Total 28 Posts

Fun with Confidence Intervals – Part 2

Last night we began our discussion on confidence intervals. Specifically, we talked about the difference between population and sample parameters and how they play a major role in understanding what a confidence interval is. Tonight I am going to demonstrate how you can calculate a confidence interval of the mean.

Six Sigma Control Phase is Not Anti-Lean

Last night I posted a question and now realize I was a bit too vague.  This question was brought on due to a recent conversation I had with someone who asked me if I thought the “control” phase in the six sigma DMAIC roadmap was perhaps a bit too dictatorial, and even

Explaining the Central Limit Theorem

If you hate statistics this post is for you. Why? Because it’s my intention to have you understand AND be in position to teach others one of the more complicated and misunderstood statistical concepts of our time – the central limit theorem (CLT) – by the end of this article.  If

10 Steps to Creating a FMEA

A Failure Modes Effect Analysis (FMEA) is an extremely powerful tool that anyone can, and will, benefit from no matter your occupation or status in life. Tonight, we’ll discuss the history of the FMEA, the different types of FMEA, and finally how to actually construct one.  At the end of the

How beer influenced statistics

Back in the early 1900s a certain W.S. Gosset, an Englishmen, was tasked with brewing better beer.  Really, I’m being serious. Gosset was a bright man, with two degrees from Oxford, and was hired by Guinness to help them brew the best beer using statistical methods instead of the “tribal knowledge” approach most

5 Steps to Data Collection

In most Six Sigma training programs and text books  you will hear about a 5 step data collection process.  However, what they don’t tell you is that collecting data is tricky.  Many people think they can simply run off and grab some data, whip it into a spreadsheet, press some

Repetitions versus Replications

Many Lean & Six Sigma practitioners struggle to differentiate between a repetition and replication. Normally this confusion arises when dealing with Design of Experiments (DOE). Let’s use an example to explain the difference. Paint Booth DOE Design Sallie wants to run a DOE in her paint booth. After some brainstorming

Taguchi Index – Cpm

Last night we discussed the Taguchi Loss Function and how Taguchi methods are more concerned with hitting the target compared to more traditional methods that often focus on keeping our data between the upper and lower specification limits. Cpm Staying with this theme I now want to introduce Taguchi’s version

Taguchi Loss Function

Saying the words “Genichi Taguchi” to a hard core “western statistician” may get you some dirty looks. Actually, some of these crazy statisticians may want to strike you for saying this person’s name. Why the hate you may ask?  Good question. Let me give you my take on it. Genichi

Span – GE’s Variation Weapon

GE is arguably one of the best examples of Six Sigma excellence today. An often heard phrase is, “Motorola invented Six Sigma and GE perfected it.”A slick “variation weapon” GE has developed is called Span. I have never worked for GE but have worked with many former GE employees who