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Eston Martz

I’m not a “math” person, but I've overcome fear of statistics and acquired a real passion for it. And if I can learn to understand and apply statistics, so can you. Continue Reading »

"Data! Data! Data! I can't make bricks without clay."  — Sherlock Holmes, in Arthur Conan Doyle's The Adventure of the Copper Beeches Whether you're the world's greatest detective trying to crack a case or a person trying to solve a problem at work, you're going to need information. Facts. Data, as Sherlock Holmes says.  But not all data is created equal, especially if you plan to analyze as part of... Continue Reading
If you have a process that isn’t meeting specifications, using the Monte Carlo simulation and optimization tool in Companion by Minitab can help. Here’s how you, as a chemical technician for a paper products company, could use Companion to optimize a chemical process and ensure it consistently delivers a paper product that meets brightness standards. The brightness of Perfect Papyrus Company’s new... Continue Reading

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Do your executives see how your quality initiatives affect the bottom line? Perhaps they would more often if they had accessible insights on the performance, and ultimately the overall impact, of improvement projects.  For example, 60% of the organizations surveyed by the American Society for Quality in their 2016 Global State of Quality study say they don’t know or don’t measure the financial... Continue Reading
Earlier, I wrote about the different types of data statisticians typically encounter. In this post, we're going to look at why, when given a choice in the matter, we prefer to analyze continuous data rather than categorical/attribute or discrete data.  As a reminder, when we assign something to a group or give it a name, we have created attribute or categorical data.  If we count something, like... Continue Reading
Everyone who analyzes data regularly has the experience of getting a worksheet that just isn't ready to use. Previously I wrote about tools you can use to clean up and eliminate clutter in your data and reorganize your data.  In this post, I'm going to highlight tools that help you get the most out of messy data by altering its characteristics. Know Your Options Many problems with data don't become... Continue Reading
You've collected a bunch of data. It wasn't easy, but you did it. Yep, there it is, right there...just look at all those numbers, right there in neat columns and rows. Congratulations. I hate to ask...but what are you going to do with your data? If you're not sure precisely what to do with the data you've got, graphing it is a great way to get some valuable insight and direction. And a good graph to... Continue Reading
In my last post, I wrote about making a cluttered data set easier to work with by removing unneeded columns entirely, and by displaying just those columns you want to work with now. But too much unneeded data isn't always the problem. What can you do when someone gives you data that isn't organized the way you need it to be?   That happens for a variety of reasons, but most often it's because the... Continue Reading
Isn't it great when you get a set of data and it's perfectly organized and ready for you to analyze? I love it when the people who collect the data take special care to make sure to format it consistently, arrange it correctly, and eliminate the junk, clutter, and useless information I don't need.   You've never received a data set in such perfect condition, you say? Yeah, me neither. But I can... Continue Reading
People can make mistakes when they test a hypothesis with statistical analysis. Specifically, they can make either Type I or Type II errors. As you analyze your own data and test hypotheses, understanding the difference between Type I and Type II errors is extremely important, because there's a risk of making each type of error in every analysis, and the amount of risk is in your control.    So if... Continue Reading
My colleague Cody Steele wrote a post that illustrated how the same set of data can appear to support two contradictory positions. He showed how changing the scale of a graph that displays mean and median household income over time drastically alters the way it can be interpreted, even though there's no change in the data being presented. When we analyze data, we need to present the results in... Continue Reading
A recent discussion on the Minitab Network on LinkedIn pertained to the I-MR chart. In the course of the conversation, a couple of people referred to it as "The Swiss Army Knife of control charts," and that's a pretty great description. You might be able to find more specific tools for specific applications, but in many cases, the I-MR chart gets the job done quite adequately. When you're... Continue Reading
Statistics can be challenging, especially if you're not analyzing data and interpreting the results every day. Statistical software makes things easier by handling the arduous mathematical work involved in statistics. But ultimately, we're responsible for correctly interpreting and communicating what the results of our analyses show. The p-value is probably the most frequently cited statistic. We... Continue Reading
Have you ever wanted to know the odds of something happening, or not happening?  It's the kind of question that students are frequently asked to calculate by hand in introductory statistics classes, and going through that exercise is a good way to become familiar with the mathematical formulas the underlie probability (and hence, all of statistics).  But let's be honest: when class is over, most... Continue Reading
In the first part of this series, we saw how conflicting opinions about a subjective factor can create business problems. In part 2, we used Minitab's Assistant feature to set up an attribute agreement analysis study that will provide a better understanding of where and when such disagreements occur.  We asked four loan application reviewers to reject or approve 30  selected applications, two... Continue Reading
Previously, I discussed how business problems arise when people have conflicting opinions about a subjective factor, such as whether something is the right color or not, or whether a job applicant is qualified for a position. The key to resolving such honest disagreements and handling future decisions more consistently is a statistical tool called attribute agreement analysis. In this post, we'll... Continue Reading
People frequently have different opinions. Usually that's fine—if everybody thought the same way, life would be pretty boring—but many business decisions are based on opinion. And when different people in an organization reach different conclusions about the same business situation, problems follow.  Inconsistency and poor quality result when people being asked to make yes / no, pass / fail, and... Continue Reading
Did you ever get a pair of jeans or a shirt that you liked, but didn't quite fit you perfectly? That happened to me a few months ago. The jeans looked good, and they were very well made, but it took a while before I was comfortable wearing them. I much prefer it when I can get a pair with a perfect fit, that feel like I was born in them, with no period of "adjustment."  So which pair do you think I... Continue Reading
The language of statistics is a funny thing, but there usually isn't much to laugh at in the consequences that can follow when misunderstandings occur between statisticians and non-statisticians. We see these consequences frequently in the media, when new studies—that usually contradict previous ones—are breathlessly related, as if their findings were incontrovertible facts. Similar, though less... Continue Reading
The line plot is an incredibly agile but frequently overlooked tool in the quest to better understand your processes. In any process, whether it's baking a cake or processing loan forms, many factors have the potential to affect the outcome. Changing the source of raw materials could affect the strength of plywood a factory produces. Similarly, one method of gluing this plywood might be better... Continue Reading
A member of Minitab's LinkedIn group asked how to create a chart to monitor change by month, specifically comparing last year's data to this year's data. My last post showed how to do this using an Individuals Chart of the differences between this year's and last year's data.  Here's another approach suggested by a participant in the group.  Applying Statistical Thinking An individuals chart of the... Continue Reading