5: Standardizing Analytical Methods

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Jun 23, 2019
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The American Chemical Society’s Committee on Environmental Improvement defines standardization as the process of determining the relationship between the signal and the amount of analyte in a sample.¹ In Chapter 3 we defined this relationship as

$S_{\large{\textrm{total}}}=k_{\large{\textrm A}}n_{\large{\textrm A}}+S_{\large{\textrm{reag}}}\hspace{5mm}\textrm{or}\hspace{5mm}S_{\large{\textrm{total}}}=k_{\large{\textrm A}}C_{\large{\textrm A}}+S_{\large{\textrm{reag}}}$

where $S_{total}$ is the signal, $n_A$ is the moles of analyte, $C_A$ is the analyte’s concentration, $k_A$ is the method’s sensitivity for the analyte, and $S_{reag}$ is the contribution to $S_{total}$ from sources other than the sample. To standardize a method we must determine values for $k_A$ and $S_{reag}$ . Strategies for accomplishing this are the subject of this chapter.

Thumbnail: Illustration showing the evaluation of a linear regression in which we assume that all uncertainty is the result of indeterminate errors affecting y. The points in blue, y_i, are the original data and the points in red, ŷ_i, are the predicted values from the regression equation, ŷ = b₀ + b₁x. The smaller the total residual error (equation 5.16), the better the fit of the straight-line to the data

Contributors

David Harvey (DePauw University)

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