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Data Analysis: Statistical and Computational Methods for Scientists and Engineers

✍ Scribed by Siegmund Brandt (auth.)


Publisher
Springer-Verlag New York
Year
1999
Tongue
English
Leaves
684
Edition
3
Category
Library

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✦ 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 pheΒ­ 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.

✦ Table of Contents


Front Matter....Pages i-xxxiv
Introduction....Pages 1-6
Probabilities....Pages 7-16
Random Variables. Distributions....Pages 17-48
Computer Generated Random Numbers. The Monte Carlo Method....Pages 49-86
Some Important Distributions and Theorems....Pages 87-132
Samples....Pages 133-186
The Method of Maximum Likelihood....Pages 187-211
Testing Statistical Hypotheses....Pages 212-247
The Method of Least Squares....Pages 248-331
Function Minimization....Pages 332-395
Analysis of Variance....Pages 396-412
Linear and Polynomial Regression....Pages 413-426
Time Series Analysis....Pages 427-440
Back Matter....Pages 441-652

✦ Subjects


Mathematical Methods in Physics;Numerical and Computational Physics;Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences;Statistics for Business/Economics/Mathematical Finance/Insurance


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