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Introduction to Uncertainty in Measurement

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ISBN-10: 0521605792

ISBN-13: 9780521605793

Edition: 2006

Authors: Les Kirkup, Bob Frenkel

List price: $64.99
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Description:

Measurement shapes scientific theories, characterises improvements in manufacturing processes and promotes efficient commerce. In concert with measurement is uncertainty, and students in science and engineering need to identify and quantify uncertainties in the measurements they make. This book introduces measurement and uncertainty to second and third year students of science and engineering. Its approach relies on the internationally recognised and recommended guidelines for calculating and expressing uncertainty (known by the acronym GUM). The statistics underpinning the methods are considered and worked examples and exercises are spread throughout the text. Detailed case studies based…    
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Book details

List price: $64.99
Copyright year: 2006
Publisher: Cambridge University Press
Publication date: 6/1/2006
Binding: Paperback
Pages: 248
Size: 6.69" wide x 9.61" long x 0.51" tall
Weight: 1.320
Language: English

Preface
The importance of uncertainty in science and technology
Measurement matters
Review
Measurement fundamentals
The system of units of measurement
Scientific and engineering notations
Rounding and significant figures
Another way of expressing proportional uncertainty
Review
Terms used in measurement
Measurement and related terms
Review
Introduction to uncertainty in measurement
Measurement and error
Uncertainty is a parameter that characterises the dispersion of values
Standard deviation as a basic measure of uncertainty
The uncertainty in the estimate of uncertainty
Combining standard uncertainties
Review
Some statistical concepts
Sampling from a population
The least-squares model and least-squares fitting
Covariance and correlation
Review
Systematic errors
Systematic error revealed by specific information
Systematic error revealed by changed conditions
Review
Calculation of uncertainties
The measurand model and propagation of uncertainties from inputs to measurand
Correlated inputs
Review
Probability density, the Gaussian distribution and central limit theorem
Distribution of scores when tossing coins or dice
General properties of probability density
The uniform or rectangular distribution
The Gaussian distribution
Experimentally observed non-Gaussian distributions
The central limit theorem
Review
Sampling a Gaussian distribution
Sampling the distribution of the mean of a sample of size n, from a Gaussian population
Sampling the distribution of the variance of a sample of size n, from a Gaussian population
Sampling the distribution of the standard deviation of a sample of size n, from a Gaussian population
Review
The t-distribution and Welch-Satterthwaite formula
The coverage interval for a Gaussian distribution
The coverage interval using a t-distribution
The Welch-Satterthwaite formula
Review
Case studies in measurement uncertainty
Reporting measurement results
Determination of the coefficient of static friction for glass on glass
A crater-formation experiment
Determination of the density of steel
The rate of evaporation of water from an open container
Review
Solutions to exercises
95% Coverage factors, k, as a function of the number of degrees of freedom, v
Further discussion following from the Welch-Satterthwaite formula
References
Index