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Data Analysis: Statistical and Computational Methods for Scientists and Engineers (Ohlin Lectures; 7) - Hardcover
Synopsis
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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Language Notes
Text: English (translation)
Original Language: German
Review
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
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date1998
- ISBN 10 0387984984
- ISBN 13 9780387984988
- BindingHardcover
- LanguageEnglish
- Edition number3
- Number of pages686
- Rating
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Data Analysis: Statistical and Computational Methods for Scientists and Engineers (Ohlin Lectures; 7)
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Data Analysis: Statistical and Computational Methods for Scientists and Engineers
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Data Analysis: Statistical and Computational Methods for Scientists and Engineers
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Data Analysis : Statistical and Computational Methods for Scientists and Engineers
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Data Analysis: Statistical and Computational Methods for Scientists and Engineers (Ohlin Lectures; 7)
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Data Analysis : Statistical and Computational Methods for Scientists and Engineers
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Data Analysis: Statistical and Computational Methods for Scientists and Engineers (Third Edition, Includes CD-ROM)
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Condition: Very Good. Hardcover, [xxxiv], 652 pages, plus CD-ROM. Very Good condition. Third edition. Size 9.5"x6.25". "Bridging the gap between statistical theory and physical experiment, this is a thorough introduction to the statistical methods used in the experimental physical sciences and to the numerical methods used to implement them. The treatment emphasises concise but rigorous mathematics but always retains its focus on applications. Readers are assumed to have a sound basic knowledge of differential and integral calculus and some knowledge of vectors and matrices. After an introduction to probability, random variables, computer generation of random numbers and important distributions, the book turns to statistical samples, the maximum likelihood method, and the testing of statistical hypotheses. The discussion concludes with several important statistical methods: least squares, analysis of variance, polynomial regression, and analysis of time series. Appendices provide the necessary methods of matrix algebra, combinatorics, and many sets of useful algorithms and formulae." Book has moderate exterior shelfwear, else Near Fine condition, clean and unmarked. CD-ROM is still sealed. Seller Inventory # 009723
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Data Analysis 3/Ed.
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Data Analysis 3/Ed.
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Data Analysis: Statistical and Computational Methods for Scientists and Engineers (Ohlin Lectures; 7)
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