Dealing In Uncertainty
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Dealing with Uncertainties in Policing Serious Crime
Grappling with uncertainties is at the heart of investigating serious crime. At a time when such crime is becoming more complex and resources are increasingly stretched, this book draws together research and practice perspectives to review fruitful approaches to uncertainties and to chart the way forward. Scene setting chapters describe the consequences of globalisation and the spread of sophisticated information technologies (Sue Wilkinson), as well as advances in understanding and managing uncertainty (Michael Smithson). Ways of enhancing responses from statistics (Robyn Attewell), risk analysis (Richard Jarrett and Mark Westcott) and the psychology of decision making (Mark Kebbell, Damon Muller and Kirsty Martin) follow. These are complemented by insights from law (the Hon. Tim Carmody SC), politics (the Hon. Carmen Lawrence) and business (Neil Fargher), which all have significant intersections with policing. Synthesis is provided by the four final chapters which present the outlooks of the investigating officer and investigation manager (Peter Martin), the provider of policing higher education (Tracey Green and Greg Linsdell), the capacity-building consultant (Steve Longford), and the leader of a law enforcement agency (Alastair Milroy).
Dealing with Uncertainties
Author: Manfred Drosg
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-03-06
Dealing with Uncertainties proposes and explains a new approach for the analysis of uncertainties. Firstly, it is shown that uncertainties are the consequence of modern science rather than of measurements. Secondly, it stresses the importance of the deductive approach to uncertainties. This perspective has the potential of dealing with the uncertainty of a single data point and of data of a set having differing weights. Both cases cannot be dealt with the inductive approach, which is usually taken. This innovative monograph also fully covers both uncorrelated and correlated uncertainties. The weakness of using statistical weights in regression analysis is discussed. Abundant examples are given for correlation in and between data sets and for the feedback of uncertainties on experiment design.
Managing Uncertainty
A guide to using the computer to come to terms with the risk, insecurity, and ambivalence that are encountered in businesses in a wide range of fields. Matching management techniques with computational equivalents, shows how to use both conflicting and confirming evidence from independent sources to induce, infer, and predict, in ways that will improve decision making. Includes several programs. Annotation copyright by Book News, Inc., Portland, OR