Valid Statistical Rationales for Sample Sizes
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Website https://www.traininng.com/webinar/valid-statistical-rationales-for-sample-sizes-200422live?ourglocal |
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Category Supervisor, Process Engineer, Manufacturing Engineer, Manufacturing Technician
Deadline: December 03, 2018 | Date: December 05, 2018
Venue/Country: Online, U.S.A
Updated: 2018-11-13 17:50:42 (GMT+9)
Call For Papers - CFP
OverviewThis webinar explains the logic behind sample-size choice for several statistical methods that are commonly used in verification or validation efforts, and how to express a valid statistical justification for a chosen sample size.The statistical methods discussed during the webinar include the following:Confidence intervalsProcess Control ChartsProcess Capability IndicesConfidence / Reliability CalculationsMTBF Studies ("Mean Time Between Failures" of electronic equipment)QC Sampling PlansWhy should you AttendAlmost all manufacturing and development companies perform at least some verification testings or validation studies of design-outputs and/or manufacturing processes, but it is sometimes difficult to explain the rationale for the sample sizes used in such efforts. This webinar provides guidance on how to justify such sample sizes, and thereby indirectly provides guidance on how to choose sample sizes.Areas Covered in the SessionIntroductionExamples of regulatory requirements related to sample size rationaleSample versus PopulationStatistic versus ParameterRationales for sample size choices when usingConfidence IntervalsAttribute dataVariables dataStatistical Process Control C harts (e.g., XbarR)Process Capability Indices (e.g., Cpk )Confidence/Reliability CalculationAttribute dataVariables data (e.g., K-tables)Significance Tests ( using t-Tests as an example )When the "significance" is the desired outcomeWhen "non-significance" is the desired outcome (i.e., "Power" analysis)AQL sampling plansExamples of statistically valid "Sample-Size Rationale" statementsWho Will BenefitQA/QC SupervisorProcess EngineerManufacturing EngineerQA/QC TechnicianManufacturing TechnicianR&D EngineerSpeaker 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 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.
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