Overview

This text reviews a broad range of evidence leading to the conclusion that the visual system is not organized to generate a veridical representation of the physical world, but rather a statistical reflection of the visual history of the species and the individual observer. Thus, what humans actually see is a reflexive manifestation of the past rather than a logical analysis of the present. The idea that the images we consciously entertain represent the historical significance of visual stimuli follows from the inability to decipher ambiguous retinal information analytically, and has far-reaching consequences not only for vision but brain function generally. The immediate benefit of this approach is that it provides a framework by which to understand a variety of fundamental visual illusions that are otherwise difficult, if not impossible, to explain.

Full Product Details

Author:   Dale Purves ,  R.Beau Lotto
Publisher:   Sinauer Associates Inc.,U.S.
Imprint:   Sinauer Associates Inc.,U.S.
Dimensions:   Width: 21.50cm , Height: 1.50cm , Length: 28.00cm
Weight:   0.595kg
ISBN:  

9780878937523

ISBN 10:   0878937528
Pages:   265
Publication Date:   01 November 2002
Audience:   College/higher education ,  General/trade ,  Undergraduate ,  General
Format:   Paperback
Publisher's Status:   Out of Print
Availability:   Awaiting stock  

Table of Contents

Foreword xiii Preface to the second edition xvii Preface to the first edition xxi 1 The logic of decision 1 1.1 Uncertainty and probability 1 1.2 Reasoning under uncertainty 12 1.3 Population proportions, probabilities and induction 19 1.4 Decision making under uncertainty 28 1.5 Further readings 42 2 The logic of Bayesian networks and influence diagrams 45 2.1 Reasoning with graphical models 45 2.2 Reasoning with Bayesian networks and influence diagrams 65 2.3 Further readings 82 3 Evaluation of scientific findings in forensic science 85 3.1 Introduction 85 3.2 The value of scientific findings 86 3.3 Principles of forensic evaluation and relevant propositions 90 3.4 Pre-assessment of the case 100 3.5 Evaluation using graphical models 103 4 Evaluation given source level propositions 113 4.1 General considerations 113 4.2 Standard statistical distributions 115 4.3 Two stains, no putative source 117 4.4 Multiple propositions 122 5 Evaluation given activity level propositions 129 5.1 Evaluation of transfer material given activity level propositions assuming a direct source relationship 130 5.2 Cross- or two-way transfer of trace material 150 5.3 Evaluation of transfer material given activity level propositions with uncertainty about the true source 154 6 Evaluation given crime level propositions 159 6.1 Material found on a crime scene: A general approach 159 6.2 Findings with more than one component: The example of marks 168 6.3 Scenarios with more than one trace: 'Two stain-one offender' cases 182 6.4 Material found on a person of interest 185 7 Evaluation of DNA profiling results 196 7.1 DNA likelihood ratio 196 7.2 Network approaches to the DNA likelihood ratio 198 7.3 Missing suspect 203 7.4 Analysis when the alternative proposition is that a brother of the suspect left the crime stain 206 7.5 Interpretation with more than two propositions 214 7.6 Evaluation with more than two propositions 217 7.7 Partially corresponding profiles 220 7.8 Mixtures 223 7.9 Kinship analyses 227 7.10 Database search 234 7.11 Probabilistic approaches to laboratory error 241 7.12 Further reading 246 8 Aspects of combining evidence 249 8.1 Introduction 249 8.2 A difficulty in combining evidence: The 'problem of conjunction' 250 8.3 Generic patterns of inference in combining evidence 252 8.4 Examples of the combination of distinct items of evidence 262 9 Networks for continuous models 281 9.1 Random variables and distribution functions 281 9.2 Samples and estimates 289 9.3 Continuous Bayesian networks 292 9.4 Mixed networks 306 10 Pre-assessment 314 10.1 Introduction 314 10.2 General elements of pre-assessment 315 10.3 Pre-assessment in a fibre case: A worked through example 316 10.4 Pre-assessment in a cross-transfer scenario 321 10.5 Pre-assessment for consignment inspection 328 10.6 Pre-assessment for gunshot residue particles 335 11 Bayesian decision networks 343 11.1 Decision making in forensic science 343 11.2 Examples of forensic decision analyses 344 11.3 Further readings 368 12 Object-oriented networks 370 12.1 Object orientation 370 12.2 General elements of object-oriented networks 371 12.3 Object-oriented networks for evaluating DNA profiling results 378 13 Qualitative, sensitivity and conflict analyses 388 13.1 Qualitative probability models 389 13.2 Sensitivity analyses 402 13.3 Conflict analysis 410 References 419 Author index 433 Subject index 438

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DALE PURVES Duke University Medical Centre. - R. BEAU LOTTO University College London.

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