Why Should You Attend:
During audits by an FDA, ISO, or CE auditor, a company might be asked to justify their Statistical Tolerance Limits. Unless the company has a clear understanding of the theoretical basis of Tolerance Limits, and has chosen valid methods for calculating them, the auditor might issue the company a 483/non-conformity.
Such auditors expect that all statistical techniques used by the company be clearly described and explained in relevant SOP's or Work Instructions; this webinar can help a company write such procedural text.
A Statistical Tolerance Interval (TI) is a range of values on either side of a sample average that includes a specified proportion of the population from which the sample was drawn; the likelihood that that range includes at least the specified proportion of the population is given by a specified % confidence.
This webinar explains the practical use and theoretical basis of Statistical Tolerance Intervals and Statistical Tolerance Limits. It explains the difference between non-statistical tolerance limits and statistical ones. It explains the difference between "identifying the distribution" and "transforming the data". It explains how "Normal Tolerance Intervals" are calculated, and how to transform non-normal data into Normality. It explains how to calculate Statistical Tolerance Intervals for data that cannot be transformed to Normality. And it recommends an alternative method to using Statistical Tolerance Intervals.
An attendee will learn...
In the speaker's experience, most medical device and pharmaceutical companies use Statistical Tolerance Limits as part of their risk-management program. Typically, such companies do not understand the principles involved, and therefore tend to make judgement errors, especially when non-normal data is being analyzed; the purpose of this webinar is to prevent such mistakes.
This webinar explains...
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Who Will Benefit:
From the following Industries:
John Zorich has spent almost 40 years in the medical device manufacturing industry; the first 20 years were as a "regular" employee in the areas of R&D, Manufacturing, QA/QC, and Regulatory; the next 15 years were as a consultant in the areas of QA/QC and Statistics. These last few years were as a trainer and consultant in the area of Applied Statistics only. His consulting clients in the area of statistics have included numerous start-ups as well as large corporations such as Boston Scientific, Novellus, and Siemens Medical. His experience as an instructor in applied statistics includes having given annual 3-day seminars for many years at Ohlone College (San Jose CA), and previously having given that same course for several years for Silicon Valley ASQ Biomedical. He's given numerous statistical seminars at ASQ meetings and conferences. And he creates and sells validated statistical software programs that have been purchased by more than 110 companies, world-wide.
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