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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 »

Figures lie, so they say, and liars figure. A recent post at Ben Orlin's always-amusing mathwithbaddrawings.com blog nicely encapsulates why so many people feel wary about anything related to statistics and data analysis. Do take a moment to check it out, it's a fast read. In all of the scenarios Orlin offers in his post, the statistical statements are completely accurate, but the person offering... Continue Reading
You need to consider many factors when you’re buying a used car. Once you narrow your choice down to a particular car model, you can get a wealth of information about individual cars on the market through the Internet. How do you navigate through it all to find the best deal?  By analyzing the data you have available.   Let's look at how this works using the Assistant in Minitab 17. With the... Continue Reading

7 Deadly Statistical Sins Even the Experts Make

Do you know how to avoid them?

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Design of Experiments is an extremely powerful statistical method, and we added a DOE tool to the Assistant in Minitab 17  to make it more accessible to more people. Since it's summer grilling season, I'm applying the Assistant's DOE tool to outdoor cooking. Earlier, I showed you how to set up a designed experiment that will let you optimize how you grill steaks.  If you're not already using it and... Continue Reading
Design of Experiments (DOE) has a reputation for difficulty, and to an extent, this statistical method deserves that reputation. While it's easy to grasp the basic idea—acquire the maximum amount of information from the fewest number of experimental runs—practical application of this tool can quickly become very confusing.  Even if you're a long-time user of designed experiments, it's still easy to... Continue Reading
Earlier this month, PLOS.org published an article titled "Ten Simple Rules for Effective Statistical Practice." The 10 rules are good reading for anyone who draws conclusions and makes decisions based on data, whether you're trying to extend the boundaries of scientific knowledge or make good decisions for your business.  Carnegie Mellon University's Robert E. Kass and several co-authors devised... Continue Reading
By looking at the data we have about 500 cardiac patients, we've learned that easy access to the hospital and good transportation are key factors influencing participation in a rehabilitation program. Past data shows that each month, about 15 of the patients discharged after cardiac surgery do not have a car. Providing transportation to the hospital might make these patients more likely to join... Continue Reading
In part 2 of this series, we used graphs and tables to see how individual factors affected rates of patient participation in a cardiac rehabilitation program. This initial look at the data indicated that ease of access to the hospital was a very important contributor to patient participation. Given this revelation, a bus or shuttle service for people who do not have cars might be a good way to... Continue Reading
My previous post covered the initial phases of a project to attract and retain more patients in a cardiac rehabilitation program, as described in a 2011 Quality Engineering article. A Pareto chart of the reasons enrolled patients left the program indicated that the hospital could do little to encourage participants to attend a greater number of sessions, so the team focused on increasing initial... Continue Reading
Over the past year I've been able to work with and learn from practitioners and experts who are using data analysis and Six Sigma to improve the quality of healthcare, both in terms of operational efficiency and better patient outcomes. I've been struck by how frequently a very basic analysis can lead to remarkable improvements, but some insights cannot be attained without conducting more... Continue Reading
There has been plenty of noisy disagreement about the state of health care in the past several years, but when you get beyond the controversies surrounding various programs and changes, a great deal of common ground exists. Everyone agrees that there's a lot of waste and inefficiency in the way we've been doing things, and that health care should be delivered as efficiently and effectively as... Continue Reading
If you want to convince someone that at least a basic understanding of statistics is an essential life skill, bring up the case of Lucia de Berk. Hers is a story that's too awful to be true—except that it is completely true. A flawed analysis irrevocably altered de Berk's life and kept her behind bars for five years, and the fact that this analysis targeted and harmed just one person makes it more... Continue Reading
In an earlier post, I shared an overview of acceptance sampling, a method that lets you evaluate a sample of items from a larger batch of products (for instance, electronics components you've sourced from a new supplier) and use that sample to decide whether or not you should accept or reject the entire shipment.  There are two approaches to acceptance sampling. If you do it by attributes, you... Continue Reading
Now that we've seen how easy it is to create plans for acceptance sampling by variables, and to compare different sampling plans, it's time to see how to actually analyze the data you collect when you follow the sampling plan.  If you'd like to follow along and you're not already using Minitab, please download the free 30-day trial.  Collecting the Data for Acceptance Sampling by Variable If you'll... Continue Reading
In my last post, I showed how to use Minitab Statistical Software to create an acceptance sampling plan by variables, using the scenario of a an electronics company that receives monthly shipments of LEDs that must have soldering leads that are at least 2 cm long. This time, we'll compare that plan with some other possible options.  The variables sampling plan we came up with to verify the... Continue Reading
Earlier, I shared an overview of acceptance sampling. Now we'll look at how to do acceptance sampling by variables, facilitated by the tools in Minitab Statistical Software. If you're not already using it and you'd like to follow along, you can get the free 30-day trial version.  In contrast to acceptance sampling by attributes, where inspectors make judgment calls about defective items,... Continue Reading
If you're just getting started in the world of quality improvement, or if you find yourself in a position where you suddenly need to evaluate the quality of incoming or outgoing products from your company, you may have encountered the term "acceptance sampling." It's a statistical method for evaluating the quality of a large batch of materials from a small sample of items, which statistical softwar... Continue Reading
Many of us have data stored in a database or file that we need to analyze on a regular basis. If you're in that situation and you're using Minitab Statistical Software, here's how you can save some time and effort by automating the process. When you're finished, instead of using File > Query Database (ODBC) each time you want to perform analysis on the most up-to-date set of data, you can add a... Continue Reading
When you work in data analysis, you quickly discover an irrefutable fact: a lot of people just can't stand statistics. Some people fear the math, some fear what the data might reveal, some people find it deadly dull, and others think it's bunk. Many don't even really know why they hate statistics—they just do. Always have, probably always will.  Problem is, that means we who analyze data need to com... Continue Reading
Not long ago, I couldn’t abide statistics. I did respect it, but in much the same way a gazelle respects a lion. Most of my early experiences with statistics indicated that close encounters resulted in pain, so I avoided further contact whenever possible. So how is it that today I write about statistics? That’s simple: it merely required completely reinventing the way I thought about and approached... Continue Reading
P-values are frequently misinterpreted, which causes many problems. I won't rehash those problems here here since my colleague Jim Frost has detailed the issues involved at some length, but the fact remains that the p-value will continue to be one of the most frequently used tools for deciding if a result is statistically significant.  You know the old saw about "Lies, damned lies, and... Continue Reading