Download Basics of Analytical Chemistry and Chemical Equilibria by Brian M. Tissue PDF

By Brian M. Tissue

Content material:
Chapter 1 Making Measurements (pages 1–52):
Chapter 2 pattern practise, Extractions, and Chromatography (pages 53–102):
Chapter three Classical tools (pages 103–140):
Chapter four Molecular Spectroscopy (pages 141–175):
Chapter five Acid?Base Equilibria and job (pages 177–220):
Chapter 6 Buffer strategies and Polyprotic Acids (pages 221–244):
Chapter 7 Complexation and Precipitation Equilibria (pages 245–291):
Chapter eight Electroanalytical Chemistry (pages 293–339):
Chapter nine Atomic Spectrometry (pages 340–366):
Chapter 10 Analytical Separations (pages 367–406):

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Extra resources for Basics of Analytical Chemistry and Chemical Equilibria

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29 We will use the standard deviation of multiple measurements of a blank as a generic approach 28 See Ettre, L. S. “Nomenclature for chromatography,” Pure & Appl, Chem. pdf. Accessed 21 Feb 2013. 29 Common approaches include peak to peak, root mean square (RMS), and standard deviation. 30 We call the average value of the blank measurements the baseline or background. Related to noise is the occurrence of drift. Drift is the gradual change in blank measurements over time. When drift is present in an analytical procedure, the timing of sample and blank measurements must be performed frequently enough so that the drift does not bias the results.

To answer these questions, we use a more definitive description of the imprecision of repetitive measurements. Illustrating this concept with the example of the EPA action level of 15 ppb for lead in drinking water, suppose that a set of 30 samples from a municipal water supply showed a mean lead concentration of 14 ppb with a standard deviation of ±1 ppb. Assuming a normal distribution for the results, 68% of measurements fall between 13 and 15 ppb, 16% are lower than 13 ppb, and 16% are higher than 15 ppb.

Ca2+ must be precipitated before measurement, leading to a source of error. 6 23 Adapted with permission from Rorabacher, D. B. “Statistical treatment for rejection of deviant values: critical values of Dixon’s “Q” parameter and related subrange ratios at the 95% confidence level” Anal. Chem. 1991, 63, 139–146. Copyright 1991 American Chemical Society. 5 mV appears lower than the rest of the values in the set. Can this value be discarded? 710 for five data points. Our calculated Q is larger than Qc , so the suspected outlier may be discarded.

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