Applied Practical Statistics, with Emphases on Verification, Validation, Sample Size, and Risk Management in R&D, Mfg. and QA/QC training seminars presented by ComplianceOnline register now on FindaSeminar.com

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Applied Practical Statistics, with Emphases on Verification, Validation, Sample Size, and Risk Management in R&D, Mfg. and QA/QC  

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R&D Manager,QA/QC Manager,Manufacturing Manager,R&D Engineer,Manufacturing Engineer,Process EngineerValidation EngineerQC/QC Technician

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Seminar Summary:

Almost all design and/or manufacturing companies evaluate product and processes in order to either manage risks, validate processes, establish product/process specifications, QC to such specifications, and/or monitor compliance to such specifications. The various statistical methods used to support such activities can be intimidating. (see full course description)

 

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Training Course Syllabus:


Learning Objectives:



  • How to apply "confidence" and "risk management" to virtually all statistical techniques

  • Know when to use "exact" methods rather than "approximation" methods

  • Know when to use commercial software (e.g., Minitab, StatGraphics) and when to use Excel

  • How to explain statistics to management

  • How to interpret regulatory requirements related to statistics

  • How to determine the smallest sample size needed to achieve a desired outcome.


Areas Covered :



  • Basic regulatory requirements related to statistics (for medical devices and pharmaceuticals)

  • Basic statistical concepts and vocabulary

  • Normality, Normality Tests, and Normality Transformations

  • Statistical Process Control

  • Process and Product Capability assessments including: Confidence/Reliability Calculations, Tolerance Limits, Cpk/Ppk, and Reliability Plotting
  • Statistical Significance tests (including testing for "Superiority", "Non-inferiority", and "TOST")

  • Statistical Power

  • Metrology (statistical analysis of measurement uncertainty, including Gage R&R and "guard-banding")

  • QC Sampling Plans (AQL vs. LQL vs AOQL vs. other alternatives)

  • Statistical justification for Process Validation sample sizes and the use of only 3 Lots

  • Examples of "statistically valid rationales" regarding sample sizes.


Seminar Summary:

Almost all design and/or manufacturing companies evaluate product and processes in order to either manage risks, validate processes, establish product/process specifications, QC to such specifications, and/or monitor compliance to such specifications. The various statistical methods used to support such activities can be intimidating. (see full course description)

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