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Data Analysis Software

Blog posts and articles with tips for using statistical software to analyze data for quality improvement.

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

7 Deadly Statistical Sins Even the Experts Make

Do you know how to avoid them?

Get the facts >
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
Welcome to the Hypothesis Test Casino! The featured game of the house is roulette. But this is no ordinary game of roulette. This is p-value roulette! Here’s how it works: We have two roulette wheels, the Null wheel and the Alternative wheel. Each wheel has 20 slots (instead of the usual 37 or 38). You get to bet on one slot. What happens if the ball lands in the slot you bet on? Well, that depends... 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
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
To make objective decisions about the processes that are critical to your organization, you often need to examine categorical data. You may know how to use a t-test or ANOVA when you’re comparing measurement data (like weight, length, revenue, and so on), but do you know how to compare attribute or counts data? It easy to do with statistical software like Minitab.  One person may look at this bar... Continue Reading
by Matthew Barsalou, guest blogger.  The old saying “if it walks like a duck, quacks like a duck and looks like a duck, then it must be a duck” may be appropriate in bird watching; however, the same idea can’t be applied when observing a statistical distribution. The dedicated ornithologist is often armed with binoculars and a field guide to the local birds and this should be sufficient. A... Continue Reading
In its industry guidance to companies that manufacture drugs and biological products for people and animals, the Food and Drug Administration (FDA) recommends three stages for process validation. While my last post covered statistical tools for the Process Design stage, here we will focus on the statistical techniques typically utilized for the second stage, Process Qualification. Stage 2: Process... 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
In my last post on DMAIC tools for the Define phase, we reviewed various graphs and stats typically used to define project goals and customer deliverables. Let’s now move along to the tools you can use in Minitab Statistical Software to conduct the Measure phase. Measure Phase Methodology The goal of this phase is to measure the process to determine its current performance and quantify the problem.... 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
Process validation is vital to the success of companies that manufacture drugs and biological products for people and animals. According to the FDA guidelines published by the U.S. Department of Health and Human Services: “Process validation is defined as the collection and evaluation of data, from the process design state through commercial production, which establishes scientific evidence that a... Continue Reading
by Matthew Barsalou, guest blogger The great Dr. Seuss tells of Mr. Plunger, who is the custodian at Diffendoofer School on the corner of Dinkzoober and Dinzott in the town of Dinkerville. The good Mr. Plunger “keeps the whole school clean” using a supper-zooper-flooper-do. Unfortunately, Dr. Seuss fails to tell us where the supper-zooper-flooper-do came from and if the production process was... 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
Reliability analysis is the perfect tool for calculating the proportion of items that you can expect to survive for a specified period of time under identical operating conditions. Light bulbs—or lamps—are a classic example. Want to calculate the number of light bulbs expected to fail within 1000 hours? Reliability analysis can help you answer this type of question. But to conduct the analysis... Continue Reading
In Parts 1 and 2 of this blog series, I wrote about how statistical inference uses data from a sample of individuals to reach conclusions about the whole population. That’s a very powerful tool, but you must check your assumptions when you make statistical inferences. Violating any of these assumptions can result in false positives or false negatives, thus invalidating your results.  The common... Continue Reading
Dear Readers, As 2016 comes to a close, it’s time to reflect on the passage of time and changes. As I’m sure you’ve guessed, I love statistics and analyzing data! I also love talking and writing about it. In fact, I’ve been writing statistical blog posts for over five years, and it’s been an absolute blast. John Tukey, the renowned statistician, once said, “The best thing about being a statistician... Continue Reading