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Using Design of Experiments to Minimize Noise Effects

All processes are affected by various sources of variations over time. Products which are designed based on optimal settings, will, in reality, tend to drift away from their ideal settings during the manufacturing process.

Environmental fluctuations and process variability often cause major quality problems. Focusing only on costs and performances is not enough. Sensitivity to deterioration and process imperfections is an important issue. It is often not possible to completely eliminate variations due to uncontrollable factors (such as temperature changes, contamination, humidity, dust etc…).

Fo...

Quality Improvement in Financial Services

Process improvement through methodologies such as Six Sigma and Lean has found its way into nearly every industry. While Six Sigma had its beginnings in manufacturing, we’ve seen it and other process improvement techniques work very well in the service industry—from healthcare to more service-oriented business functions, such as human resources.

However, Six Sigma seems to have had a slower rate of adoption in financial services. I recently came across a great article about the challenges faced in the financial industry when it comes to successfully implementing a process improvement...

Studying Old Dogs with New Statistical Tricks: Bone-Cracking Hypercarnivores and 3D Surface Plots

A while back my colleague Jim Frost wrote about applying statistics to decisions typically left to expert judgment; I was reminded of his post this week when I came across a new research study that takes a statistical technique commonly used in one discipline, and applies it in a new way. 

The study, by paleontologist Zhijie Jack Tseng, looked at how the skulls of bone-cracking carnivores--modern-day hyenas--evolved. They may look like dogs, but hyenas in fact are more closely related to cats. However, some extinct dog species had skulls much like a hyena's. 

Tseng analyzed data from 3D...

What Is a t-test? And Why Is It Like Telling a Kid to Clean Up that Mess in the Kitchen?

A t-test is one of the most frequently used procedures in statistics.

But even people who frequently use t-tests often don’t know exactly what happens when their data are wheeled away and operated upon behind the curtain using statistical software like Minitab.

It’s worth taking a quick peek behind that curtain.

Because if you know how a t-test works, you can understand what your results really mean. You can also better grasp why your study did (or didn’t) achieve “statistical significance.”

In fact, if you’ve ever tried to communicate with a distracted teenager, you already have experience with...

Regression Analysis: How Do I Interpret R-squared and Assess the Goodness-of-Fit?

After you have fit a linear model using regression analysis, ANOVA, or design of experiments (DOE), you need to determine how well the model fits the data. To help you out, Minitab statistical software presents a variety of goodness-of-fit statistics. In this post, we’ll explore the R-squared (R2 ) statistic, some of its limitations, and uncover some surprises along the way. For instance, low R-squared values are not always bad and high R-squared values are not always good!

What Is Goodness-of-Fit for a Linear Model?

Definition: Residual = Observed value - Fitted value

Linear regression...

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,...

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...

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...

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...

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...

Benthic Invertebrates Gone Wild!

Using a Survey of Aquatic Bugs to Estimate Stream Quality

As we click, flip, and scroll through hundreds of sites and channels, cruising for our daily dose of e-thrills, it’s easy to forget there’s a beautiful, wild, creative universe right in our backyards.

I had the chance to experience a tiny part of that universe on a recent Saturday afternoon, when a couple of friends, Yolanda and Monika, asked me if I wanted to join them to monitor the water quality of the stream that runs in back of our house.

Yolanda and Monika are part of a large grassroots network of volunteers who selflessly give their...

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...

Getting Started with Factorial Design of Experiments (DOE)

When I talk to quality professionals about how they use statistics, one tool they mention again and again is design of experiments, or DOE. I'd never even heard the term before I started getting involved in quality improvement efforts, but now that I've learned how it works, I wonder why I didn't learn about it sooner. If you need to find out how several factors are affecting a process outcome, DOE is the way to go. 

Somewhere in school you probably learned, like I did, that when you do an experiment you need to hold all the factors constant except for the one you're studying. That seems simple...

What Statistical Software Should You Choose: Three More Critical Questions

Earlier I wrote about four important questions you should ask if you're looking at using statistical software to analyze data in your organization, especially if you're hoping to improve quality using methods like Six Sigma. But there are other points to consider as well. If you're in market for statistical software, be sure to investigate these questions, too!

What Types of Statistical Analysis Will They Be Doing? 

The specific types of analysis you need to do could play a big part in determining the right statistical software for your organization. The American Statistical Association's softwa...

If You Don't Try Minitab's Project Manager, You'll Hate Yourself Later

Normally, I like to talk about fun statistical things to build your confidence: gummi bears, poetry, and movies, just to name a few. But building your confidence also means getting comfortable with Minitab Statistical Software. One of the features that makes it easy to view your results and data in a snap is Minitab's Project Manager.

My favorite way to use the Project Manager is through the toolbar:

Click the leftmost button once, and you see all of the output in your project. Click the second button once, and you see all of the worksheets in your project. Click the third button once, and...

Using Minitab to Choose the Best Ranking System in College Basketball

Life is full of choices. Some are simple, such as what shirt to put on in the morning (although if you’re like me, it’s not so much of a “choice” as it is throwing on the first thing you grab out of the closet). And some choices are more complex. In the quality world, you might have to determine which distribution to choose for your capability analysis or which factor levels to use to bake the best cookie in a design of experiments. But all of these choices pale in comparison* to the most important decision you have to make each year: which college basketball teams to pick during March...

Build a DIY Catapult for DOE (Design of Experiments), part 2

by Matthew Barsalou, guest blogger

In my last post, I shared my plans for building a simple do-it-yourself catapult for performing experiments to practice using design of experiments (DOE)

That's the completed catapult there on the right. If you want to build your own, here are my plans and instructions in a PDF.  

Now that my catapult is built, I have one last step to complete:  to find the optimal catapult setting using DOE, which I'll do with Minitab Statistical Software. (If you'd like to follow along but don't already have it, please download the 30-day free trial of Minitab.) 

Planning...

Build a DIY Catapult for DOE (Design of Experiments), part 1

by Matthew Barsalou, guest blogger

I needed to find a way to perform experiments to practice using design of experiments (DOE), so I built a simple do-it-yourself (DIY) catapult. The basic plan for the catapult is based on the table-top troll catapult from http://www.stormthecastle.com/catapult/how-to-build-a-catapult.htm.

My catapult is not as attractive as the troll catapult; my goal was to build a catapult with multiple adjustable factors—and not to lay siege to a castle—so I don’t mind the rough appearance of my catapult.

The frame consists of two pieces of 40 cm x 4 cm x 2 cm wood, two...

Violations of the Assumptions for Linear Regression (Day 2): Independence of the Residuals

Recap: Lionel Loosefit has been arrested and hauled to court for violating the assumptions of regression analysis. In the previous court session, the prosecution presented evidence to show that the errors in Mr. Loosefit’s model were not normally distributed. Today, the prosecution addresses the second alleged violation: namely, that the errors in the defendant’s regression model are not independent. Dr. Minnie Tabber, a world-renowned statistician, is on the witness stand.

Prosecutor: Let me remind the members of the jury that a residual is simply the difference between the data value...

Performing DOE for Defect Reduction

Lean Six Sigma and process excellence leaders are often asked to “remove defects” from products and processes. This can be quite a challenge! Lou Johnson, senior Minitab technical trainer and mentor, has some tips that might help if you’re faced with this situation. I had the chance to talk with Lou, and here’s what he shared with me about how to first approach a DOE.

How to Approach a DOE

Before jumping into a Design of Experiment (DOE) for defect reduction, Lou suggests stepping back and thinking first about what issue is likely causing the problem. If you need help thinking about what might...