Articles by Mark Durivage
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How To Establish Sample Sizes For Process Validation Using Variable Sampling Plans
11/28/2016
The first article in this series, Risk-Based Approaches To Establishing Sample Sizes For Process Validation (June 2016), provided and established the relationship between risk and sample size. This article will demonstrate the use of variable sampling plans to establish sample sizes for process validation.
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How To Establish Sample Sizes For Process Validation Using Statistical Tolerance Intervals
10/27/2016
This article demonstrates how to use statistical tolerance limits, which use the confidence level (how sure we are) and reliability value (population value) to determine appropriate statistically valid sample sizes for process validation.
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How To Establish Sample Sizes For Process Validation Using C=0 Sampling Plans
9/7/2016
The first article in this series, Risk-Based Approaches To Establishing Sample Sizes For Process Validation (June 2016), provided and established the relationship between risk and sample size. This article will demonstrate the use of C=0 sampling plans to establish sample sizes for process validation.
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How To Establish Sample Sizes For Process Validation Using The Success-Run Theorem
7/19/2016
This article demonstrates two methods using the success-run theorem, which uses the confidence level (how sure we are) and reliability value (valid, consistent results) to determine appropriate statistically valid sample sizes for process validation.
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Risk-Based Approaches To Establishing Sample Sizes For Process Validation
6/14/2016
Using confidence, reliability, and acceptance quality limits (AQLs) to determine sample sizes for process validation are proven methods to ensure validation activities will yield valid results based upon an organization’s risk acceptance determination threshold, industry practice, guidance documents, and regulatory requirements.