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Data Analysis: Statistical and Computational Methods for Scientists and Engineers

Autor Siegmund Brandt Traducere de Glen Gowan
en Limba Engleză Paperback – 5 oct 2012
1. 1 Typical Problems of Data Analysis Every branch of experimental science, after passing through an early stage of qualitative description, concerns itself with quantitative studies of the phe­ nomena of interest, i. e. , measurements. In addition to designing and carrying out the experiment, an importal1t task is the accurate evaluation and complete exploitation of the data obtained. Let us list a few typical problems. 1. A study is made of the weight of laboratory animals under the influence of various drugs. After the application of drug A to 25 animals, an average increase of 5 % is observed. Drug B, used on 10 animals, yields a 3 % increase. Is drug A more effective? The averages 5 % and 3 % give practically no answer to this question, since the lower value may have been caused by a single animal that lost weight for some unrelated reason. One must therefore study the distribution of individual weights and their spread around the average value. Moreover, one has to decide whether the number of test animals used will enable one to differentiate with a certain accuracy between the effects of the two drugs. 2. In experiments on crystal growth it is essential to maintain exactly the ratios of the different components. From a total of 500 crystals, a sample of 20 is selected and analyzed.
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Specificații

ISBN-13: 9781461271475
ISBN-10: 1461271479
Pagini: 692
Ilustrații: XXXIV, 652 p.
Dimensiuni: 155 x 235 x 36 mm
Greutate: 0.95 kg
Ediția:Softcover reprint of the original 3rd ed. 1999
Editura: Springer
Colecția Springer
Locul publicării:New York, NY, United States

Public țintă

Graduate

Cuprins

1. Introduction; 2. Probabilities; 3. Random Variables; 4. Computer- Generated Random Numbers: The Monte Carlo Method; 5. Some Important Distributions and Theorems; 6. Samples; 7. The Method of Maximum Likelihood; 8. Testing Statistical Hypotheses; 9. The Method of Least Squares; 10. Function Minimization; 11. Analysis of variance; 12. Linear and Polynomial Regression; 13. Time-Series Analysis; Appendix A: Matrix Calculation; Appendix B: Combinatorics; Appendix C: Formulas and Programs for Statistical Functions; Appendix D: The Gamma Function and Related Functions. methods and Programs for Their Computation; Appendix E: Utility Programs; Appendix F: The Graphics Programming Package GRPACK; Appendix G: Software Installation and technical Hints; Appendix H: Collection of Formulas; Appendix I: Statistical Tables; Literature; List of Computer Programs; Register.

Recenzii

From the reviews:
"The book is concise, but gives a sufficiently rigorous mathematical treatment of practical statistical methods for data analysis¿It can be of great use to all who are involved with data analysis." Physicalia
"... Serves as a nice reference guide for any scientist interested in the fundamentals of data analysis on the computer." The American Statistician

Notă biografică

Siegmund Brandt is Emeritus Professor of Physics at the University of Siegen. With his group he worked on experiments in elementary-particle physics at the research centers DESY in Hamburg and CERN in Geneva in which the analysis of the experimental data plays an important role. He is author or coauthor of textbooks which have appeared in ten languages.


Textul de pe ultima copertă

The fourth edition of this successful textbook presents a comprehensive introduction to statistical and numerical methods for the evaluation of empirical and experimental data. Equal weight is given to statistical theory and practical problems. The concise mathematical treatment of the subject matter is illustrated by many examples, and for the present edition a library of Java programs has been developed. It comprises methods of numerical data analysis and graphical representation as well as many example programs and solutions to programming problems. The programs (source code, Java classes, and documentation) and extensive appendices to the main text are available for free download from the book’s page at www.springer.com.
Contents
  • Probabilities. Random variables.
  • Random numbers and the Monte Carlo Method.
  • Statistical distributions (binomial, Gauss, Poisson). Samples. Statistical tests.
  • Maximum Likelihood. Least Squares. Regression.Minimization.
  • Analysis of Variance. Time series analysis.
Audience
The book is conceived both as an introduction and as a work of reference. In particular it addresses itself to students, scientists and practitioners in science and engineering as a help in the analysis of their data in laboratory courses, working for bachelor or master degrees, in thesis work, and in research and professional work.
“The book is concise, but gives a sufficiently rigorous mathematical treatment of practical statistical methods for data analysis; it can be of great use to all who are involved with data analysis.” Physicalia
“This lively and erudite treatise covers the theory of the main statistical tools and their practical applications…a first rate university textbook, and good background material for the practicing physicist.” Physics Bulletin
The Author
Siegmund Brandt is Emeritus Professor of Physics at the University of Siegen. With his group he worked on experiments in elementary-particle physics at the research centers DESY in Hamburg and CERN in Geneva in which the analysis of the experimental data plays an important role. He is author or coauthor of textbooks which have appeared in ten languages.

Caracteristici

Provides rigorous mathematical treatment of practical statistical methods for data analysis Serves as a graduate textbook and reference guide for those interested in the fundamentals of data analysis Useful for all fields of science and engineering requiring an understanding of statistical methods applied to experimental data Includes example programs and solutions to programming problems which are written in the modern computer language Java Modernizes the content in the previous edition and shortens the length of the text Includes supplementary material: sn.pub/extras