Practical Guide to Data Analysis for Physical Science Students

ISBN-10: 0521424631

ISBN-13: 9780521424639

Edition: 1991

Authors: Louis Lyons
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Description: It is usually straightforward to calculate the result of a practical experiment in the laboratory. Estimating the accuracy of that result is often regarded by students as an obscure and tedious routine, involving much arithmetic. An estimate of the error is, however, an integral part of the presentation of the results of experiments. This textbook is intended for undergraduates who are carrying out laboratory experiments in the physical sciences for the first time. It is a practical guide on how to analyse data and estimate errors. The necessary formulas for performing calculations are given, and the ideas behind them are explained, although this is not a formal text on statistics. Specific examples are worked through step by step in the text. Emphasis is placed on the need to think about whether a calculated error is sensible. At first students should take this book with them to the laboratory, and the format is intended to make this convenient. The book will provide the necessary understanding of what is involved, should inspire confidence in the method of estimating errors, and enable numerical calculations without too much effort. The authors aim is to make practical classes more enjoyable. Students who use this book will be able to complete their calculations quickly and confidently, leaving time to appreciate the basic physical ideas involved in the experiments.

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Book details

Copyright year: 1991
Publisher: Cambridge University Press
Publication date: 11/29/1991
Binding: Paperback
Pages: 112
Size: 5.50" wide x 8.50" long x 0.25" tall
Weight: 0.330
Language: English

Lyons, Department of Nuclear Physics, University of Oxford.

Preface
Glossary
Experimental errors
Why estimate errors?
Random and systematic errors
Distributions
Mean and variance
Gaussian distribution
The meaning of s
Combining errors
Systematic errors
An example including random and systematic errors
Combining results of different experiments
Worked examples
Does it feel right?
Least squares fitting
What are we trying to do
Weighted sum of squares
Determining the parameters
The error on the gradient and the intercept
Other examples
Observed numbers
Parameter testing
Distribution testing
Worked example of a straight line fit
Summary of straight line fitting
Problems
Appendices
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