Measurement Uncertainties in Science and Technology

At the turn of the 19th century, Carl Friedrich Gauss founded error calculus by predicting the then unknown position of the minor planet Ceres. Ever since, error calculus has occupied a place at the heart of science. In this book, Grabe illustrates the breakdown of traditional error calculus in the face of modern measurement techniques. Revising Gauss' error calculus ab initio, he treats random and unknown systematic errors on an equal footing from the outset. Furthermore, Grabe also proposes what may be called well defined measuring conditions, a prerequisite for defining confidence intervals that are consistent with basic statistical concepts. The resulting measurement uncertainties are as robust and reliable as required by modern-day science, engineering and technology.

A new error calculus for modern-day science

Autorentext
At the turn of the 19 th century, Carl Friedrich Gauss founded error calculus by predicting the then unknown position of the minor planet Ceres. Ever since, error calculus has occupied a place at the heart of science. In this book, Grabe illustrates the breakdown of traditional error calculus in the face of modern measurement techniques. Revising Gauss' error calculus ab initio, he treats random and unknown systematic errors on an equal footing from the outset. Furthermore, Grabe also proposes what may be called well defined measuring conditions, a prerequisite for defining confidence intervals that are consistent with basic statistical concepts. The resulting measurement uncertainties are as robust and reliable as required by modern-day science, engineering and technology.

Inhalt
Characterization, Combination and Propagation of Errors.- Basic Ideas of Measurement.- Formalization of Measuring Processes.- Densities of Normal Parent Distributions.- Estimators and Their Expectations.- Combination of Measurement Errors.- Propagation of Measurement Errors.- Least Squares Adjustment.- Least Squares Formalism.- Consequences of Systematic Errors.- Uncertainties of Least Squares Estimators.- Special Linear and Linearized Systems.- Systems with Two Parameters.- Systems with Three Parameters.- Special Metrology Systems.