Statistical Elements of Sample Size Calculations for Non-Clinical Verification and Validation Studies
Duration: 90 Minutes
This webinar provides the logic and processes for determining samples sizes for common tests used in verification or validation of processes. The focus of this webinar is on providing the information needed for attendees to know the appropriate measures and formulas to use for the determining sample size and providing justification for the planned sample sizes.
- Understand statistical concepts and terminology related to sample size determination
- Use of open-source GPower software to perform sample size calculations
- How to write a justification statement for the rationale used to determine sample size.
- Regulatory Requirements for sample size in verification and validation
- Population vs. Sample, Statistical Theory and Terminology
- Confidence Intervals
- Statistical Process Control Charts
- Process Capability Indices
- Confidence/Reliability Calculations
- Tests of Significance
- Mean Time Between Failure (MTBF) studies
- Example of sample size determination
- Tips for writing “sample size rationale” statements that are statistically sound.
Verification and validation studies of design-outputs and/or manufacturing processes are required in many manufacturing processes. However, it can be difficult to understand the rational for same sizes used in these contexts. This webinar will be useful to those interested in learning how to make and justify the reasoning behind sample size determination.
Learn the theory, terminology, regulatory requirements, best practices, and of course, the steps for calculating sample sizes for process verification and validation.
NOTE: This webinar does not address rationales for sample sizes used in clinical trials.
- QA/QC Supervisor
- Process Engineer
- Manufacturing Engineer
- QA/QC Technician
- Manufacturing Technician
- R&D Engineer
Elaine Eisenbeisz is a private practice statistician and owner of Omega Statistics, a statistical consulting firm based in Southern California.
Elaine earned her B.S. in Statistics at UC Riverside and received her Master’s Certification in Applied Statistics from Texas A&M.
Elaine is a member in good standing with the American Statistical Association and a member of the Mensa High IQ Society. Omega Statistics holds an A+ rating with the Better Business Bureau.
Elaine has designed the methodology and analyzes data for numerous studies in the clinical, biotech, and health care fields. Elaine has also works as a contract statistician with private researchers and biotech start-ups as well as with larger companies such as Allergan, Nutrisystem and Rio Tinto Minerals. Throughout her tenure as a private practice statistician, she has published work with researchers and colleagues in peer-reviewed journals.
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