Error and Uncertainty in Scientific Practice

Assessment of error and uncertainty is a vital component of both natural and social science. Empirical research involves dealing with all kinds of errors and uncertainties, yet there is significant variance in how such results are dealt with. Contributors to this volume present case studies of research practices across a wide spectrum of scientific fields, including experimental physics, econometrics, environmental science, climate science, engineering, measurement science and statistics. They compare methodologies and present the ingredients needed for an overarching framework applicable to all.

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Error and Uncertainty in Scientific Practice

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Frontmatter
pp i-iv

Contents
pp v-vi

Acknowledgements
pp vii-viii

List of Contributors
pp ix-xii

List of Figures and Tables
pp xiii-xiv

Introduction
pp 1-12

1 - The Lack of a Satisfactory Conceptualization of the Notion of Error in the Historiography of Science: Two Main Approaches and Shortcomings
pp 13-38

2 - Experimental Knowledge in the Face of Theoretical Error
pp 39-56

3 - Learning from Error: How Experiment Gets a Life (of its Own)
pp 57-78

4 - Modelling Measurement: Error and Uncertainty
pp 79-96

5 - Handling Uncertainty in Environmental Models at the Science–Policy–Society Interfaces
pp 97-136

6 - Variations on Reliability: Connecting Climate Predictions to Climate Policy
pp 137-156

7 - Order and Indeterminism: An Info-Gap Perspective
pp 157-176

8 - Learning from Data: The Role of Error in Statistical Modelling and Inference
pp 177-208

Notes
pp 209-242

Index
pp 243-249

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