Pack of THREE: 3-Hour On-Demand Training on Sample Size Determination By 3 Statisticians

Product Id: 31000PACK


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Instructor : Steven Walfish
Product Id : 31000PACK

Overview: This webinar covers the statistical methods used to calculate sample sizes for both attribute and variables data. Methods for collecting the sample will be covered. Every sampling plan has risks. This webinar covers how to calculate Type I and Type II errors. A discussion of how the FDA views sampling plans, especially for validation and acceptance activities. Sample size to ensure a certain level of process capability will be covered.

Areas Covered in the Session:
  • How to collect a sample
  • What are the two types of error (Type I and Type II)
  • How to calculate sample sizes for variables data
  • How to calculate sample sizes for attribute data
  • Using confidence intervals on Cpk to calculate a sample size
  • Using binomial confidence intervals

Who Will Benefit:
  • Management
  • Research and Development
  • Regulatory Affairs Personnel
  • Quality Assurance/Quality Control Personnel
  • Auditors and Inspectors

Instructor : John N. Zorich
Product Id : 31000PACK

Overview: 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

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 guidance on how to justify such sample sizes, and thereby indirectly provides guidance on how to choose sample sizes. Those justifications can then be documented in Protocols or regulatory submissions, or can be given to regulatory auditors who may ask for them during onsite audits at your company. Thus, this webinar is designed to help you avoid regulatory delays in product approvals and to prevent an auditor from issuing you a nonconformity.

NOTE: This webinar does not address rationales for sample sizes used in clinical trials.

Areas Covered in the Session:
  • 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 Calculation
      • 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

Who Will Benefit:
  • QA/QC Supervisor
  • Process Engineer
  • Manufacturing Engineer
  • QC/QC Technician
  • Manufacturing Technician
  • R&D Engineer

Instructor : Steven Wachs
Product Id : 31000PACK

Overview: The webinar will provide important considerations when selecting sample sizes for specific applications. The knowledge gained by attending the webinar will allow practitioners to consider the implications of sample size selection prior to conducting the study and ensure that the information obtained can be useful for decision making.

Areas Covered in the Session:
  • Population and Samples
  • Basic Statistics
  • Common Applications requiring sample size determination (e.g. estimation, hypothesis testing, demonstration of conformance to specification)
  • Sample Size Determination (Examples)

Who Will Benefit:
  • R&D Personnel
  • Product Development Personnel
  • Quality Personnel
  • Lab Testing Personnel
  • Operations / Production Managers
  • Quality Assurance Managers, Engineers
  • Process or Manufacturing Engineers or Managers
  • Program or Product Managers
  • Business Analysts
  • Process Improvement Personnel
  • Management

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NetZealous LLC,
161 Mission Falls Lane, Suite 216,
Fremont, CA 94539, USA.


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