Understanding, Calculating, and Using Statistical Power

Overview: 

Statistical power is an indicator of the ability of a test of significance to "detect" a practical difference (e.g., between the averages of two products that are being compared).  A low power typically means that the sample sizes in the study are too small.  Without an analysis of statistical power, a conclusion of "non-significant" is rightfully questionable.  Unless power is high, a study may be doomed to failure even before it is begun.

This webinar provides thorough training in how to interpret and use the power-analysis outputted by text-book calculations or software programs modules(e.g.,StatgraphicsCenturionXV). 

Why should you Attend: 

Whenever a test of statistical significance is conducted with the hope that the result will be non-significant, the results may be unacceptable to a regulatory agency unless the test had an acceptable level of "power".  FDA typically requires a minimum of 80% power, and often requires 90% power.  Calculation of power is so complicated that it typically must be done with a software program.  Even so, the software program's output can be misunderstood unless the user has a firm understanding of the basic concept of statistical power.

This seminar explains the basics, by using a t-test as an example.  One of the very many possible formulas is then demonstrated, as well as 2 different software programs and their "Power Curves". 

This webinar is designed to help you understand how the new rules for the sanitary transportation of human and animal foods will impact your short and long food movement logistics operations and to provide you with some of the tools needed to meet new regulations and customer demands. 

Areas Covered in the Session:

• Vocabulary and Concepts
• t-Tests and p-values
• Statistical power
  • for t-Tests
  • critical difference to detect
  • example calculations
  • Power Curves

Who Will Benefit:

• QA/QC Supervisor
• Process Engineer
• Manufacturing Engineer
• QC/QC Technician
• Manufacturing Technician
• R&D Engineer