Abstract
Statistical inference is that part of probabilistic reasoning in which the unknowns are hypotheses which have statistical consequences, that is, they specify a probability distribution of possible outcomes. The actual occurrence of a particular outcome will intuitively seem to support one or other of the hypotheses which might have generated it. Statistical inference attempts to discover the rules by which such support may be gauged.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
D. R. Cox and D. V. Hinkley. Theoretical Statistics. Chapman and Hall, London,1974.
S. Kotz and N. L. Johnson, editors. Encyclopedia of Statistical Sciences. Wiley, New York, 1982.
A. Stuart and J. K. Ord. Kendall’s Advanced Theory of Statistics, Vol. 2: Classical Inference and Relationship. Arnold, Sevenoaks, Kent, 1991.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1998 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Edwards, A.W.F. (1998). Statistical Inference. In: Smets, P. (eds) Quantified Representation of Uncertainty and Imprecision. Handbook of Defeasible Reasoning and Uncertainty Management Systems, vol 1. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-1735-9_11
Download citation
DOI: https://doi.org/10.1007/978-94-017-1735-9_11
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-5038-0
Online ISBN: 978-94-017-1735-9
eBook Packages: Springer Book Archive