Statistical Tolerance Intervals & Limits: What, Why, How, & Alternatives

Instructor: John N Zorich
Product ID: 706349
Training Level: Intermediate
  • 6
  • May 2020
    Wednesday
  • 10:00 AM PDT | 01:00 PM EDT
    Duration: 60 Min
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". You will learn how "Normal Tolerance Intervals" are calculated, and how to transform non-normal data into Normality, 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.

Live Online Training
May 06, Wednesday 10:00 AM PDT | 01:00 PM EDT | Duration: 60 Min

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recorded version

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CD/USB and Ref. material will be shipped within 15 business days after completion of Live training

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Read Frequently Asked Questions

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...

  • what is a Statistical Tolerance Interval and how it differs from a Confidence Interval, a Prediction Interval, or a non-statistical Tolerance Interval
  • how to identify a distribution (e.g., Normality)
  • how to transform to Normality or other distribution
  • how to calculate Tolerance Interval Limits
  • when software programs are needed for calculations
  • what alternative to Statistical Tolerance Intervals is available.

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...

  • practical uses for TI's
  • theoretical foundation for TI's
  • how TI Limits are calculated
  • how to decide whether or not the raw sample data needs to be "transformed"
  • how to decide on which "transformation" to use
  • how to calculate TI Limits based upon "transformed" data
  • how to reverse-transform TI Limits back into units of the raw sample data
  • an alternative to TI's

Areas Covered in the Webinar:

  • Statistical Tolerance Limits
  • Non-statistical Tolerance Limits
  • Identification of Distributions
  • Data Transformations
  • Theoretical Basis of Statistical Tolerance Limits
  • Calculation of Statistical Tolerance Limits for raw data
  • Calculation of Statistical Tolerance Limits transformed non-normal data
  • When it is best to use Software Programs
  • Recommended Alternative to Tolerance Limits

Who Will Benefit:

  • QA/QC Supervisor
  • Process Engineer
  • Manufacturing Engineer
  • QC/QC Technician
  • Manufacturing Technician
  • R&D Engineer

From the following Industries:

  • Design/manufacturing in the Medical Device and Pharmaceutical Industries

Free Materials:

  • Attendees will have access to speaker's website, for download of articles, example-SOP's, and demo-software on a variety of statistical topics.
Instructor Profile:
John N Zorich

John N Zorich
Statistical Consultant and Trainer, Statistical Consultant

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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Refund Policy

Registrants may cancel up to two working days prior to the course start date and will receive a letter of credit to be used towards a future course up to one year from date of issuance. ComplianceOnline would process/provide refund if the Live Webinar has been cancelled. The attendee could choose between the recorded version of the webinar or refund for any cancelled webinar. Refunds will not be given to participants who do not show up for the webinar. On-Demand Recordings can be requested in exchange.

Webinar may be cancelled due to lack of enrolment or unavoidable factors. Registrants will be notified 24hours in advance if a cancellation occurs. Substitutions can happen any time.

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