Determining Sample Size: What Sample Size Should I Use?
In this session author will speak about Basic Statistics and Common Applications requiring sample size determination
October 8, 2020
10:00 AM PDT | 01:00 PM EDT
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Product Id : 503362
Live: One Dial-in One Attendee
Corporate Live: Any number of participants
Recorded: Access recorded version, only for one participant unlimited viewing for 6 months ( Access information will be emailed 24 hours after the completion of live webinar)
Corporate Recorded: Access recorded version, Any number of participants unlimited viewing for 6 months ( Access information will be emailed 24 hours after the completion of live webinar)
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:
Who Will Benefit:
- 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)
- 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
Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. He has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.
Mr. Wachs is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Mr. Wachs regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.
He has an M.A. in Applied Statistics from the University of Michigan, an M.B.A, Katz Graduate School of Business from the University of Pittsburgh, 1992, and a B.S., Mechanical Engineering from the University of Michigan.