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14: Developing a Standard Method

  • Page ID
    127244
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    In Chapter 1 we made a distinction between analytical chemistry and chemical analysis. Among the goals of analytical chemistry are improving established methods of analysis, extending existing methods of analysis to new types of samples, and developing new analytical methods. Once we develop a new method, its routine application is best described as chemical analysis. We recognize the status of these established methods by calling them standard methods.

    Numerous examples of standard methods are presented and discussed in Chapters 8–13. What we have yet to consider is what constitutes a standard method. In this chapter we discuss how we develop a standard method, including optimizing the experimental procedure, verifying that the method produces acceptable precision and accuracy in the hands of a single analyst, and validating the method for general use.

    • 14.1: Optimizing the Experimental Procedure
      This page discusses the quantitative analysis of vanadium by measuring the absorbance of a reddish-brown compound formed in the presence of H2O2 and H2SO4. It elaborates on optimization strategies for maximizing the system's response, which involves the concentrations of these reagents.
    • 14.2: Verifying the Method
      The page outlines the process of determining a method's effectiveness in a single-analyst scenario, involving the evaluation of precision, accuracy, and detection limits through single-operator characteristics, blind analysis, and ruggedness testing. It highlights the comparison of new and standard methods and describes ruggedness testing through experimental design to assess variability factors.
    • 14.3: Validating the Method as a Standard Method
      For an analytical method to be useful, an analyst must be able to achieve results of acceptable accuracy and precision. Verifying a method, as described in the previous section, establishes this goal for a single analyst. The process by which we approve a method for general use is known as validation and it involves a collaborative test of the method by analysts in several laboratories.
    • 14.4: Using Excel and R for an Analysis of Variance
      This page provides guidance on conducting an analysis of variance (ANOVA) using both Excel and R. Excel's Analysis ToolPak simplifies ANOVA, allowing users to input data and parameters to obtain results, including statistical measures like mean, variance, F-value, and p-values. R, on the other hand, requires coding but offers additional features like Tukey's honest significant difference test to identify sources of significant differences.
    • 14.5: Problems
      This page outlines a series of problems in experimental design and analysis, including factorial and simplex optimization methods in chemometrics, response surface determination through factorial design, and model validation.
    • 14.6: Additional Resources
      This page provides a collection of practical experiments and discussions focused on optimizing experimental conditions in chemistry. It includes examples of various optimization techniques such as simplex optimization, factorial design, and fitting experimental data to response surfaces. Additionally, it discusses mathematical modeling, ANOVA calculations, and method validation in analytical chemistry.
    • 14.7: Chapter Summary and Key Terms
      This chapter discusses the development of standard analytical methods in chemistry, focusing on optimizing experimental conditions, verifying precision and accuracy, and ensuring methods are suitable for general use. It outlines approaches such as one-factor-at-a-time and simplex optimization to find optimal responses.


    This page titled 14: Developing a Standard Method is shared under a CC BY-NC-SA 4.0 license and was authored, remixed, and/or curated by David Harvey.

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