Figures of merit are a way for analytical chemists to characterize a method. The six figures of merit we will use are precision, accuracy, sensitivity, linear dynamic range, detection limit, and selectivity.
In order to complete this exercise, first download the “InClass 2 Figures of Merit” Excel file from Canvas. It is the In-Class Assignments Module.
After completing this exercise, students will be able to:
- Calculate the standard deviation and confidence interval for a data set.
- Describe the precision of a data set.
- Describe the accuracy of a data set.
- Estimate the sensitivity and linear dynamic range from a calibration curve.
- Calculate the detection limit and limit of quantitation from a data set.
- Using the data on the Precision and Accuracy tab, calculate the average, standard deviation, percent relative standard deviation, and 95% confidence interval.
- What is the precision of the data?
- The known value for the data is 0.1500. Is there evidence of bias? Support your answer.
- A calibration curve is presented in the Calibration Curve tab, where the response of a method is plotted versus the analyte concentration.
- Estimate the linear region of the data. One way to approach this problem is to selectively remove data points from the plot until you maximize the R2 value. If you do not know how to do this, I will be happy to show you.
- What is the sensitivity in the linear region? Note – sensitivity has units.
- Data are presented in the Limit of Detection tab for 10 replicate measurements of a 4.00 mM sample ([A] = 4.00 mM) and 10 replicate measurements of a blank ([A] = 0 mM). Perform the following calculations in the spreadsheet. Use the calibration curve from part (2) to determine the slope.
- Calculate the signal detection limit.
- Calculate the limit of detection.
- Calculate the signal quantitation limit.
- Calculate the limit of quantitation.
Submit the completed Excel spreadsheet through Canvas. Answer all questions directly on the Excel spreadsheet.