Statistical Tolerance Intervals & Limits: What, Why, How, & Alternatives
March 11, 2020
10:00 AM PDT | 01:00 PM EDT
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Product Id : 502902
Live: One Dial-in One Attendee
Corporate Live: Any number of participants
Recorded: Access recorded version, only for one participant unlimited viewing for 6 months ( Access information will be emailed 24 hours after the completion of live webinar)
Corporate Recorded: Access recorded version, Any number of participants unlimited viewing for 6 months ( Access information will be emailed 24 hours after the completion of live webinar)
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.
Why you should Attend:
- 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
- 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 calculated 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.
Attendees will have access to speaker's website, for download of articles, example-SOP's, and demo-software on a variety of statistical topics.
Areas Covered in the Session:
Who Will Benefit:
- 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
- QA/QC Supervisor
- Process Engineer
- Manufacturing Engineer
- QC/QC Technician
- Manufacturing Technician
- R&D Engineer
John N. 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.