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DTSTART:19700308T020000
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UID:2140535:Event:252670
DTSTAMP:20260522T212005Z
SUMMARY:Confidence-Reliability Calculations and Statistically Valid Sa
 mple Sizes
DESCRIPTION:Overview:The webinar begins with a discussion of relevant 
 regulatory requirements, as motivation for calculating \"confidence/re
 liability\". Then, some vocabulary and basic concepts are discussed.\n
 Next, detailed descriptions are given for how to calculate confidence/
 reliability for data that is either pass/fail (i.e., \"attribute\" dat
 a), normally-distributed measurement data, non-normally distributed me
 asurement data that can be transformed into normality, or non-normally
  distributed measurement data that cannot be transformed into normalit
 y. Spreadsheets are shown as examples of how to implement the methods 
 described in the webinar. A final discussion is provided on how to int
 roduce the methods into a company.Why should you attend: All manufact
 uring and development companies perform testing and/or inspections tha
 t involve concluding whether or not a product or lot is acceptable vs.
  design or QC specifications. Such test/inspections may occur during d
 esign verification/validation or during incoming or final QC. The most
  informative method for analyzing the data that results from such acti
 vities is the calculation of the product's or lot's \"reliability\" at
  a chosen \"confidence\" level (where \"reliability\" means \"in-speci
 fication\"). Such a method produces information that is more valuable 
 than simply that the given product or lot \"passed\" (as is the case w
 hen \"AQL Attribute Sampling Plans\" are used) or a % in-specification
  statement without any corresponding confidence statement (as is the c
 ase with AQL Variables Sampling Plans and with Process Capability calc
 ulations).Areas Covered in the Session:\n\nRegulatory Requirements\nVo
 cabulary and Concepts\nAttribute Data\nNormal Data\nNormal Probability
  Plotting\nNon-Normal Data that can be normalized\nReliability Plottin
 g (for data that cannot be normalized)\nImplementation Recommendations
 \n\nWho Will Benefit:\n\nQA/QC Supervisor\nProcess Engineer\nManufactu
 ring Engineer\nQC/QC Technician\nManufacturing Technician\nR&D Enginee
 r\n\n\n\n\nSpeaker ProfileJohn 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 consult
 ant in the area of Applied Statistics only. His consulting clients in 
 the area of statistics have included numerous start-ups as well as lar
 ge corporations such as Boston Scientific, Novellus, and Siemens Medic
 al.\nEvent link:\nhttps://www.compliance4all.com/webinar/-502878LIVE?c
 hannel=medtechiq_2020_SEO\nContact Info\nNet zealous LLC, DBA -Complia
 nce4all\nEmail: support@compliance4All.com\nPhone: +1-800-447-9407\nWe
 bsite: https://www.compliance4all.com/\n\n\n\nFor more information vis
 it https://medtechiq.ning.com/events/confidence-reliability-calculatio
 ns-and-statistically-valid
DTSTART;TZID=America/New_York:20200318T100000
DTEND;TZID=America/New_York:20200318T130000
CATEGORIES:online, event
LOCATION:Online
WEBSITE:https://www.compliance4all.com/webinar/confidence-reliability-
 calculations-and-statistically-valid-sample-sizes-502878LIVE
URL:https://www.compliance4all.com/webinar/confidence-reliability-calc
 ulations-and-statistically-valid-sample-sizes-502878LIVE
CONTACT:+1-800-447-9407
ORGANIZER:Compliance4all
ATTACH;FMTTYPE="image/jpeg":
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=ACCEPTED;RSVP=TRUE;CN="Adam Fle
 ming":https://medtechiq.ning.com/profile/Compliance4all
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