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Data Analysis

Blog posts and articles with tips for analyzing data for quality improvement methodologies, including Six Sigma and Lean.

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 elminate 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
College basketball season tips off today, and for the second straight season Kentucky is the #1 ranked preseason team in the AP poll. Last year Kentucky did not live up to that ranking in the regular season, going 24-10 and earning a lowly 8 seed in the NCAA tournament. But then, in the tournament, they overachieved and made a run all the way to the championship game...before losing... Continue Reading
Analysis of variance (ANOVA) is great when you want to compare the differences between group means. For example, you can use ANOVA to assess how three different alloys are related to the mean strength of a product. However, most ANOVA tests assess one response variable at a time, which can be a big problem in certain situations. Fortunately, Minitab statistical software offers a... 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
A few weeks ago my colleague Cody Steele 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
Users often contact Minitab technical support to ask how the software calculates the control limits on control charts. A frequently asked question is how the control limits are calculated on an I-MR Chart or Individuals Chart. If Minitab plots the upper and lower control limits (UCL and LCL) three standard deviations above and below the mean, why are the limits plotted at values other than 3 times... Continue Reading
We like to host webinars, and our customers and prospects like to attend them. But when our webinar vendor moved from a pay-per-person pricing model to a pay-per-webinar pricing model, we wanted to find out how to maximize registrations and thereby minimize our costs. We collected webinar data on the following variables: Webinar topic Day of week Time of day – 11 a.m. or 2 p.m. Newsletter promotion –... Continue Reading
Halloween's right around the corner, so here's a scary thought for the statistically minded: That pattern in your time series plot? Maybe it's just a ghost. It might not really be there at all.   That's right. The trend that seems so evident might be a phantom. Or, if you don't believe in that sort of thing, chalk it up to the brain's desire to impose order on what we see, even when it doesn't... Continue Reading
In quality initiatives such as Six Sigma, practitioners often need to assess the capability of a process to make sure it can meet specifications, or to verify that it produces good parts. While many Minitab users are familiar with the capability analysis tools in the Stat menu and in Minitab’s Assistant, the Assistant includes a less-frequently used feature—the Capability Snapshot. What Is the... Continue Reading
Keeping your vehicle fueled up is expensive. Maximizing the miles you get per gallon of fuel saves money and helps the environment, too.  But knowing if you're getting good mileage requires some data analysis, which gives us a good opportunity to apply one of the common tools used in Six Sigma -- the I-MR (individuals and moving range) control chart to daily life.    Finding Trends or Unusual... Continue Reading
Using statistical techniques to optimize manufacturing processes is quite common now, but using the same approach on social topics is still an innovative approach. For example, if our objective is to improve student academic performances, should we increase teachers wages or would it be better to reduce the number of students in a class? Many social topics (the effect of increasing the minimum... Continue Reading
The no-hitter is one of the most impressive feats in baseball. It’s no easy task to face more than 27 batters without letting one of them get a hit. So naturally, no-hitters don’t occur very often. In fact, since 1900 there has been an average of only about 2 no-hitters per year. But what if you had the opportunity to bet that one wouldn’t occur? That’s exactly what happened to sportswriter C. Trent... Continue Reading
Screening experimental designs allow you to study a very large number of factors in a very limited number of runs. The objective is to focus on the few factors that have a real effect and eliminate the effects that are not significant. This is often the initial typical objective of any experimenter when a DOE (design of experiments) is performed. Table of Factorial Designs Consider the table below.... Continue Reading
by Lion "Ari" Ondiappan Arivazhagan, guest blogger In India, we've seen this story far too many times in recent years: Timmanna Hatti, a six-year old boy, was trapped in a 160-feet borewell for more than 5 days in Sulikeri village of Bagalkot district in Karnataka after falling into the well. Perhaps the most heartbreaking aspect of the situation was the decision of the Bagalkot district... Continue Reading
Do you suffer from PAAA (Post-Analysis Assumption Angst)? You’re not alone. Checking the required assumptions for a statistical  analysis is critical. But if you don’t have a Ph.D. in statistics, it can feel more complicated and confusing than the primary analysis itself. How does the cuckoo egg data, a common sample data set often used to teach analysis of variance, satisfy the following formal... Continue Reading
Choosing the right type of subgroup in a control chart is crucial. In a rational subgroup, the variability within a subgroup should encompass common causes, random, short-term variability and represent “normal,” “typical,” natural process variations, whereas differences between subgroups are useful to detect drifts in variability over time (due to “special” or “assignable” causes). Variation within... Continue Reading
by Iván Alfonso, guest blogger I'm a huge fan of hot cakes—they are my favorite dessert ever. I’ve been cooking them for over 15 years, and over that time I’ve noticed many variation in textures, flavor, and thickness. Personally, I like fluffy pancakes. There are many brands of hotcake mix on the market, all with very similar formulations. So I decided to investigate which ingredients and inputs... Continue Reading
The calendar just flipped to August, meaning it’s time to get ready for fantasy football season! As you prepare for your draft, you will no doubt be looking at all sorts of rankings. But when the season is over, do you ever go back and see how accurate those rankings were? And are rankings for some positions more accurate than others? Well that’s exactly what we’re going to find out! I went back... Continue Reading
In Part I, Part II, and Part III we shared our experiment, the survey results, and the experimental results. To wrap things up, we're going to see if the survey results tied to the experimental results in any meaningful way... First, we look at whether self-identified knowledge correlated to the total number of correct appraisals: We have no evidence of a relationship (p = 0.795).  So we'll look... Continue Reading