Elementary Partial Differential Equations

Science & Math

Paul W. Berg

James. L. McGregor

Mathematics

Holden-Day

Intended for students and researchers, this text employs basic techniques of univariate and multivariate statistics for the analysis of time series and signals. It provides a broad collection of theorems, placing the techniques on firm theoretical ground. The techniques, which are illustrated by data analyses, are discussed in both a heuristic and a formal manner, making the book useful for both the applied and the theoretical worker. An extensive set of original exercises is included. Time Series: Data Analysis and Theory takes the Fourier transform of a stretch of time series data as the basic quantity to work with and shows the power of that approach. It considers second- and higher-order parameters and estimates them equally, thereby handling non-Gaussian series and nonlinear systems directly. The included proofs, which are generally short, are based on cumulants.

Time Series: Data Analysis and Theory

Computers & Technology

Brillinger, David R.

Software

Humorous account of a biologist's study of the physiology and psychology of the common fly

To Know a Fly

Humor & Entertainment

Vincent Gaston Dethier

Humor

Student's Guide to Operations Research

Jensen, Paul A.

Business & Money

Hardback, ex-library, with usual stamps and markings, in good all round condition. No dust jacket

Complex Variables

Levinson, Norman

Based on lectures for an undergraduate UCLA course in quantum mechanics, this volume focuses on the formulas of quantum mechanics rather than on applications. Topics include the dual nature of matter and radiation, state functions, linear momentum, the motion of a free particle, Schrödinger's equation, approximation methods, angular momentum, and many other subjects. 1968 edition.

Elementary Quantum Mechanics

Saxon, David S.

Physics

We now have an updated printing! Find more information at: http://vig.prenhall.com/catalog/academic/product/0,1144,0132306379,00.html. In response to feedback from faculty and students, some sections within the book have been rewritten. Also, a number of corrections have been made, further improving the accuracy of this outstanding textbook. 
This classic, time-honored introduction to the theory and practice of statistics modeling and inference reflects the changing focus of contemporary Statistics. Coverage begins with the more general nonparametric point of view and then looks at parametric models as submodels of the nonparametric ones which can be described smoothly by Euclidean parameters. Although some computational issues are discussed, this is very much a book on theory. It relates theory to conceptual and technical issues encountered in practice, viewing theory as suggestive for practice, not prescriptive. It shows readers how assumptions which lead to neat theory may be unrealistic in practice. Statistical Models, Goals, and Performance Criteria. Methods of Estimation. Measures of Performance, Notions of Optimality, and Construction of Optimal Procedures in Simple Situations. Testing Statistical Hypotheses: Basic Theory. Asymptotic Approximations. Multiparameter Estimation, Testing and Confidence Regions. A Review of Basic Probability Theory. More Advanced Topics in Analysis and Probability. Matrix Algebra. For anyone interested in mathematical statistics working in statistics, bio-statistics, economics, computer science, and mathematics.

Mathematical Statistics

Bickel, Peter J.

Book by Kenneth J. Arrow, Frank H. Hahn

General Competitive Analysis

Kenneth J. Arrow

Frank H. Hahn

Economics

Lectures On Applications Oriented Mathematics

Friedman, Bernard

Nmr: An Introduction to Proton Nuclear Magnetic Resonance Spectroscopy

Ault, Addison

Chemistry

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