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Elementary Signal Detection Theory - Thomas D. Wickens

Elementary Signal Detection Theory

Hardcover

Published: 1st October 2001
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Signal detection theory, as developed in electrical engineering and based on statistical decision theory, was first applied to human sensory discrimination about 40 years ago. The theory's intent was to explain how humans discriminate and how we might use reliable measures to quantify this ability. An interesting finding of this work is that decisions are involved even in the simplest of discrimination tasks--say, determining whether or not a sound has been heard (a yes-no decision). Detection theory has been applied to a host of varied problems (for example, measuring the accuracy of diagnostic systems, survey research, reliability of lie detection tests) and extends far beyond the detection of signals. This book is a primer on signal detection theory, useful for both undergraduates and graduate students.

"This book contains the theoretical explications of the ways observers detect weak, uncertain, or ambiguous signals. It explains the math underlying the theory, and outlines its uses in measuring an observer's sensitivity. The book is intended to serve as an introductory text for undergraduate or graduate courses in sensation and perception, psychophysics, cognition, and quantitative methods; it may also be used as a reference for researchers. Wickens teaches at the University of California, Los Angeles."--SciTech Book News "This book contains the theoretical explications of the ways observers detect weak, uncertain, or ambiguous signals. It explains the math underlying the theory, and outlines its uses in measuring an observer's sensitivity. The book is intended to serve as an introductory text for undergraduate or graduate courses in sensation and perception, psychophysics, cognition, and quantitative methods; it may also be used as a reference for researchers. Wickens teaches at the University of California, Los Angeles."--SciTech Book News "This book contains the theoretical explications of the ways observers detect weak, uncertain, or ambiguous signals. It explains the math underlying the theory, and outlines its uses in measuring an observer's sensitivity. The book is intended to serve as an introductory text for undergraduate or graduate courses in sensation and perception, psychophysics, cognition, and quantitative methods; it may also be used as a reference for researchers. Wickens teaches at the University of California, Los Angeles."--SciTech Book News "This book contains the theoretical explications of the ways observers detect weak, uncertain, or ambiguous signals. It explains the math underlying the theory, and outlines its uses in measuring an observer's sensitivity. The book is intended to serve as an introductory text for undergraduate or graduate courses in sensation and perception, psychophysics, cognition, and quantitative methods; it may also be used as a reference for researchers. Wickens teaches at the University of California, Los Angeles."--SciTech Book News "This book contains the theoretical explications of the ways observers detect weak, uncertain, or ambiguous signals. It explains the math underlying the theory, and outlines its uses in measuring an observer's sensitivity. The book is intended to serve as an introductory text for undergraduate or graduate courses in sensation and perception, psychophysics, cognition, and quantitative methods; it may also be used as a reference for researchers. Wickens teaches at the University of California, Los Angeles."--SciTech Book News

The signal-detection modelp. 3
Some examplesp. 3
Hits and false alarmsp. 6
The statistical decision representationp. 9
Reference notesp. 15
Exercisesp. 16
The equal-variance Gaussian modelp. 17
The Gaussian detection modelp. 17
The equal-variance modelp. 20
Estimating d' and [lambda]p. 22
Measuring biasp. 26
Ideal observers and optimal performancep. 32
Reference notesp. 36
Exercisesp. 37
Operating characteristics and the Gaussian modelp. 39
The operating characteristicp. 39
Isocriterion and isobias contoursp. 42
The equal-variance Gaussian operating characteristicp. 45
The unequal-variance Gaussian modelp. 48
Fitting an empirical operating characteristicp. 52
Computer programsp. 56
Reference notesp. 58
Exercisesp. 58
Measures of detection performancep. 60
The distance between distributionsp. 61
Distances to the isosensitivity linep. 64
The area under the operating characteristicp. 66
Recommendationsp. 72
Measures of biasp. 74
Aggregation of detection statisticsp. 78
Reference notesp. 81
Exercisesp. 81
Confidence ratingsp. 83
The rating experimentp. 83
The detection model for rating experimentsp. 85
Fitting the rating modelp. 88
Exercisesp. 91
Forced-choice proceduresp. 93
The forced-choice experimentp. 93
The two-alternative forced-choice modelp. 96
Position biasp. 98
Forced-choice and yes/no detection tasksp. 104
The K-alternative forced-choice procedurep. 106
Exercisesp. 111
Discrimination and identificationp. 113
The two-alternative discrimination taskp. 114
The relationship between detection and discriminationp. 118
Identification of several stimulip. 124
Reference notesp. 129
Exercisesp. 129
Finite-state modelsp. 131
The high-threshold modelp. 131
The high-threshold operating characteristicp. 137
Other finite-state representationsp. 140
Rating-scale datap. 143
Reference notesp. 148
Exercisesp. 148
Likelihoods and likelihood ratiosp. 150
Likelihood-ratio testsp. 151
The Bayesian observerp. 157
Likelihoods and signal-detection theoryp. 160
Non-Gaussian distributionsp. 165
Reference notesp. 168
Exercisesp. 169
Multidimensional stimulip. 172
Bivariate signal detectionp. 172
Likelihood ratiosp. 176
Compound signalsp. 179
Signals with correlated componentsp. 184
Uncertainty effectsp. 188
Reference notesp. 192
Exercisesp. 193
Statistical treatmentp. 195
Variability in signal-detection studiesp. 195
Fundamental sampling distributionsp. 198
Simple detection statisticsp. 201
Confidence intervals and hypothesis testsp. 206
Goodness-of-fit testsp. 212
Comparison of hierarchical modelsp. 217
Interobserver variabilityp. 221
Reference notesp. 223
Exercisesp. 224
Summary of probability theoryp. 226
Basic definitionsp. 226
Random variablesp. 229
Some specific distributionsp. 235
Referencesp. 253
Indexp. 257
Table of Contents provided by Syndetics. All Rights Reserved.

ISBN: 9780195092509
ISBN-10: 0195092503
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 276
Published: 1st October 2001
Publisher: Oxford University Press Inc
Country of Publication: US
Dimensions (cm): 23.5 x 15.88  x 1.91
Weight (kg): 0.46