I n the past there was only one criterion required to be a good supplier: you had to ship very few nonconforming items. If your proportion of nonconforming items took a turn for the worse ... [Read More]

This is the final column in the debate between Donald Wheeler and Forrest Breyfogle on whether or not to transform data prior to analysis. Because the debate started with Wheeler's article "Do ... [Read More]

Following my article on Leptokurtophobics (Do You Have Leptokurtophobia?) it was almost inevitable that we should hear from one. We were fortunate to have someone as articulate as Forrest Breyfogle ... [Read More]

The symptoms of leptokurtophobia are (1) routinely asking if your data are normally distributed and (2) transforming your data to make them appear to be less leptokurtic and more “mound ... [Read More]

Some authors recommend that you have to wait until you have the range chart “in control” before you can compute the limits for the average chart or the X chart. Why this is not true will be the ... [Read More]

Last month we showed the X chart in figure 1. The four lowest values and the three highest values were seen to be “outliers” when we looked at the histogram. When we fitted a bell-shaped curve ... [Read More]

Many have been taught that they must remove outliers prior to analysis. This is because much of modern statistics is concerned with creating a mathematical model for the data. Because all these models are created using algorithms, they tend to be severely affected by any unusual or extreme values. Therefore, to use these mathematical techniques to obtain useful and appropriate models, ... [Read More]

As Davis Balestracci frequently emphasized in his column, “RealWorldSPC,” published in Quality Digest for four years, it is fundamental to understand the context of the data before you begin to do any computations. It is the background for your data that determines how you should organize the data, how you should analyze the data, and how you should interpret the results of your analysis. ... [Read More]

The number of major hurricanes in the Atlantic since 1940 (as we considered in my February column, “First, Look at the Data”) are shown as a histogram in figure 1, below. Some analysts would begin their treatment of these data by considering whether they might be distributed according to a Poisson distribution. The 68 data in figure 1 have an average of 2.60. Using this value as the ... [Read More]

I recently received a data set consisting of the number of major hurricanes in the North Atlantic from 1940 to 2007. (Major hurricanes are those that reach Category 3 status or higher at some point during their existence.) The first step in analyzing any data set is to look at the data. This means plotting the data in some meaningful format. With data that form a time series, the simplest ... [Read More]