Tag: continuous data

Z bench is not where Zorro rested after saving another town. There are a number of Six Sigma terms associated with the letter Z, such as Z score, Z bench long term, Z bench short term, and Z shift. Let’s explore the A to Zs about Z.

Data analysis is a fundamental process in any project. However, data can be lumped into different types, with categorical and continuous data seeming almost opposed at first glance. That said, mastering these data types and understanding when and where to use them can lead to far more precision during data analysis as a […]

Measurement system analysis (MSA) determines whether the measurement system is adequate and confirms that significant error is not introduced to the true value of a process characteristic. MSA is the one of the most misunderstood and underused concepts in Six Sigma. This article highlights two of the common mistakes made during the study and explains […]

The distribution of data can be categorized in two ways: normal and non-normal. If data is normally distributed, it can be expected to follow a certain pattern in which the data tend to be around a central value with no bias left or right (Figure 1). Non-normal data, on the other hand, does not tend […]

In some situations, Six Sigma practitioners find a Y that is discrete and Xs that are continuous. How can a regression equation be developed in these cases? Black Belt training indicated that the correct technique is something called logistic regression but this tool is often not well understood. An example about a well-known space shuttle […]

Six Sigma projects in various industries often deal with experiments whose outcomes are not continuous variable data, but ordered categorical data. Analysis of variables (ANOVA) is a technique used to analyze continuous experimental data, but is not adequate for analyzing categorical experimental outcomes. Fortunately, many other methods have been developed to deal with categorical experiments, […]