# Tag: variances

## Homogeneity of Variance and Statistical Inference: What You Need to Know

Published:There are several statistical tests which assume that independent data sets have equal, similar or equivalent variances. Violating this assumption could render any statistical conclusions invalid.

Read more »## Avoid Two Common Mistakes in Measurement System Analysis

Updated: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 […]

Read more »## Use Earned Value Management for Process Improvement

Published:Whenever there is an issue in a process, attempts are made to identify the process step that is causing the problem, identify the root cause and come up with a corrective or preventive action. The time taken to identify the “right” process step is directly proportional to the number of process steps involved and it […]

Read more »## A Simple Model of a Variance Stable Process

Published:Most fairly accurate descriptions of equipment and/or process lifetimes assume that failure rates follow a three period I II III “bathtub-curve pattern” where failures/errors: I – Decrease during the debugging or improvement time period. II – Remain relatively constant and at their lowest levels during the normal equipment or process operating period. III – Increase […]

Read more »## What You May Not Know About Adding Variances

Published:Imagine for a moment that your Six Sigma project does not have the rigorous measurement system you would like it to have, and you have to calculate your primary metric from a few inputs instead of measuring it directly. Or perhaps you are designing a new product and want to understand how the variability in […]

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