Last updated on Oct 12, 2024

How do you use SPC to detect and correct skewness and kurtosis in your data?

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Statistical Process Control (SPC) is a method of monitoring and improving the quality and consistency of a process by using data and statistical tools. One of the aspects of data quality that SPC can help you with is the shape of the distribution of your measurements, which can be described by two parameters: skewness and kurtosis. Skewness measures how asymmetric your data is, while kurtosis measures how peaked or flat your data is. In this article, you will learn how to use SPC to detect and correct skewness and kurtosis in your data, and why it matters for your process performance.

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