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A Student s Guide to Data and Error Analysis 1st Edition by Herman J C Berendsen ISBN 0521119405 9780521119405

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A Student s Guide to Data and Error Analysis 1st Edition Herman J. C. Berendsen Digital Instant Download

Author(s): Herman J. C. Berendsen
ISBN(s): 9780521119405, 0521119405
Edition: 1
File Details: PDF, 1.70 MB
Year: 2011
Language: english
SKU: EB-2523858 Category: Tag:

A Student s Guide to Data and Error Analysis 1st Edition by Herman J C Berendsen – Ebook PDF Instant Download/Delivery: 0521119405, 9780521119405
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ISBN 10: 0521119405 
ISBN 13: 9780521119405
Author: Herman J C Berendsen

All students taking laboratory courses within the physical sciences and engineering will benefit from this book, whilst researchers will find it an invaluable reference. This concise, practical guide brings the reader up-to-speed on the proper handling and presentation of scientific data and its inaccuracies. It covers all the vital topics with practical guidelines, computer programs (in Python), and recipes for handling experimental errors and reporting experimental data. In addition to the essentials, it also provides further background material for advanced readers who want to understand how the methods work. Plenty of examples, exercises and solutions are provided to aid and test understanding, whilst useful data, tables and formulas are compiled in a handy section for easy reference.

A Student s Guide to Data and Error Analysis 1st Table of contents:

Part I Data and error analysis
1 Introduction
2 The presentation of physical quantities with their inaccuracies
2.1 How to report a series of measurements
2.2 How to represent numbers
2.3 How to express inaccuracies
2.4 Reporting units
2.5 Graphical presentation of experimental data
3 Errors: classification and propagation
3.1 Classification of errors
3.2 Error propagation
4 Probability distributions
4.1 Introduction
4.2 Properties of probability distributions
4.3 The binomial distribution
4.4 The Poisson distribution
4.5 The normal distribution
4.6 The central limit theorem
4.7 Other distributions
5 Processing of experimental data
5.1 The distribution function of a data series
5.2 The average and the mean squared deviation of a data series
5.3 Estimates for mean and variance
5.4 Accuracy of mean and Student’s t-distribution
5.5 Accuracy of variance
5.6 Handling data with unequal weights
5.7 Robust estimates
6 Graphical handling of data with errors
6.1 Introduction
6.2 Linearization of functions
6.3 Graphical estimates of the accuracy of parameters
6.4 Using calibration
7 Fitting functions to data
7.1 Introduction
7.2 Linear regression
7.3 General least-squares fit
7.4 The chi-squared test
7.5 Accuracy of the parameters
7.6 F-test on significance of the fit
8 Back to Bayes: knowledge as a probability distribution
8.1 Direct and inverse probabilities
8.2 Enter Bayes
8.3 Choosing the prior
8.4 Three examples of Bayesian inference
8.5 Conclusion
References
Answers to exercises
Part II Appendices
A1 Combining uncertainties
A2 Systematic deviations due to random errors
A3 Characteristic function
A4 From binomial to normal distributions
A4.1 The binomial distribution
A4.2 The multinomial distribution
A4.3 The Poisson distribution
A4.4 The normal distribution
A5 Central limit theorem
A6 Estimation of the variance
A7 Standard deviation of the mean
A8 Weight factors when variances are not equal
A9 Least-squares fitting
A9.1 How do you find the best parameters a and b in y ≈ ax + b?
A9.2 General linear regression
A9.3 SSQ as a function of the parameters
A9.4 Covariances of the parameters
Part III Python codes
Part IV Scientific data
Chi-squared distribution
F-distribution
Least-squares fitting
Normal distribution
Physical constants
Probability distributions
Student’s t-distribution

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Tags: Herman J C Berendsen, Error Analysis, Data