Overdispersion of data

One of my Master Black Belt students sent me an inquiry about a manufacturing process that was producing a very small percentage of scrap.  He was having trouble understanding the control charts that he had created from his data and was convinced that he needed to perform a transformation on the underlying data. I started […] read more

On July 20th, 2016, posted in: Project Management by

Lies and Statistics……

One of my Black Belt students recently submitted his final project report.  He used the two proportions test in Minitab to compare the proportion of on time performance for completion of employee appraisals, before and after improvement.  I sent him the following feedback regarding this test. “Hi.  Your null and alternate hypotheses are correctly stated.  […] read more

On July 9th, 2016, posted in: Articles, Six Sigma by Tags: ,

The Central Limit Theorem

Although the central limit theorem can seem abstract and devoid of any practical application, this theorem is actually quite important to the practice of statistics.  As we will see, this theorem allows us to make some assumptions about a population. In order to understand the basis for the Central Limit Theorem, consider a population of […] read more

On June 16th, 2016, posted in: Articles, Six Sigma by Tags: ,

Percentage data – is it continuous or discrete?

I received the following email in response to a previous article about discrete and continuous data.  The exchange has been edited slightly for ease of reading. “Hello Roger.  I enjoyed your posted article regarding discrete and continuous data. I have encountered similar discussions with other Industrial Engineers and Master Black Belts over the years. As […] read more

On June 2nd, 2016, posted in: Six Sigma by Tags: , ,