dcsimg

How to Handle Extreme Outliers in Capability Analysis

Transformations and non-normal distributions are typically the first approaches considered when the when the Normality test fails in a capability analysis. These approaches do not work when there are extreme outliers because they both assume the data come from a single common-cause variation distribution. But because extreme outliers typically represent special-cause variation, transformations and non-normal distributions are not good approaches for data that contain extreme outliers.

As an example, the four graphs below show distribution fits for a dataset with 99 values simulated from a...

Is Your Statistical Software FDA Validated for Medical Devices or Pharmaceuticals?

We're frequently asked whether Minitab has been validated by the U.S. Food and Drug Administration (FDA) for use in the pharmaceutical and medical device industries.

Minitab does extensive testing to validate our software internally, but Minitab’s statistical software is not—and cannot be—FDA-validated out-of-the-box.

Nobody's can.

It is a common misconception that software vendors can go through a certification process to achieve FDA software validation. It's simply not true.

Software vendors who claim their products are FDA-validated should be scrutinized. It is up to the software purchaser to...

Five Ways to Make Your Control Charts More Effective

Have you ever wished your control charts were better?  More effective and user-friendly?  Easier to understand and act on?  In this post, I'll share some simple ways to make SPC monitoring more effective in Minitab.

Common Problems with SPC Control Charts

I worked for several years in a large manufacturing plant in which control charts played a very important role. Virtually thousands of SPC (Statistical Process Control) charts were used to monitor processes, contamination in clean rooms, monitor product thicknesses and shapes as well as critical equipment process parameters. Process engineers...

(We Just Got Rid of) Three Reasons to Fear Data Analysis

Today our company is introducing Minitab 17 Statistical Software, the newest version of the leading software used for quality improvement and statistics education.    So, why should you care? Because important people in your life -- your co-workers, your students, your kids, your boss, maybe even you -- are afraid to analyze data.    There's no shame in that. In fact, there are pretty good reasons for people to feel some trepidation (or even outright panic) at the prospect of making sense of a set of data.

I know how it feels to be intimidated by statistics. Not long ago, I would do almost...

Applying Six Sigma to a Small Operation

Using data analysis and statistics to improve business quality has a long history. But it often seems like most of that history involves huge operations. After all, Six Sigma originated with Motorola, and became adopted by thousands of other businesses after it was adopted by a little-known outfit called General Electric.

There are many case studies and examples of how big companies used Six Sigma methods to save millions of dollars, slash expenses, and improve quality...but when they read about the big dogs getting those kind of results, a lot of folks hear a little voice in their heads...

Use the Minitab Assistant to Choose a Graph

Everyone loves Minitab’s Assistant. My favorite bit, as I’ve shown with the Gage R&R Study, is the way that the Assistant puts all the results you need into reports that are easy to understand and present. But it’s also pretty neat that before you ever choose what to do in Minitab, the Assistant is ready to help you. Let’s take a closer look at the Assistant's Graphical Analysis tools.

Help Me Choose

Choose Assistant > Graphical Analysis and the most prominent thing you’ll see is a question:

But you’re not left with just the three objectives. Select "graph variables over time," and before you...

R-Squared: Sometimes, a Square is just a Square

If you regularly perform regression analysis, you know that R2 is a statistic used to evaluate the fit of your model. You may even know the standard definition of R2: the percentage of variation in the response that is explained by the model.

Fair enough. With Minitab Statistical Software doing all the heavy lifting to calculate your R2 values, that may be all you ever need to know.

But if you’re like me, you like to crack things open to see what’s inside. Understanding the essential nature of a statistic helps you demystify it and interpret it more accurately.

R-squared: Where Geometry Meets...

Regression Analysis Tutorial and Examples

I’ve written a number of blog posts about regression analysis and I think it’s helpful to collect them in this post to create a regression tutorial. I’ll supplement my own posts with some from my colleagues.

This tutorial covers many aspects of regression analysis including: choosing the type of regression analysis to use, specifying the model, interpreting the results, determining how well the model fits, making predictions, and checking the assumptions. At the end, I include examples of different types of regression analyses.

If you’re learning regression analysis right now, you might want to...

Understanding ANOVA by Looking at Your Household Budget

by Arun Kumar, guest blogger

One of the most commonly used statistical methods is ANOVA, short for “Analysis of Variance.” Whether you’re analysing data for Six-Sigma styled quality improvement projects, or perhaps just taking your first statistics course, a good understanding of how this technique works is important.

A lot of concepts are involved in any analysis using ANOVA and its subsequent interpretation. You’re going to have to grapple with terms such as Sources of Variation, Sum of Squares, Mean Squares, Degrees of Freedom, and F-ratio—and you’ll need to understand what statistical...

Applied Regression Analysis: How to Present and Use the Results to Avoid Costly Mistakes, part 2

Applied regression analysis can be a great decision-making tool because you can predict the average outcome given input values. However, predictions are not as simple as plugging numbers into an equation. In my previous post I showed how a majority of experts vastly underestimated the variability around the predicted outcome in a manner that can lead to costly mistakes.

We also saw how graphing the data is a simple way to avoid these mistakes because it highlights the uncertainty. In this post, I'll explore other techniques that you can use in Minitab statistical software to facilitate good...

Making a Difference in How People Use Data

A colleague of mine at Minitab, Cheryl Pammer, was recently featured in "A Statistician's Journey," a monthly feature that appears in the print and online versions of the American Statistical Association's AMSTAT News magazine.  

Each month, the magazine asks ASA members to talk about the paths they took to get to where they are today. Cheryl is a "user experience designer" at Minitab. In other words, she's one of the people who help determine how our statistical softwaredoes what it does, and tries to make it as helpful, useful, and beneficial as possible. Cheryl is always looking for ways to...

Optical Illusions, Zen Koans, and Simpson’s Paradox

What do you see when you look at the image at right?

Do you see a bulging sphere that stretches the checkerboard pattern in the center, causing its lines to curve?

Are you sure? Look again. This time, test any “curved” line by holding a straightedge next to it.

The image is actually composed of small squares and straight lines. Yet, when perceived as a composite whole, it creates a completely different  impression.

A similar “illusion” can occur when you analyze your data.  It’s called the Yule-Simpson effect—or Simpson’s paradox for short.

When you look at the overall results of all your data, you...

Use Analysis of Means to Classify Baseball Parks

When I first got interested in looking at baseball park factors, I only wanted to know which parks benefited hitters and which benefited pitchers. Once I got started, I got interested in the difference between ESPN's published formula and its results and whether there were obvious reasons for the variation in park factors from year-to-year.

But today I’m returning to the original question: which parks are hitters’ parks, and which are pitchers’ parks?

We already know that the mean and median are inadequate by themselves. For example, consider AT&T Park, where the mean suggests a pitchers’...

Itchy, Sneezy, Stuffy: Delivering Relief with Nasal Spray and DOE

Recently, a customer called our Technical Support team about a Design of Experiment he was performing in Minitab Statistical Software. After they helped to answer his question, the researcher pointed our team to an interesting DOE he and his colleagues conducted that involved using nasal casts to predict the drug delivery of nasal spray.

The study has already been published, and you can read more about it here, but I wanted to highlight this use of the DOE tools in Minitab in this blog post.

Using Nasal Casts to Predict Nasal Spray Drug Delivery

The nose is a convenient route of administration...

How much do different scoring systems affect fantasy football rankings?

Ever start a fantasy football draft and realize that passing touchdowns are worth 6 points, not 4? Or how about realizing at the last minute that the commissioner of your league decided to have a point per reception (PPR) league. We know that this year running backs are going to be going early in the draft. But if your league is a PPR or gives 6 points for a passing touchdown, should you be focusing on quarterbacks and receivers instead?

Sounds like a perfect question for a data analysis in a statistical software package like Minitab!

Getting Six Points for Passing Touchdowns

My first reaction to...

How Many Licks to the Tootsie Roll Center of a Tootsie Pop? Part 2

by Cory Heid, guest blogger

A few months ago I posted a blog about Tootsie Pops and how many licks it takes to get to the Tootsie Roll center. If you haven’t read the post, here's a quick summary.

Recap of Initial Study

I broke down my experiment into four parts where I would test:

  • the force of a lick
  • temperature of a person's mouth
  • pH level of a person's saliva
  • the solubility of a person's saliva

After some tests and analysis of the data I collected, I was able to conclude that none of the factors I tested were statistically different or important enough to affect the number of licks required to...

Doing Gage R&R at the Microscopic Level

by Dan Wolfe, guest blogger

How would you measure a hole that was allowed to vary one tenth the size of a human hair? What if the warmth from holding the part in your hand could take the measurement from good to bad? These are the types of problems that must be dealt with when measuring at the micron level.

As a Six Sigma professional, that was the challenge I was given when Tenneco entered into high-precision manufacturing. In Six Sigma projects “gage studies” and “Measurement System Analysis (MSA)” are used to make sure measurements are reliable and repeatable. It’s tough to imagine doing that...

Normality Tests and Rounding

All measurements are rounded to some degree. In most cases, you would not want to reject normality just because the data are rounded. In fact, the normal distribution would be a quite desirable model for the data if the underlying distribution is normal since it would smooth out the discreteness in the rounded measurements.

Some normality tests reject a very high percentage of time due to rounding when the underlying distribution is normal (Anderson-Darling and Kolmogorov-Smirnov), while others seem to ignore the rounding (Ryan-Joiner and chi square).

As an extreme example of how data that is...

Spicy Statistics and Attribute Agreement Analysis

My husband, Sean, and I were recently at my parent’s house for a picnic dinner. As a lover of hot sauce (I’m talking extremely hot, hot, hot, HOT sauce!), my stepdad always has a plethora of bottles around to try. While I do enjoy spicy foods from time to time, I’ve learned not to touch his hot sauce selections. His favorites are much too spicy for my taste!

Unfortunately, Sean learned the hard way. He used Habanero hot sauce on his hot sausage sandwich – talk about double the heat! I saw him sinking in his seat, eyes watering … a few hoarse coughs …

Yikes!  Anyway, Sean is alive and well after...

A correspondence table for non parametric and parametric tests

Most of the data that one can collect and analyze follow a normal distribution (the famous bell-shaped curve). In fact, the formulae and calculationsused in many analyses simply take it for granted that our data follow this distribution; statisticians call this the "assumption of normality."

For example, our data need to meet the normality assumption before we can accept the results of a one- or two-sample t (Student) or z test. Therefore, it is generally good practice to run a normality test before performing the hypothesis test.

But wait...according to the Central Limit Theorem, when the...