What Are Good Measurements?Consistency trumps precision
Mon, 05/19/2014 - 18:06
Who could ever be against having good measurements? Good measurements are like apple pie and motherhood. Since we all want good measurements, it sounds reasonable when people are told to check out the quality of their measurement system before… The Data-Free GraphHow to streamline your analysis
Tue, 04/01/2014 - 13:59
Why bother to plot your data? A simple shortcut is available that will allow you to do your analysis without the data getting in the way. How do you accomplish this breakthrough? Read on.
This marvelous advance in analysis is known as the “data-… Statistics and SPCTwo things sharing a common name can still be different
Mon, 03/03/2014 - 17:46
Students typically encounter many obstacles while learning statistics. In 44 years of teaching I have discovered some distinctions that help students overcome these obstacles. This article will remove some sources of confusion concerning the… Why Use Ranges?What they didn’t teach in your stat class
Mon, 02/03/2014 - 16:29
Last month in “The Analysis of Experimental Data,” I presented a method for analyzing experimental data that was built on the use of the range statistic as a measure of dispersion. In this day of computers and software, why should we even consider… The Analysis of Experimental DataMinimizing the complexity improves communication
Mon, 01/06/2014 - 12:26
You have spent good money obtaining your experimental results, and now the time has come to communicate those results to those who need to take action. This column will describe how to cut through the complexities of your analysis and communicate… Gauge R&R Methods ComparedHow do the ANOVA, AIAG, and EMP approaches differ?
Mon, 12/02/2013 - 17:05
It would appear that there is still considerable confusion regarding which method to use in evaluating a measurement process. There are many voices speaking on this subject, however, most of them fail to use the guidance provided by statistical… Separating the Signals From the NoiseEssential knowledge for all who seek to understand their data
Thu, 10/03/2013 - 15:13
The second principle for understanding data is that some data contain signals; however, all data contain noise. Therefore, before you can detect the signals you will have to filter out the noise. This act of filtration is the essence of all data… More to Beware About Tukey Control ChartsAnswers to questions asked
Mon, 09/09/2013 - 15:50
Last month’s column, “Beware the Tukey Control Chart,” generated several questions of a fundamental nature that deserve expanded answers. These questions and their answers will be considered here.
Interquartile ranges
The Tukey control chart uses… Beware the Tukey Control ChartAnother bad idea surfaces
Mon, 08/05/2013 - 16:06
I recently read about a technique for analyzing data called the "Tukey control chart." Since Professor John Tukey is no longer with us, it appears that someone without his brilliance has tried to adapt one of his techniques into an alternative type… The Problem of Long-Term CapabilityPoor labels lead to incorrect ideas
Mon, 07/08/2013 - 14:38
Based on some recent inquiries there seems to be some need to review the four capability indexes in common use today. A clear understanding of what each index does, and does not do, is essential to clear thinking and good usage. To see how to use…
