts determine which factors affect product quality. Or perhaps medical studies, like determining the effectiveness of flu shots.

In this post,...

Planning Summer Fun with Decision Matrix Tools

Normally, I tell you about ways to practice with Minitab Statistical Software so that you can boost your confidence with statistical analysis. But over the last few days in my house, we’ve been planning some activities for the family. That planning has given me a chance to have some fun with Quality Companion.

Quality Companion is a substantial piece of software: everything that you need to manage a quality improvement project in one application. Quality Companion provides project management tools so that you can make and communicate decisions.

My favorite tools in Quality Companion, with...

Using Games to Teach Statistics

We usually think of games as a distraction—just something we do for fun. However, growing evidence suggests that games can do much more, especially when it comes to learning in a classroom setting.

Because statistics is a topic that doesn’t come easily to most, using properly designed games to teach statistics can become a valuable tool to spark interest and help explain difficult concepts.

So what kinds of “properly designed” games are we talking about here? Not traditional board games like Monopoly or Chutes and Ladders, but interactive computer games—the types of games younger generations...

Get Your Way, Every Time: 7 Default Settings in Minitab You Didn’t Know You Could Change

Unless you’re 3 years old, you probably can’t have things just the way you want them all the time.  

You can’t always have peanut butter and ranch dressing on your toast. Or ketchup on your pineapple. Or sugar sprinkles on your peas.

But there is one small arena in life over which you can still exert your control. 

Tools > Options in Minitab's statistical software allows you to change selected default settings in the software, without having to throw a temper tantrum first.

This powerful, underutilized feature in Minitab may save you from the inconvenience of having to change a default setting...

Which Big Ten Division is Better?

After another round of what seems like endless conference realignment, the Big Ten has settled on 14 teams split into two divisions; East and West. However, with the likes of Ohio State, Penn State, Michigan, and Michigan State, the East division appears to be much stronger. In fact, Indiana athletic director Fred Glass called it the “Big Boy Division,” and Penn State coach Bill O’Brien referred to it as “Murderers' Row.”

But will the statistics back up their claims? After all, it’s easy to spout off any opinion you want. I could claim that the Sun Belt is a better football conference than the...

The Diversity (and Consistency) of Quality Improvement: the 2013 ASQ ITEA Presentations

I'm in the airport at Indianapolis, waiting to go home after three exciting days at the 2013 American Society for Quality World Conference.  As I write this, it's Wednesday evening after the conference has closed, and it turns out my flight has been delayed.

This could give me ample opportunity to muse about the quality issues that might keep me from reaching central Pennsylvania tonight. But I'm kind of pumped up, so I'm more interested in thinking about what I've experienced and seen over the past few days. This is the kind of event that makes you want to keep focusing on the positive, not...

How to “Expand” Your Gage Studies

As we said in yesterday’s post, it’s been exciting for Minitab to be a supporter of the ASQ World Conference on Quality and Improvement taking place this week in Indianapolis. There have been many great sessions and an abundance of case studies shared that highlight how quality teams worldwide are improving the performance of their businesses.

One session that generated a lot of interest from the conference participants was conducted by Minitab trainers Lou Johnson, Daniel Griffith and Jim Colton.

Their presentation, Sampling Plan for Expanded Gage R&R Studies, covered Gage R&R studies and how...

Talking Design of Experiments (DOE) and Quality at the 2013 ASQ World Conference

The 2013 ASQ World Conference is taking place this week in Indianapolis, Indiana, and it's been a treat to see how our software was used in the projects highlighted in many of the presentations. As a supporter of the conference, a key event for quality practitioners around the world, Minitab was proud to sponsor one of the presentations that seemed to get a lot of attendees talking. Scott Sterbenz, a Six Sigma leader from Ford Motor Company, delivered a presentation entitled "Leveraging Designed Experiments for Success," which explained how to make designed experiments succeed with examples...

Explaining Quality Statistics So Your Boss Will Understand: Pareto Charts

I once had a boss who had difficulty understanding many, many things. When I need to discuss statistical concepts with people who don't have a statistical background, I like to think about how I could explain things so even my old boss would get it. 

My boss and I shared a common interest in rock and roll, so that's the device I'll use to explain one of the workhorses of quality statistics, the Pareto chart. I'd tell my boss to imagine that instead of managing a surly gang of teenaged restaurant employees, he's managing a surly rock and roll band, the Zero Sigmas. The band did a 100-date tour...

Control Charts: Rational Subgrouping and Marshmallow Peeps!

Control charts are used to monitor the stability of processes, and can turn time-ordered data for a particular characteristic—such as product weight or hold time at a call center—into a picture that is easy to understand. These charts indicate when there are points out of control or unusual shifts in a process.

Statistically speaking, control charts help you detect nonrandom sources of variation in the data. In other words, they separate variation due to common causes from variation due to special causes, where:

  • Common cause variation is variation that is naturally inherent in a process, and...

What Are the Effects of Multicollinearity and When Can I Ignore Them?

Multicollinearity is problem that you can run into when you’re fitting a regression model, or other linear model. It refers to predictors that are correlated with other predictors in the model. Unfortunately, the effects of multicollinearity can feel murky and intangible, which makes it unclear whether it’s important to fix.

My goal in this blog post is to bring the effects of multicollinearity to life with real data! Along the way, I’ll show you a simple tool that can remove multicollinearity in some cases.


 My goal in this blog post is to bring multicollinearity to life with real data about...

Understanding Alpha Alleviates Alarm

One of the more misunderstood concepts in statistics is alpha, more formally known as the significance level. Alpha is typically set before you conduct an experiment. When the calculated p-value from a hypothesis test is less than the significance level (α), the results of an experiment are so unlikely to happen by chance that the more likely explanation is the results occur because of the effect being studied. That the results are unlikely to happen by chance is what we mean by the phrase “statistical significance,” not to be confused with practical significance.

There was a wonderful example...

Leveraging Designed Experiments (DOE) for Success

You know the drill…you’re in Six Sigma training and you’re learning how to conduct a design of experiment (DOE). Everything is making sense, and you’ve started thinking about how you’ll apply what you are learning to find the optimal settings of a machine on the factory floor. You’ve even got the DOE setup chosen and you know the factors you want to test …

Then … BAM! … You’re on your own and you immediately have issues analyzing the data. The design you’ve chosen might actually not be the best for the results you need.  It's a classic case of learning something in theory that becomes much more...

Truth, Beauty, Nonparametrics & Symmetry Plots

  “Shall I compare thee to a standard normal distribution?
  Thou art more symmetric and more bell-shaped…”  — Melvin Shakespeare (William’s lesser-known statistician brother)

The Greek philosopher Aristotle believed that symmetry was one of the primary elements of the universal ideal of beauty. Over 2000 years later, emerging research seems to bear him out. 

Studies suggest we tend to be more attracted to people with symmetrical bodies. Using motion-capture technology to record the movements of people dancing to a popular song, one recent study concluded that we even prefer those who dance...

Using Binary Logistic Regression to Investigate High Employee Turnover

Human resources might not be a business area where you’d typically expect to conduct a Six Sigma project. However, Jeff Parks, Lean Six Sigma master black belt, found the opportunity to apply Six Sigma to human resources while leading quality improvement efforts at a large manufacturer of aerospace engine parts.

The manufacturer was suffering from high employee attrition, or turnover, and struggled to understand why. With a DMAIC Six Sigma project, Parks set out to work with the HR department to investigate and reduce the high turnover rates.

In 2009, the manufacturer had normal attrition rates...

Explaining Quality Statistics So My Boss Will Understand: Measurement Systems Analysis (MSA)

As a teenaged dishwasher at a local eatery, I had a boss who'd never washed dishes in a restaurant himself. I once spent 40 minutes trying to convince him that forks and spoons should go in their holders with the business end up, while knives should go in point-down. Whatever I said, he didn't get it. We were ordered to put forks and spoons in the holders with the handles up.

The outraged wait staff soon made clear what I hadn't: you can't immediately tell the difference between a fork and a spoon when all you can see is the handle! Explaning that in the right way would have minimized wasted...

Remembering the Positive in a Time of Tragedy

My holy of holies is the human body, health, intelligence, talent, inspiration, love, and the most absolute freedom imaginable, freedom from violence and lies, no matter what form the latter two take.

                -Anton Chekhov

Normally, I write about subjects that are generally of interest to me when I do a blog post: you may have seen the list before. So I’ll have to start out this post with the admission that until I was leaving the office on Monday, I had no idea that the Boston Marathon was going on that day. I had no clue that the estimate of the number of spectators would be over...

When Should I Use Confidence Intervals, Prediction Intervals, and Tolerance Intervals

In statistics, we use a variety of intervals to characterize the results. The most well-known of these are confidence intervals. However, confidence intervals are not always appropriate. In this post, we’ll take a look at the different types of intervals that are available in Minitab, their characteristics, and when you should use them.

I’ll cover confidence intervals, prediction intervals, and tolerance intervals. Because tolerance intervals are the least-known, I’ll devote extra time to explaining how they work and when you’d want to use them.

What are Confidence Intervals?

A confidence...

Enough Is Enough! Handling Multicollinearity in Regression Analysis

In regression analysis, we look at the correlations between one or more input variables, or factors, and a response. We might look at how baking time and temperature relate to the hardness of a piece of plastic, or how educational levels and the region of one's birth relate to annual income. The number of potential factors you might include in a regression model is limited only by your imagination...and your capacity to actually gather the data you imagine.

But before throwing data about every potential predictor under the sun into your regression model, remember a thing called multicollinearity...