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Calibration Curves (Oxley)

Last updated

Oct 27, 2020
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- Calibration Curves (Mullaugh)
- Calibration Curves (Venton)

Contributor
Analytical Sciences Digital Library

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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.
1. Report the concentration of Cl^- as the 95% confidence interval.
2. Which source of error – the calibration curve or the sample reproducibility – dominates the total error in the analysis?

Contributors and Attributions

Susan Oxley, St. Mary’s University (San Antonio) (soxley@stmarytx.edu)
Sourced from the Analytical Sciences Digital Library

Contributors and Attributions

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