Data Reduction and Error Analysis for the Physical Sciences 3rd Edition by Philip Bevington, D. Keith Robinson – Ebook PDF Instant Download/Delivery: 0072472278, 978-0072472271
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ISBN 10: 0072472278
ISBN 13: 978-0072472271
Author: Philip Bevington, D. Keith Robinson
Data Reduction and Error Analysis for the Physical Sciences 3rd Edition: The purpose of this book is to provide an introduction to the concepts of statistical analysis of data for students at the undergraduate and graduate level, and to provide tools for data reduction and error analysis commonly required in the physical sciences. The presentation is developed from a practical point of view, including enough derivation to justify the results, but emphasizing methods of handling data more than theory. The text provides a variety of numerical and graphical techniques. Computer programs that support these techniques will be available on an accompanying website in both Fortran and C++.
Data Reduction and Error Analysis for the Physical Sciences 3rd Edition Table of contents:
Chapter 1 Uncertainties in Measurements
1.1 Measuring Errors
1.2 Uncertainties
1.3 Parent and Sample Distributions
1.4 Mean and Standard Deviation of Distributions
Chapter 2 Probability Distributions
2.1 Binomial Distribution
2.2 Poisson Distribution
2.3 Gaussian or Normal Error Distribution
2.4 Lorentzian Distribution
Chapter 3 Error Analysis
3.1 Instrumental and Statistical Uncertainties
3.2 Propagation of Errors
3.3 Specific Error Formulas
3.4 Application of Error Equations
Chapter 4 Estimates of Mean and Errors
4.1 Method of Least Squares
4.2 Statistical Fluctuations
4.3 Probability Tests
4.4 x2 Test of a Distribution
Chapter 5 Monte Carlo Techniques
5.1 Introduction
5.2 Random Numbers
Chapter 6 Least-Squares Fit to a Straight Line
6.1 Dependent and Independent Variables
6.2 Method of Least Squares
6.3 Minimizing x2
6.4 Error Estimation
6.5 Some Limitations of the Least-Squares Method
6.6 Alternate Fitting Methods
Chapter 7 Least-Squares Fit to a Polynomial
7.1 Determinant Solution
7.2 Matrix Solution
7.3 Independent Parameters
7.4 Nonlinear Functions
Chapter 8 Least-Squares Fit to an Arbitrary Function
8.1 Nonlinear Fitting
8.2 Searching Parameter Space
8.3 Grid-Search Method
8.4 Gradient-Search Method
8.5 Expansion Methods
8.6 The Marquardt Method
8.7 Comments
Chapter 9 Fitting Composite Curves
9.1 Lorentzian Peak on Quadratic Background
9.2 Area Determination
9.3 Composite Plots
Chapter 10 Direct Application of the Maximum-Likelihood Method
10.1 Introduction to Maximum Likelihood
10.2 Computer Example
Chapter 11 Testing the Fit
11.1 x2 Test for Goodness of Fit
11.2 Linear-Correlation Coefficient
11.3 Multivariable Correlations
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