The class will cover the understanding the properties of single test results and how they may be compared.
There are many problems that arise from a misunderstanding of the properties of single data sets and the problems are compounded when data sets are compared. The discussion will cover the misconceptions and present methods to allow proper comparisons, while considering the risks inherent in decisions based on analytical data.
Areas Covered in the Session: - Averages and their properties that affect decision making.
- The proper way to compare averages.
- The selection of sample sizes with the attendant risks.
- The interaction of variation and sample sizes.
- How to compare the variation observed in two different data sets.
- How to make predictions of intervals for future data, and the use of these predictions for setting specifications.
Who Will Benefit: - Workers in Quality Control Laboratories.
- Supervisors of workers who perform analytical testing.
- Managers who must make decisions based on analytical data.
- Planners who must make predictions of future performance based on current test data.
- Reviewers who must understand the relationships among analytical data.
