Yates analysis is a method of analyzing data from full and partial factorial design experiments. It requires two levels for each factor in the experiment.

In his latest article Jeremy provides great real-life examples how performing root cause analysis can change lives.

Design of Experiments is a way to intelligently form decision frameworks on how to improve a process. This is done by determine what factors into a process.

Full Factorial Design leads to experiments where at least one trial is included for all possible combinations of factors and levels.

Design of Experiments Terminology can be daunting! Here’s an easy glossary to reference when working with these types of questions.