Understanding the Calibration Curve
The linear fit "looks good" and the correlation coefficient is "three nines." This must be a good curve, right? Unfortunately, if you reanalyzed the standards as samples, you would find that five of the eight standards were in error by more than five percent. Three of the standards are in error by more than 15% from their known values! Clearly, the usual procedures for evaluating calibration curves are not always accurate.
There is more to understanding calibration curves than just running standards and measuring the correlation coefficient! The calibration curve is one of the most important steps in the generation of analytical data. We will show you how to do it the right way (and it isn't difficult)!
When properly designed, the calibration system provides accurate results with a minimum of effort. However, a poorly constructed system can waste valuable instrument and analyst time, and result in poor quality data.
This seminar will provide a complete set of instructions on how to set up and evaluate any analytical calibration system, with an emphasis on providing the highest quality results with a minimum of effort. Examples are drawn from GC, LC, GC/MS, and AA data sets. Spreadsheet programming examples are included in the course notes.
This course provides valuable and practical information that is not currently available from any other single reference source.
Students will learn:
Course Length: 1/2 day
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