256 pages, 40 illustrations
Statistical techniques have assumed an integral role in both the interpretation and quality assessment of analytical results. In this book the range of statistical methods available for such tasks are described in detail, with the advantages and disadvantages of each technique clarified by use of examples. With a focus on the essential practical application of these techniques the book also includes sufficient theory to facilitate understanding of the statistical principles involved. Statistical Treatment of Analytical Data is written for professional analytical chemists in industry, government and research institutions who require a practical understanding of the application of statistics in day to day activities in the analytical laboratory. It is also for students who require further and detailed information that may not be available directly in a typical undergraduate course.
What makes this book stand out is its introductory and fundamental character and its good working up from a didactic point of view with easily understandable examples from the fields of analytical chemistry. This enables the reader to understand the selected statistical and mathematical methods introduced. "This book can be recommended to students and scientists who are interested in a brief introduction to selected statistical and mathematical methods for treatment of analytical data. It gives a good overview of the mathematical fundamentals of the methods presented. Simple examples from the practice of analytical chemistry substantiate the reader's understanding of what happens if chemometric methods are applied." Anal Bioanal Chem 2006
1: Introduction 2: Statistical Measures of Experimental Data 3: Distribution functions 4: Confidence limits of the mean 5: Significance test 6: Outliers 7: Instrumental Calibration - Regression Analysis 8: Identification of analyte by multi measurement analysis 9: Smoothing of Spectra Signals 10: Peak Search and Peak Integration 11: Fourier Transform Methods 12: General and specific issues in uncertainty analysis 13: Artificial Neural Networks in Analytical Chemistry
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