Scientific Methods for the Treatment of Uncertainty in Social Sciences PDF Download
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Author: Jaime Gil-Aluja
Publisher: Springer
ISBN: 3319197045
Category : Technology & Engineering
Languages : en
Pages : 430
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Book Description
This book is a collection of selected papers presented at the SIGEF conference, held at the Faculty of Economics and Business of the University of Girona (Spain), 06-08 July, 2015. This edition of the conference has been presented with the slogan “Scientific methods for the treatment of uncertainty in social sciences”. There are different ways for dealing with uncertainty in management. The book focuses on soft computing theories and their role in assessing uncertainty in a complex world. It gives a comprehensive overview of quantitative management topics and discusses some of the most recent developments in all the areas of business and management in soft computing including Decision Making, Expert Systems and Forgotten Effects Theory, Forecasting Models, Fuzzy Logic and Fuzzy Sets, Modelling and Simulation Techniques, Neural Networks and Genetic Algorithms and Optimization and Control. The book might be of great interest for anyone working in the area of management and business economics and might be especially useful for scientists and graduate students doing research in these fields.
Author: Jaime Gil-Aluja
Publisher: Springer
ISBN: 3319197045
Category : Technology & Engineering
Languages : en
Pages : 430
Get Book Here
Book Description
This book is a collection of selected papers presented at the SIGEF conference, held at the Faculty of Economics and Business of the University of Girona (Spain), 06-08 July, 2015. This edition of the conference has been presented with the slogan “Scientific methods for the treatment of uncertainty in social sciences”. There are different ways for dealing with uncertainty in management. The book focuses on soft computing theories and their role in assessing uncertainty in a complex world. It gives a comprehensive overview of quantitative management topics and discusses some of the most recent developments in all the areas of business and management in soft computing including Decision Making, Expert Systems and Forgotten Effects Theory, Forecasting Models, Fuzzy Logic and Fuzzy Sets, Modelling and Simulation Techniques, Neural Networks and Genetic Algorithms and Optimization and Control. The book might be of great interest for anyone working in the area of management and business economics and might be especially useful for scientists and graduate students doing research in these fields.
Author: Anol Bhattacherjee
Publisher: CreateSpace
ISBN: 9781475146127
Category : Science
Languages : en
Pages : 156
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Book Description
This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309486165
Category : Science
Languages : en
Pages : 257
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Book Description
One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.
Author: Kostas Kampourakis
Publisher: Oxford University Press, USA
ISBN: 0190871660
Category : Philosophy
Languages : en
Pages : 273
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Book Description
Anti-evolutionists, climate denialists, and anti-vaxxers, among others, question some of the best-established scientific findings by referring to the uncertainties in these areas of research. Uncertainty: How It Makes Science Advance shows that uncertainty is an inherent feature of science that makes it advance by motivating further research.
Author: Marcel Boumans
Publisher: Routledge
ISBN: 1317319486
Category : History
Languages : en
Pages : 264
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Book Description
Assessment of error and uncertainty is a vital component of both natural and social science. This edited volume presents case studies of research practices across a wide spectrum of scientific fields. It compares methodologies and presents the ingredients needed for an overarching framework applicable to all.
Author: Sandra W. Pyke
Publisher:
ISBN:
Category : Social Science
Languages : en
Pages : 328
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Book Description
This reference source provides coverage of the various research methods used in the social sciences. Explaining all the major research designs, techniques and data analysis strategies, it also explains each method in terms of its strengths, weaknesses and sources of error. Examples of student assignments are used to demonstrate the practical applications of abstract research principles. The text provides coverage of the key features of a research enterprise, such as quantitative and qualitative research designs, statistics, theory, ethics bias, validity and report writing. New features of this fifth edition include further discussion of fraud and misconduct in science and of qualitative research methods including Q-sort. There is examination of the increased reliance by government and the courts on police science, and introduction of new statistical concepts such as factor analysis and meta analysis. A revised concluding chapter discusses contemporary meta-theoretical issues and conceptual/methodological trends.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309133092
Category : Education
Languages : en
Pages : 204
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Book Description
Researchers, historians, and philosophers of science have debated the nature of scientific research in education for more than 100 years. Recent enthusiasm for "evidence-based" policy and practice in educationâ€"now codified in the federal law that authorizes the bulk of elementary and secondary education programsâ€"have brought a new sense of urgency to understanding the ways in which the basic tenets of science manifest in the study of teaching, learning, and schooling. Scientific Research in Education describes the similarities and differences between scientific inquiry in education and scientific inquiry in other fields and disciplines and provides a number of examples to illustrate these ideas. Its main argument is that all scientific endeavors share a common set of principles, and that each fieldâ€"including education researchâ€"develops a specialization that accounts for the particulars of what is being studied. The book also provides suggestions for how the federal government can best support high-quality scientific research in education.
Author: Luc Wilkin
Publisher:
ISBN: 9789024726882
Category :
Languages : en
Pages : 285
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Book Description
Author: Ryan G. McClarren
Publisher: Springer
ISBN: 3319995251
Category : Science
Languages : en
Pages : 345
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Book Description
This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties. It addresses a critical knowledge gap in the widespread adoption of simulation in high-consequence decision-making throughout the engineering and physical sciences. Constructing sophisticated techniques for prediction from basic building blocks, the book first reviews the fundamentals that underpin later topics of the book including probability, sampling, and Bayesian statistics. Part II focuses on applying Local Sensitivity Analysis to apportion uncertainty in the model outputs to sources of uncertainty in its inputs. Part III demonstrates techniques for quantifying the impact of parametric uncertainties on a problem, specifically how input uncertainties affect outputs. The final section covers techniques for applying uncertainty quantification to make predictions under uncertainty, including treatment of epistemic uncertainties. It presents the theory and practice of predicting the behavior of a system based on the aggregation of data from simulation, theory, and experiment. The text focuses on simulations based on the solution of systems of partial differential equations and includes in-depth coverage of Monte Carlo methods, basic design of computer experiments, as well as regularized statistical techniques. Code references, in python, appear throughout the text and online as executable code, enabling readers to perform the analysis under discussion. Worked examples from realistic, model problems help readers understand the mechanics of applying the methods. Each chapter ends with several assignable problems. Uncertainty Quantification and Predictive Computational Science fills the growing need for a classroom text for senior undergraduate and early-career graduate students in the engineering and physical sciences and supports independent study by researchers and professionals who must include uncertainty quantification and predictive science in the simulations they develop and/or perform.
Author: Frank H. Knight
Publisher: Cosimo, Inc.
ISBN: 1602060053
Category : Business & Economics
Languages : en
Pages : 401
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Book Description
A timeless classic of economic theory that remains fascinating and pertinent today, this is Frank Knight's famous explanation of why perfect competition cannot eliminate profits, the important differences between "risk" and "uncertainty," and the vital role of the entrepreneur in profitmaking. Based on Knight's PhD dissertation, this 1921 work, balancing theory with fact to come to stunning insights, is a distinct pleasure to read. FRANK H. KNIGHT (1885-1972) is considered by some the greatest American scholar of economics of the 20th century. An economics professor at the University of Chicago from 1927 until 1955, he was one of the founders of the Chicago school of economics, which influenced Milton Friedman and George Stigler.