Why Should You Attend:
Almost 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 the training in how to make and word such rationales.
NOTE: This webinar does not address rationales for sample sizes used in clinical trials.
This 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 intervals
Process Control Charts
Process Capability Indices
Confidence / Reliability Calculations
MTBF Studies ("Mean Time Between Failures" of electronic equipment)
QC Sampling Plans.
Areas Covered in the Webinar:
Introduction
Examples of regulatory requirements related to sample size rationale
Sample versus Population
Statistic versus Parameter
Rationales for sample size choices when using...
Confidence Intervals
** attribute data
** variables data
Statistical Process Control C harts (e.g., XbarR)
Process Capability Indices (e.g., Cpk )
Confidence/Reliability Calculations
** attribute data
** variables data (e.g., K-tables)
Significance Tests ( using t-Tests as an example )
** when the "significance" is the desired outcome
**when "non-significance" is the desired outcome (i.e., "Power" analysis)
AQL sampling plans
Examples of statistically valid "Sample-Size Rationale" statements
Almost 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 the training in how to make and word such rationales.
NOTE: This webinar does not address rationales for sample sizes used in clinical trials.
This 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 intervals
Process Control Charts
Process Capability Indices
Confidence / Reliability Calculations
MTBF Studies ("Mean Time Between Failures" of electronic equipment)
QC Sampling Plans.
Areas Covered in the Webinar:
Introduction
Examples of regulatory requirements related to sample size rationale
Sample versus Population
Statistic versus Parameter
Rationales for sample size choices when using...
Confidence Intervals
** attribute data
** variables data
Statistical Process Control C harts (e.g., XbarR)
Process Capability Indices (e.g., Cpk )
Confidence/Reliability Calculations
** attribute data
** variables data (e.g., K-tables)
Significance Tests ( using t-Tests as an example )
** when the "significance" is the desired outcome
**when "non-significance" is the desired outcome (i.e., "Power" analysis)
AQL sampling plans
Examples of statistically valid "Sample-Size Rationale" statements
