Bayesian Networks As A Decision Support Tool For Rural Water Supply And Sanitation Sector

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Bayesian Networks as a Decision Support Tool for Rural Water Supply and Sanitation Sector

Author : David Requejo Castro
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (112 download)

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Book Synopsis Bayesian Networks as a Decision Support Tool for Rural Water Supply and Sanitation Sector by : David Requejo Castro

Download or read book Bayesian Networks as a Decision Support Tool for Rural Water Supply and Sanitation Sector written by David Requejo Castro and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite the efforts made towards the Millennium Development Goals targets during the last decade, still millions of people across the world lack of improved access to water supply or basic sanitation. The increasing complexity of the context in which these services are delivered is not properly captured by the conventional approaches that pursue to assess water, sanitation and hygiene (WaSH) interventions. Instead, a holistic framework is required to integrate the wide range of aspects which are influencing sustainable and equitable provision of safe water and sanitation, especially to those in vulnerable situations. In this context, the WaSH Poverty Index (WaSH-PI) was adopted, as a multi-dimensional policy tool that tackles the links between access to basic services and the socio-economic drivers of poverty. Nevertheless, this approach does not fully describe the increasing interdependency of the reality. For this reason, appropriate Decision Support Systems (DSS) are required to i) inform about the results achieved in past and current interventions, and to ii) determine expected impacts of future initiatives, particularly taking into account envisaged investments to reach the targets set by the Sustainable Development Goals (SDGs). This would provide decision-makers with adequate information to define strategies and actions that are efficient, effective, and sustainable. This master thesis explores the use of object-oriented Bayesian networks (ooBn) as a powerful instrument to support project planning and monitoring, as well as targeting and prioritization. Based on WaSH-PI theoretical framework, a simple ooBn model has been developed and applied to reflect the main issues that determine access to safe water, sanitation and hygiene. A case study is presented in Kenya, where the Government launched in 2008 a national program aimed to increase the access to improved water, sanitation and hygiene in 22 of the 47 existing districts. Main impacts resulted from this initiative are assessed and compared against the initial situation. This research concludes that the proposed approach is able to accommodate the conditions at different scales, at the same time that reflects the complexities of WaSH-related issues. Additionally, this DSS represents an effective management tool to support decisionmakers to formulate informed choices between alternative actions.

Bayesian Networks and Decision Graphs

Author : Thomas Dyhre Nielsen
Publisher : Springer Science & Business Media
ISBN 13 : 0387682821
Total Pages : 457 pages
Book Rating : 4.3/5 (876 download)

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Book Synopsis Bayesian Networks and Decision Graphs by : Thomas Dyhre Nielsen

Download or read book Bayesian Networks and Decision Graphs written by Thomas Dyhre Nielsen and published by Springer Science & Business Media. This book was released on 2009-03-17 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a brand new edition of an essential work on Bayesian networks and decision graphs. It is an introduction to probabilistic graphical models including Bayesian networks and influence diagrams. The reader is guided through the two types of frameworks with examples and exercises, which also give instruction on how to build these models. Structured in two parts, the first section focuses on probabilistic graphical models, while the second part deals with decision graphs, and in addition to the frameworks described in the previous edition, it also introduces Markov decision process and partially ordered decision problems.

Risk Assessment and Decision Analysis with Bayesian Networks

Author : Norman Fenton
Publisher : CRC Press
ISBN 13 : 1351978969
Total Pages : 672 pages
Book Rating : 4.3/5 (519 download)

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Book Synopsis Risk Assessment and Decision Analysis with Bayesian Networks by : Norman Fenton

Download or read book Risk Assessment and Decision Analysis with Bayesian Networks written by Norman Fenton and published by CRC Press. This book was released on 2018-09-03 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the first edition of this book published, Bayesian networks have become even more important for applications in a vast array of fields. This second edition includes new material on influence diagrams, learning from data, value of information, cybersecurity, debunking bad statistics, and much more. Focusing on practical real-world problem-solving and model building, as opposed to algorithms and theory, it explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide more powerful insights and better decision making than is possible from purely data-driven solutions. Features Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliability, law, forensics, cybersecurity and more Introduces all necessary mathematics, probability, and statistics as needed Establishes the basics of probability, risk, and building and using Bayesian network models, before going into the detailed applications A dedicated website contains exercises and worked solutions for all chapters along with numerous other resources. The AgenaRisk software contains a model library with executable versions of all of the models in the book. Lecture slides are freely available to accredited academic teachers adopting the book on their course.

How to Support Community Management of Water Supplies

Author : Catarina Fonseca
Publisher : Kit Pub
ISBN 13 :
Total Pages : 156 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis How to Support Community Management of Water Supplies by : Catarina Fonseca

Download or read book How to Support Community Management of Water Supplies written by Catarina Fonseca and published by Kit Pub. This book was released on 2002 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is for those who are in charge of facilitating community management of water supplies. It provides guidelines and food for thought for managers and decision-makers who want to improve the performance of their organization and make sure that water supply services in place keep working. It answers such questions as: what kind of support do communities require? How can this support be provided? What are the organizational conditions we need to put in place? What tools can we use? Who should be involved? What does it demand from support organizations and the communities? In other words: what does it take to support community management of water supplies.

Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis

Author : Uffe B. Kjærulff
Publisher : Springer Science & Business Media
ISBN 13 : 1461451043
Total Pages : 388 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis by : Uffe B. Kjærulff

Download or read book Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis written by Uffe B. Kjærulff and published by Springer Science & Business Media. This book was released on 2012-11-30 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new sections, in addition to fully-updated examples, tables, figures, and a revised appendix. Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his or her level of understanding. The techniques and methods presented for knowledge elicitation, model construction and verification, modeling techniques and tricks, learning models from data, and analyses of models have all been developed and refined on the basis of numerous courses that the authors have held for practitioners worldwide.

Bayesian Networks

Author : Olivier Pourret
Publisher : John Wiley & Sons
ISBN 13 : 0470060301
Total Pages : 446 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Bayesian Networks by : Olivier Pourret

Download or read book Bayesian Networks written by Olivier Pourret and published by John Wiley & Sons. This book was released on 2008-05-05 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields.

Bayesian Networks

Author : Wichian Premchaiswadi
Publisher : BoD – Books on Demand
ISBN 13 : 9535105566
Total Pages : 128 pages
Book Rating : 4.5/5 (351 download)

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Book Synopsis Bayesian Networks by : Wichian Premchaiswadi

Download or read book Bayesian Networks written by Wichian Premchaiswadi and published by BoD – Books on Demand. This book was released on 2012-04-20 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Belief Networks are a powerful tool for combining different knowledge sources with various degrees of uncertainty in a mathematically sound and computationally efficient way. A Bayesian network is a graphical model that encodes probabilistic relationships among variables of interest. When used in conjunction with statistical techniques, the graphical model has several advantages for data modeling. First, because the model encodes dependencies among all variables, it readily handles situations where some data entries are missing. Second, a Bayesian network can be used to learn causal relationships, and hence can be used to gain an understanding about a problem domain and to predict the consequences of intervention. Third, because the model has both causal and probabilistic semantics, it is an ideal representation for combining prior knowledge (which often comes in a causal form) and data. Fourth, Bayesian statistical methods in conjunction with Bayesian networks offer an efficient and principled approach to avoid the over fitting of data.

Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science

Author : Franco Taroni
Publisher : John Wiley & Sons
ISBN 13 : 1118914740
Total Pages : 472 pages
Book Rating : 4.1/5 (189 download)

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Book Synopsis Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science by : Franco Taroni

Download or read book Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science written by Franco Taroni and published by John Wiley & Sons. This book was released on 2014-07-21 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Networks “This book should have a place on the bookshelf of every forensic scientist who cares about the science of evidence interpretation.” Dr. Ian Evett, Principal Forensic Services Ltd, London, UK Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science Second Edition Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates diffculties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. Includes self-contained introductions to probability and decision theory. Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. Features implementation of the methodology with reference to commercial and academically available software. Presents standard networks and their extensions that can be easily implemented and that can assist in the reader’s own analysis of real cases. Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

Bayesian Networks as a Decision Support Tool in Marine Applications

Author : Andreas Friis-Hansen
Publisher :
ISBN 13 : 9788789502489
Total Pages : 184 pages
Book Rating : 4.5/5 (24 download)

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Book Synopsis Bayesian Networks as a Decision Support Tool in Marine Applications by : Andreas Friis-Hansen

Download or read book Bayesian Networks as a Decision Support Tool in Marine Applications written by Andreas Friis-Hansen and published by . This book was released on 2000 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Probabilistic Networks and Expert Systems

Author : Robert G. Cowell
Publisher : Springer Science & Business Media
ISBN 13 : 0387226303
Total Pages : 324 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Probabilistic Networks and Expert Systems by : Robert G. Cowell

Download or read book Probabilistic Networks and Expert Systems written by Robert G. Cowell and published by Springer Science & Business Media. This book was released on 2006-05-29 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic expert systems are graphical networks which support the modeling of uncertainty and decisions in large complex domains, while retaining ease of calculation. Building on original research by the authors, this book gives a thorough and rigorous mathematical treatment of the underlying ideas, structures, and algorithms. The book will be of interest to researchers in both artificial intelligence and statistics, who desire an introduction to this fascinating and rapidly developing field. The book, winner of the DeGroot Prize 2002, the only book prize in the field of statistics, is new in paperback.

Introduction to Bayesian Networks

Author : Finn V. Jensen
Publisher : Springer
ISBN 13 : 9780387915029
Total Pages : 178 pages
Book Rating : 4.9/5 (15 download)

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Book Synopsis Introduction to Bayesian Networks by : Finn V. Jensen

Download or read book Introduction to Bayesian Networks written by Finn V. Jensen and published by Springer. This book was released on 1997-08-15 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Disk contains: Tool for building Bayesian networks -- Library of examples -- Library of proposed solutions to some exercises.

The Use of Bayesian Networks to Facilitate Implementation of Water Demand Management Strategies

Author :
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (656 download)

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Book Synopsis The Use of Bayesian Networks to Facilitate Implementation of Water Demand Management Strategies by :

Download or read book The Use of Bayesian Networks to Facilitate Implementation of Water Demand Management Strategies written by and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian networks have received increasing recognition in recent years as a potentially effective tool in supporting water management decisions. Despite a number of reports of their use, no formal evaluation of the effectiveness of Bayesian networks in facilitating water resources management exists. This study improves understanding of the strengths and weaknesses of Bayesian networks through their application in a water-stressed region in Europe where domestic sector water demand management is considered as a mitigation measure. The fieldwork results provide a comprehensive technical and end-user evaluation of the use of Bayesian networks in water demand management implementation which, to our knowledge, is the first of its kind to be reported in the academic literature. For the technical evaluation, expert knowledge was first used to generate the structure of Bayesian network models which were then populated with data collected in the case study region. The model development supported the examination of several research questions regarding the technical suitability of Bayesian network modelling to facilitate implementation of water demand management strategies. For the end-user evaluation a survey was used to record the experiences of practitioners who applied Bayesian network models to a number of water demand management problems during a one-day workshop. Evaluation indicators included the effectiveness of Bayesian networks in facilitating strategic planning, technical support, transparency of data, learning among and between stakeholders, organisational receptivity, reliance on decision, and a comparison of experiences of decision conflict, effort and decision confidence. Results from the end-user evaluation provide evidence that Bayesian networks are particularly effective in terms of technical suitability and transparency, and policy-makers perceived effectiveness scores were significantly higher than individuals from other professions. Conclusions from the t.

Solutions to Water Crises (Related to Actual Interventions)

Author : Jenia Mukherjee
Publisher : Frontiers Media SA
ISBN 13 : 283254214X
Total Pages : 148 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Solutions to Water Crises (Related to Actual Interventions) by : Jenia Mukherjee

Download or read book Solutions to Water Crises (Related to Actual Interventions) written by Jenia Mukherjee and published by Frontiers Media SA. This book was released on 2024-01-26 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Research Topic is a part of the Delft 2021: 1st Sociohydrology Conference series. To view the other sessions please follow the links below: Innovating a New Knowledge Base for Water Justice Studies: Hydrosocial, Sociohydrology, and Beyond Scale Issues in Human-Water Systems Water Resources and Human Behavior: Analysis and Modeling of Coupled Water-Human Systems Feedbacks and Coevolution Innovative Sensing, Observing, Measuring and Analysing Human-Water Data “Pluralistic water research” integrates the hydrological and the social to provide sustainable solutions to water crises. While relying upon robust quantitative modelling, sociohydrology captures crises across many waters (surface, ground and interstitial) along quantity and quality dimensions, hydrosocial unfurls power hierarchies in access to safe and required quota of water, be it for drinking or irrigation purposes. The success of engineering solutions laying out “hard” interventions such as solar powered irrigation, dams, high yielding crop varieties, water treatment plants and water distributions and purifications depend on “soft” socio-political, cultural and psychological variables like the political landscape, community behaviours and governance arrangements. How these soft parameters limit or advance the effect of hard interventions await more enhanced modelling and place-based qualitative analyses to disentangle various cause-effect pathways. While historical and process-based sociohydrology accommodates detailed temporal datasets and causal relationships across human-water systems, the hydrosocial paradigm reconciles “non-modern”, anti-hegemonic, water techniques and knowledge systems, animating local agencies within specific hydroscapes. This issue is dedicated to capture real time innovations through which water challenges have been confronted. It intends to unravel “storylines” along actionable water projects, reflecting on mediations across multiple actors and networks in specific spatio-temporal and cultural contexts, finally drawing our attention to the correlation between projected promises and actual realities. Situated at the crossroads of “boundary work”, we invite articles that will deploy a range of interdisciplinary frameworks like RANAS (Risk, Attitude, Norms, Ability, and Self-regulation), APIE (Awareness, Participation, Involvement and Engagement), HUPE (Historical Urban Political Ecology), etc. to demonstrate coupled sociohydrological and hydrosocial realties and in turn getting informed by empirical insights emanating from these actual water interventions. The final aim of the special issue is not to showcase water just actual interventions but to elicit a rigorous mapping of sustainable processes facilitating collective co-production of resilient water trajectories.

Bayesian Networks and Decision Graphs

Author :
Publisher :
ISBN 13 : 9781475735048
Total Pages : 268 pages
Book Rating : 4.7/5 (35 download)

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Book Synopsis Bayesian Networks and Decision Graphs by :

Download or read book Bayesian Networks and Decision Graphs written by and published by . This book was released on 2001 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian networks and decision graphs are formal graphical languages for representation and communication of decision scenarios requiring reasoning under uncertainty. Their strengths are two-sided. It is easy for humans to construct and to understand them, and when communicated to a computer, they can easily be compiled. Furthermore, handy algorithms are developed for analyses of the models and for providing responses to a wide range of requests such as belief updating, determining optimal strategies, conflict analyses of evidence, and most probable explanation. The book emphasizes both the human and the computer sides. Part I gives a thorough introduction to Bayesian networks as well as decision trees and infulence diagrams, and through examples and exercises, the reader is instructed in building graphical models from domain knowledge. This part is self-contained and it does not require other background than standard secondary school mathematics. Part II is devoted to the presentation of algorithms and complexity issues. This part is also self-contained, but it requires that the reader is familiar with working with texts in the mathematical language. The author also: - provides a well-founded practical introduction to Bayesian networks, decision trees and influence diagrams; - gives several examples and exercises exploiting the computer systems for Bayesian netowrks and influence diagrams; - gives practical advice on constructiong Bayesian networks and influence diagrams from domain knowledge; - embeds decision making into the framework of Bayesian networks; - presents in detail the currently most efficient algorithms for probability updating in Bayesian networks; - discusses a wide range of analyes tools and model requests together with algorithms for calculation of responses; - gives a detailed presentation of the currently most efficient algorithm for solving influence diagrams.

A Bayesian Network Based Decision Support System for the Management of Fiels Operations

Author : C. Grøn Sørensen
Publisher :
ISBN 13 :
Total Pages : 194 pages
Book Rating : 4.:/5 (473 download)

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Book Synopsis A Bayesian Network Based Decision Support System for the Management of Fiels Operations by : C. Grøn Sørensen

Download or read book A Bayesian Network Based Decision Support System for the Management of Fiels Operations written by C. Grøn Sørensen and published by . This book was released on 1999 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Bayesian Network Technologies

Author : Ankush Mittal
Publisher : Igi Publishing
ISBN 13 : 159904143X
Total Pages : 356 pages
Book Rating : 4.5/5 (99 download)

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Book Synopsis Bayesian Network Technologies by : Ankush Mittal

Download or read book Bayesian Network Technologies written by Ankush Mittal and published by Igi Publishing. This book was released on 2007-01-01 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides an excellent, well-balanced collection of areas where Bayesian networks have been successfully applied; it describes the underlying concepts of Bayesian Networks with the help of diverse applications, and theories that prove Bayesian networks valid"--Provided by publisher.

Probabilistic Methods for Bionformatics

Author : Richard E. Neapolitan
Publisher : Morgan Kaufmann
ISBN 13 : 9780123704764
Total Pages : 406 pages
Book Rating : 4.7/5 (47 download)

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Book Synopsis Probabilistic Methods for Bionformatics by : Richard E. Neapolitan

Download or read book Probabilistic Methods for Bionformatics written by Richard E. Neapolitan and published by Morgan Kaufmann. This book was released on 2009 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. This text explains the application of probability and statistics, in particular Bayesian networks, to genetics.