Integrating Inferences

Integrating Inferences PDF Author: Macartan Humphreys
Publisher: Cambridge University Press
ISBN: 1107169623
Category : Social Science
Languages : en
Pages : 435

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Book Description
Develops a new approach to the use of causal models for qualitative and mixed-method research design and causal inference.

Integrating Inferences

Integrating Inferences PDF Author: Macartan Humphreys
Publisher: Cambridge University Press
ISBN: 1107169623
Category : Social Science
Languages : en
Pages : 435

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Book Description
Develops a new approach to the use of causal models for qualitative and mixed-method research design and causal inference.

Bayesian Inference in Statistical Analysis

Bayesian Inference in Statistical Analysis PDF Author: George E. P. Box
Publisher: John Wiley & Sons
ISBN: 111803144X
Category : Mathematics
Languages : en
Pages : 610

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Book Description
Its main objective is to examine the application and relevance of Bayes' theorem to problems that arise in scientific investigation in which inferences must be made regarding parameter values about which little is known a priori. Begins with a discussion of some important general aspects of the Bayesian approach such as the choice of prior distribution, particularly noninformative prior distribution, the problem of nuisance parameters and the role of sufficient statistics, followed by many standard problems concerned with the comparison of location and scale parameters. The main thrust is an investigation of questions with appropriate analysis of mathematical results which are illustrated with numerical examples, providing evidence of the value of the Bayesian approach.

Statistical Inference in Science

Statistical Inference in Science PDF Author: D.A. Sprott
Publisher: Springer Science & Business Media
ISBN: 0387227660
Category : Mathematics
Languages : en
Pages : 254

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Book Description
A treatment of the problems of inference associated with experiments in science, with the emphasis on techniques for dividing the sample information into various parts, such that the diverse problems of inference that arise from repeatable experiments may be addressed. A particularly valuable feature is the large number of practical examples, many of which use data taken from experiments published in various scientific journals. This book evolved from the authors own courses on statistical inference, and assumes an introductory course in probability, including the calculation and manipulation of probability functions and density functions, transformation of variables and the use of Jacobians. While this is a suitable text book for advanced undergraduate, Masters, and Ph.D. statistics students, it may also be used as a reference book.

Aspects of Statistical Inference

Aspects of Statistical Inference PDF Author: A. H. Welsh
Publisher: John Wiley & Sons
ISBN: 1118165438
Category : Mathematics
Languages : en
Pages : 480

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Book Description
Relevant, concrete, and thorough--the essential data-based text onstatistical inference The ability to formulate abstract concepts and draw conclusionsfrom data is fundamental to mastering statistics. Aspects ofStatistical Inference equips advanced undergraduate and graduatestudents with a comprehensive grounding in statistical inference,including nonstandard topics such as robustness, randomization, andfinite population inference. A. H. Welsh goes beyond the standard texts and expertly synthesizesbroad, critical theory with concrete data and relevant topics. Thetext follows a historical framework, uses real-data sets andstatistical graphics, and treats multiparameter problems, yet isultimately about the concepts themselves. Written with clarity and depth, Aspects of Statistical Inference: * Provides a theoretical and historical grounding in statisticalinference that considers Bayesian, fiducial, likelihood, andfrequentist approaches * Illustrates methods with real-data sets on diabetic retinopathy,the pharmacological effects of caffeine, stellar velocity, andindustrial experiments * Considers multiparameter problems * Develops large sample approximations and shows how to use them * Presents the philosophy and application of robustness theory * Highlights the central role of randomization in statistics * Uses simple proofs to illuminate foundational concepts * Contains an appendix of useful facts concerning expansions,matrices, integrals, and distribution theory Here is the ultimate data-based text for comparing and presentingthe latest approaches to statistical inference.

Diagrammatic Representation and Inference

Diagrammatic Representation and Inference PDF Author: Alan Blackwell
Publisher: Springer Science & Business Media
ISBN: 354021268X
Category : Art
Languages : en
Pages : 469

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Book Description
This book constitutes the refereed proceedings of the Third International Conference, Diagrams 2004, held in Cambridge, UK, in March 2004. The 18 revised full papers and 42 revised poster papers presented together with a survey article and the abstracts of 2 posters were carefully reviewed and selected from a total of 91 submissions. The papers are organized in topical sections on fundamental issues, logical aspects of diagrammatic representation and reasoning, computational aspects of diagrammatic representation and reasoning, cognitive aspects of diagrammatic representation and reasoning, visualizing information with diagrams, diagrams in human-computer interaction, and diagrams in software engineering.

Reading Development and Difficulties

Reading Development and Difficulties PDF Author: Kate Cain
Publisher: John Wiley & Sons
ISBN: 1405151552
Category : Psychology
Languages : en
Pages : 276

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Book Description
Reading Development and Difficulties is a comprehensive and balanced introduction to the development of the two core aspects of reading: good word reading skills and the ability to extract the overall meaning of a text. Unique in its balanced coverage of both word reading and reading comprehension development, this book is an essential resource for undergraduates studying literacy acquisition Offers wide coverage of the subject and discusses both typical development and the development of difficulties in reading Accessibly written for students and professionals with no previous background in reading development or reading difficulties Provides a detailed examination of the specific problems that underlie reading difficulties

Inferences during Reading

Inferences during Reading PDF Author: Edward J. O'Brien
Publisher: Cambridge University Press
ISBN: 1107049792
Category : Education
Languages : en
Pages : 439

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Book Description
A study of inferencing from a wide variety of theoretical and disciplinary perspectives, as well as different levels of processing.

Age of Inference

Age of Inference PDF Author: Philip C. Short
Publisher: IAP
ISBN: 1648027997
Category : Education
Languages : en
Pages : 487

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Book Description
In an age where we are inundated with information, the ability to discern verifiable information to make proper decisions and solve problems is ever more critical. Modern science, which espouses a systematic approach to making “inferences,” requires a certain mindset that allows for a degree of comfort with uncertainty. This book offers inspirations and ideas for cultivating the proper mindset for the studying, teaching, and practicing of science that will be useful for those new to as well as familiar with the field. Although a paradigm shift from traditional instruction is suggested in the National Framework for K-12 science, this volume is intended to help educators develop a personal mental framework in which to transition from a teacher-centered, didactical approach to a student-centered, evidence-guided curriculum. While the topics of the book derive from currently published literature on STEM education as they relate to the National Framework for K-12 Science and the Three-Dimensional science instruction embedded in the Next Generation Science Standards, this book also examines these topics in the context of a new societal age posited as the “Age of Inference” and addresses how to make sense of the ever-increasing deluge of information that we are experiencing by having a scientific and properly discerning mindset. ENDORSEMENTS: "This volume takes on one of the thorniest existential problems of our time, the contradiction between the exponentially growing amount of information that individuals have access to, and the diminished capacity of those individuals to understand it. Its chapters provide the reader with an introduction to the relationship between knowledge, science, and inference; needed new approaches to learning science in our new data rich world; and a discussion of what we can and must do to reduce or eliminate the growing gap between the inference have’s and have nots. It is not too much to say that how we resolve the issues outlined in this volume will determine the future of our species on this planet." — Joseph L. Graves Jr., Professor of Biological Sciences North Carolina A&T State University, Fellow, American Association for the Advancement of Science: Biological Sciences, Author of: The Emperor’s New Clothes: Biological Theories of Race at the Millennium "Big data is not enough for addressing dangers to the environment or tackling threats to democracy; we need the ability to draw sound inferences from the data. Cultivating a scientific mindset requires fundamental changes to the way we teach and learn. This important and well -written volume shows how." — Ashok Goel, Professor of Computer Science and Human Centered Computing, Georgia Institute of Technology. Editor of AI Magazine Founding Editor of AAAI’s Interactive AI Magazine "If you are a science teacher concerned about the implications of information overload, analysis paralysis, and intellectual complacency on our health, economic future, and democracy, then I recommend this book." — Michael Svec, Professor for Physics and Astronomy Education, Furman University, Fulbright Scholar to Czech Republic

Quantitative Assessment and Validation of Network Inference Methods in Bioinformatics

Quantitative Assessment and Validation of Network Inference Methods in Bioinformatics PDF Author: Benjamin Haibe-Kains
Publisher: Frontiers Media SA
ISBN: 2889194787
Category : Bioengineering
Languages : en
Pages : 192

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Book Description
Scientists today have access to an unprecedented arsenal of high-tech tools that can be used to thoroughly characterize biological systems of interest. High-throughput “omics” technologies enable to generate enormous quantities of data at the DNA, RNA, epigenetic and proteomic levels. One of the major challenges of the post-genomic era is to extract functional information by integrating such heterogeneous high-throughput genomic data. This is not a trivial task as we are increasingly coming to understand that it is not individual genes, but rather biological pathways and networks that drive an organism’s response to environmental factors and the development of its particular phenotype. In order to fully understand the way in which these networks interact (or fail to do so) in specific states (disease for instance), we must learn both, the structure of the underlying networks and the rules that govern their behavior. In recent years there has been an increasing interest in methods that aim to infer biological networks. These methods enable the opportunity for better understanding the interactions between genomic features and the overall structure and behavior of the underlying networks. So far, such network models have been mainly used to identify and validate new interactions between genes of interest. But ultimately, one could use these networks to predict large-scale effects of perturbations, such as treatment by multiple targeted drugs. However, currently, we are still at an early stage of comprehending methods and approaches providing a robust statistical framework to quantitatively assess the quality of network inference and its predictive potential. The scope of this Research Topic in Bioinformatics and Computational Biology aims at addressing these issues by investigating the various, complementary approaches to quantify the quality of network models. These “validation” techniques could focus on assessing quality of specific interactions, global and local structures, and predictive ability of network models. These methods could rely exclusively on in silico evaluation procedures or they could be coupled with novel experimental designs to generate the biological data necessary to properly validate inferred networks.

Advances in Mixed Methods Research

Advances in Mixed Methods Research PDF Author: Manfred Max Bergman
Publisher: SAGE
ISBN: 1446241211
Category : Social Science
Languages : en
Pages : 202

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Book Description
Advances in Mixed Methods Research provides an essential introduction to the fast-growing field of mixed methods research. Bergman′s book examines the current state of mixed-methods research, exploring exciting new ways of conceptualizing and conducting empirical research in the social and health sciences. Contributions from the world′s leading experts in qualitative, quantitative, and mixed methods approaches are brought together, clearing the way for a more constructive approach to social research. These contributions cover the main practical and methodological issues and include a number of different visions of what mixed methods research is. The discussion also covers the use of mixed methods in a diverse range of fields, including sociology, education, politics, psychology, computational science and methodology. This book represents an important contribution to the ongoing debate surrounding the use of mixed methods in the social sciences and health research, and presents a convincing argument that the conventional, paradigmatic view of qualitative and quantitative research is outdated and in need of replacement. It will be essential reading for anyone actively engaged in qualitative, quantitative and mixed methods research and for students of social research methods. Manfred Max Bergman is Chair of Methodology and Political Sociology at the University of Basel.