Submit an Excel spreadsheet with your work.
Student Learning Outcomes
After this exercise, students will be able to:
- Prepare a linear calibration curve from experimental data.
- Perform a linear fit, including regression statistics, in Excel.
- Use a calibration curve to determine the quantity of an unknown.
- Discuss the limitations of a calibration curve.
The purpose of this exercise is to introduce calibration curves in the context of quantitative chemical analysis.
The concentration of chloride in a water sample can be determined by a technique called ion chromatography. The instrument response is peak area (no units). A series of standard chloride solutions were prepared by diluting a 30 ppm Cl- standard by 2x, 5x, 10x, and 50x in ultra-pure water. The peak area of the undiluted and diluted solutions were 6.642, 3.250, 1.308, 0.634, 0.061, respectively.
- Prepare a calibration curve for Cl-. Perform a linear least squares fit to the data, and display the equation and R2 value on the plot.
- Determine the concentration of Cl- in a sample yielding a peak area of 1.443.
- Determine the uncertainty in the slope and intercept of the calibration curve.
- Five water samples from the same location were analyzed, yielding peak areas of 1.684, 1.454, 1.338, 1.472, and 1.443.
- Report the concentration of Cl- as the 95% confidence interval.
- Which source of error – the calibration curve or the sample reproducibility – dominates the total error in the analysis?