Statistics Article Features

Donald J. Wheeler's picture
Donald J. Wheeler
The shape parameters for a probability model are called skewness and kurtosis. While skewness at least sounds like something we might understand, kurtosis simply sounds like jargon. Here we’ll use...
Alan Metzel's picture
Alan Metzel
Almost seven years ago, Quality Digest presented a short article by Matthew Barsalou titled “A Worksheet for Ishikawa Diagrams.” At the time, I commented concerning enhancements that provide...
Donald J. Wheeler's picture
Donald J. Wheeler
The computation for skewness does not fully describe everything that happens as a distribution becomes more skewed. Here we shall use some examples to visualize just what skewness does—and does not—...
Tony Boobier's picture
Tony Boobier
Does your use of probabilities confuse your audience? Sometimes even using numbers can be misleading. The notion of a 1-in-a-100-year flood doesn’t prevent the possibility of flooding occurring in...
Donald J. Wheeler's picture
Donald J. Wheeler
There are four major questions in statistics. These can be listed under the headings of description, probability, inference, and homogeneity. An appreciation of the relationships between these four...
Donald J. Wheeler's picture
Donald J. Wheeler
The cumulative sum (or Cusum) technique is occasionally offered as an alternative to process behavior charts, even though they have completely different objectives. Process behavior charts...
Donald J. Wheeler's picture
Donald J. Wheeler
Last month we found that capability and performance indexes have no inherent preference for one probability model over another. However, whenever we seek to convert these indexes into fractions of...
Donald J. Wheeler's picture
Donald J. Wheeler
Many people have been taught that capability indexes only apply to “normally distributed data.” This article will consider the various components of this idea to shed some light on what has, all too...
Donald J. Wheeler's picture
Donald J. Wheeler
Walter Shewhart made a distinction between common causes and assignable causes based on the effects they have upon the process outcomes. While Shewhart’s distinction predated the arrival of chaos...
William A. Levinson's picture
William A. Levinson
Quality-related data collection is useful, but statistics can also deliver misleading and even dysfunctional results when incomplete. This is often the case when information is collected only from...
Donald J. Wheeler's picture
Donald J. Wheeler
Many different approaches to process improvement are on offer today. An appreciation of the way each approach works is crucial to selecting one that will be effective. Here we look at the problem of...
Paul Laughlin's picture
Paul Laughlin
As I started reading The Book of Why: The New Science of Cause and Effect, by Judea Pearl and Dana Mackenzie (Basic Books, 2018), I was reminded how often analysts trot out the bromide “correlation...
Donald J. Wheeler's picture
Donald J. Wheeler
Students are told that they need to check their data for normality before doing virtually any data analysis. And today’s software encourages this by automatically providing normal probability plots...
Donald J. Wheeler's picture
Donald J. Wheeler
Acceptance sampling uses the observed properties of a sample drawn from a lot or batch to make a decision about whether to accept or reject that lot or batch. Although the textbooks are full of...
Danielle Underferth's picture
Danielle Underferth
As municipalities clamor for a slice of President Biden’s $1.2 trillion infrastructure spending bill, one Johns Hopkins scientist is re-examining one of the basic elements of road-building:...
Scott A. Hindle's picture
Scott A. Hindle
In 2010, new to the world of statistical process control (SPC), I was intrigued by Don Wheeler’s statement that “No data have meaning apart from their context” (from his book, Understanding...
Tristan Mobbs's picture
Tristan Mobbs
All too often the topic of fixing dirty data is neglected in the plethora of online media covering artificial intelligence (AI), data science, and analytics. This is wrong for many reasons. To...
Donald J. Wheeler's picture
Donald J. Wheeler
Last month we looked at analyzing observational data. Here we will consider experimental data and discover a weakness in the way they are obtained that can contribute to the problem of...
Atul Minocha's picture
Atul Minocha
Do you ever feel like you’re spending money like crazy on marketing and getting little or nothing in return? If so, you might be tempted to pull the plug on marketing altogether. That would be a big...
Donald J. Wheeler's picture
Donald J. Wheeler
Most of the world’s data are obtained as byproducts of operations. These observational data track what happens over time and have a structure that requires a different approach to analysis than that...