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Mathematical Methods for Physical and Analytical Chemistry By David Z. Goodson

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Review
“Finally it can be said that this book helps to refresh and extend the knowledge about mathematical and statistical methods to be used for physico-chemical or analytical applications.” (Materials and Corrosion, 1 November 2012)
From the Back Cover
Bridging the gap between undergraduate calculus and the mathematics of chemistry
A focused presentation of statistical and advanced mathematical methods likely to be encountered by chemists, Mathematical Methods for Physical and Analytical Chemistry can serve as a text for a one-semester course at the undergraduate or graduate level, or as a resource for independent study by students and professionals in all areas of chemistry and in related fields such as environmental science, geochemistry, and chemical engineering.
Mathematical Methods for Physical and Analytical Chemistry covers:
CALCULUS—review of the basics, coordinate systems, degrees of freedom, special functions, numerical methods, complex numbers, singular points, improper integrals, Taylor series
STATISTICS—probability theory, distribution functions, confidence intervals, propagation of error, significance of difference, ANOVA, method of least squares, calibration, model testing, fits with error in both variables, experiment design, randomization, optimization
DIFFERENTIAL EQUATIONS—chemical reaction rate equations, Lagrangian and Hamiltonian mechanics, transport equations, the superposition principle, separation of variables, methods for exact, approximate, and numerical solutions
LINEAR ALGEBRA—groups, Hilbert spaces, basis sets, matrices, determinants, orthogonal polynomials, spherical harmonics, Fourier series, eigenvalue equations, diagonalization, Fourier transform, spectral lineshapes, convolution, principles of quantum mechanics, Schrödinger's equation, hydrogen orbitals, hybrid orbitals, molecular orbitals
Mathematical Methods for Physical and Analytical Chemistry features:
Modern topics such as Monte Carlo simulation, robust estimation, and discrete Fourier transform, which are otherwise available only in more specialized texts
Numerous figures and worked out examples and more than 200 exercises, many of which take advantage of computer algebra
An annotated bibliography of references for further study
About the Author
David Z. Goodson, Associate Professor of Chemistry at the University of Massachusetts Dartmouth, has a BA in chemistry from Pomona College and a PhD in chemical physics from Harvard University. An interdisciplinary scientist, he is author of numerous articles on a wide range of topics including quantum chemistry, molecular spectroscopy, reaction rate theory, atomic physics, and applied mathematics.
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