Statistical Methods in Applied Chemistry deals in detail with the methods of statistical description and inference which are applied to chemical experimentation. It introduces the reader to the problems of random variables and their distributions, reviews principal statistical tests - both parametric and non-parametric, presents basic models of variance analysis, and deals with correlation of phenomena. The material is presented from the viewpoint of the experimenter. All methods are illustrated by numerical examples which reflect genuine experimental situations. Useful for students and teachers at universities and polytechnics, the book is of interest to scientists in all fields of pure and applied chemistry. Moreoever, it will be invaluable for researchers in all experimental sciences where statistical methods can be used.
Statistical Methods in Applied Chemistry deals in detail with the methods of statistical description and inference which are applied to chemical experimentation. It introduces the reader to the problems of random variables and their distributions, reviews principal statistical tests - both parametric and non-parametric, presents basic models of variance analysis, and deals with correlation of phenomena. The material is presented from the viewpoint of the experimenter. All methods are illustrated by numerical examples which reflect genuine experimental situations. Useful for students and teachers at universities and polytechnics, the book is of interest to scientists in all fields of pure and applied chemistry. Moreoever, it will be invaluable for researchers in all experimental sciences where statistical methods can be used.
Reihe
Sprache
Verlagsort
Verlagsgruppe
Elsevier Science & Technology
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Maße
ISBN-13
978-0-444-98862-1 (9780444988621)
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Schweitzer Klassifikation
Chapter 1. Random Variables. Properties and variables. Random events and elementary event space. Probability. Basic properties of probability. One-dimensional random variable. Measure of position and dispersion of one-dimensional random variable. Moments of one-dimensional random variable. Selected distributions of one-dimensional random variables. Multi-dimensional random variable. 2. Estimation of Parameters of Random Variable Distribution. Population and sample. Empirical distributions. Point estimation. Probability distributions of selected sample characteristics. Interval estimation. 3. Testing Statistical Hypotheses. Introduction. Verification of parametric hypotheses. Non-parametric hypothesis testing. Sequential tests. 4. Analysis of Variance. Theoretical model of analysis of variance for one-way classification. Computation of sum of squares. Models and assumptions of the analysis of variance. Grouping of object means; the m = m 0 hypothesis testing. Approximate test in the case of non-homogeneity of variance. Analysis of variance for two-way classification. 5. Correlation and Regression. Correlation. Regression. 6. Methodical Guidelines. Criteria of choice and evaluation of research methods. Operation on approximate numbers. Calculation of errors. Formation of sample population. Registration and analysis of results. 7. Examples of a Complete Analysis of Experiment Results. A technological example. An analytical example. Appendicex A. Statistical Tables. Appendix B. Computer Programmes and Procedures. Bibliography. Index.
