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Data Analysis

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

Maybe you're just getting started with analyzing data. Maybe you're reasonably knowledgeable about statistics, but it's been a long time since you did a particular analysis and you feel a little bit rusty. In either case, the Assistant menu in Minitab Statistical Software gives you an interactive guide from start to finish. It will help you choose the right tool quickly, analyze your data... Continue Reading
Can you trust your data?  That's the very first question we need to ask when we perform a statistical analysis. If the data's no good, it doesn't matter what statistical methods we employ, nor how much expertise we have in analyzing data. If we start with bad data, we'll end up with unreliable results. Garbage in, garbage out, as they say. So, can you trust your data? Are you positive?... Continue Reading

7 Deadly Statistical Sins Even the Experts Make

Do you know how to avoid them?

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We had solar panels fitted on our property in 2011. Last year, we had a few problems with the equipment. It was shutting down at various times throughout the day, typically when it was very sunny, resulting in no electricity being generated. In summer 2016, I completed a statistical analysis in Minitab to confirm my suspicions that my solar panels were not working as well as they did when they were... Continue Reading
In my time at Minitab, I’ve gotten a good understanding of what types of graphs users create. Everyone knows about histograms, bar charts, and time series plots. Even relatively less familiar plots like the interval plot and individual value plot are still used quite often. However, one of the most underutilized graphs we have available is the area graph. If you’re not familiar with an Area... Continue Reading
There may not be a situation more perilous than being a character on Game of Thrones. Warden of the North, Hand of the King, and apparent protagonist of the entire series? Off with your head before the end of the first season! Last male heir of a royal bloodline? Here, have a pot of molten gold poured on your head! Invited to a wedding? Well, you probably know what happens at weddings in the show. ... Continue Reading
The two previous posts in this series focused on manipulating data using Minitab’s calculator and the Data menu. In this third and final post, we continue to explore helpful features for working with text data and will focus on some features in Minitab’s Editor menu. Using the Editor Menu  The Editor menu is unique in that the options displayed depend on what is currently active (worksheet, graph,... Continue Reading
Have you ever had a probability plot that looks like this? The probability plot above is based on patient weight (in pounds) after surgery minus patient weight (again, in pounds) before surgery. The red line appears to go through the data, indicating a good fit to the Normal, but there are clusters of plotting points at the same measured value. This occurs on a probability plot when there are many... Continue Reading
My previous post focused on manipulating text data using Minitab’s calculator. In this post we continue to explore some of the useful tools for working with text data, and here we’ll focus on Minitab’s Data menu. This is the second in a 3-part series, and in the final post we’ll look at the new features in Minitab’s Editor menu. Using the Data Menu When I think of the Data menu, I think... Continue Reading
With Minitab, it’s easy to create graphs and manage numeric, date/time and text data. But Minitab’s enhanced data manipulation features make it easier to work with text data, too. This is the first of three posts in which I'm going to focus on various tools in Minitab that are useful when working with text data, including the Calculator, the Data menu, and the Editor menu. Using the Calculator You... Continue Reading
One of the biggest pieces of international news last year was the so-called "Brexit" referendum, in which a majority of voters in the United Kingdom cast their ballots to leave the European Union (EU). That outcome shocked the world. Follow-up media coverage has asserted that the younger generation prefers to remain in the EU since that means more opportunities on the continent. The older... Continue Reading
Easy access to the right tools makes any task easier. That simple idea has made the Swiss Army knife essential for adventurers: just one item in your pocket gives you instant access to dozens of tools when you need them.   If your current adventures include analyzing data, the multifaceted Editor menu in Minitab Statistical Software is just as essential. Minitab’s Dynamic Editor Menu Whether you’re... Continue Reading
It's a very exciting time at Minitab's offices around the world because we've just announced the availability of Minitab® 18 Statistical Software. Data is everywhere today, but to use it to make sound, strategic business decisions, you need to have tools that turn that data into knowledge and insights. We've designed Minitab 18 to do exactly that.  We've incorporated a lot of new features, made some... Continue Reading
Before cutting an expensive piece of granite for a countertop, a good carpenter will first confirm he has measured correctly. Acting on faulty measurements could be costly. While no measurement system is perfect, we rely on such systems to quantify data that help us control quality and monitor changes in critical processes. So, how do you know whether the changes you see are valid and not just the... 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
"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
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
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
You run a capability analysis and your Cpk is bad. Now what? First, let’s start by defining what “bad” is. In simple terms, the smaller the Cpk, the more defects you have. So the larger your Cpk is, the better. Many practitioners use a Cpk of 1.33 as the gold standard, so we’ll treat that as the gold standard here, too. Suppose we collect some data and run a capability analysis using Minitab Statisti... Continue Reading
In Part 1 of Gauging Gage, I looked at how adequate a sampling of 10 parts is for a Gage R&R Study and providing some advice based on the results. Now I want to turn my attention to the other two factors in the standard Gage experiment: 3 operators and 2 replicates.  Specifically, what if instead of increasing the number of parts in the experiment (my previous post demonstrated you would need... Continue Reading
"You take 10 parts and have 3 operators measure each 2 times." This standard approach to a Gage R&R experiment is so common, so accepted, so ubiquitous that few people ever question whether it is effective.  Obviously one could look at whether 3 is an adequate number of operators or 2 an adequate number of replicates, but in this first of a series of posts about "Gauging Gage," I want to look at... Continue Reading