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Simulation For The Social Scientist

Author: Gilbert, Nigel
Publisher: McGraw-Hill Education (UK)
ISBN: 0335225128
Size: 43.31 MB
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Social sciences -- Simulation methods. Social interaction -- Computer simulation. Social sciences -- Mathematical models. (publisher)

Handbuch Modellbildung Und Simulation In Den Sozialwissenschaften

Author: Norman Braun
Publisher: Springer-Verlag
ISBN: 3658011645
Size: 42.92 MB
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Das Handbuch Modellbildung und Simulation in den Sozialwissenschaften bietet in 37 Artikeln einen umfassenden Überblick über sozialwissenschaftliche Modellbildung und Simulation. Es vermittelt wissenschaftstheoretische und methodische Grundlagen sowie den Stand der Forschung in den wichtigsten Anwendungsgebieten. Behandelt werden realistische, strukturalistische und konstruktivistische Zugriffe auf Modellbildung und Simulation, bedeutende Methoden und Typen der Modellierung (u.a. stochastische Prozesse und Bayes-Verfahren, nutzen- und spieltheoretische Modellierungen) und Ansätze der Computersimulation (z.B. Multi-Agenten-Modelle, zelluläre Automaten, neuronale Netze, Small Worlds). Die Anwendungskapitel befassen sich u.a. mit sozialen Dilemmata, sozialen Normen, Innovation und Diffusion, Herrschaft und Organisation, Gewalt und Krieg.

Handbuch Methoden Der Organisationsforschung

Author: Stefan Kühl
Publisher: Springer-Verlag
ISBN: 9783531158273
Size: 36.55 MB
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Das Handbuch verschafft einen umfassenden Überblick über die quantitativen und qualitativen Methoden der Organisationsforschung. Die übergreifende Struktur, die durchgängige Herangehensweise und der hohe Praxisbezug versetzen Wissenschaftler, Studierende und insbesondere Praktiker in die Lage, das Methodeninstrumentarium der Organisationsforschung gezielt für eigene Zwecke zu nutzen.

Numerical Issues In Statistical Computing For The Social Scientist

Author: Micah Altman
Publisher: John Wiley & Sons
ISBN: 0471475742
Size: 64.54 MB
Format: PDF
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At last—a social scientist's guide through the pitfalls ofmodern statistical computing Addressing the current deficiency in the literature onstatistical methods as they apply to the social and behavioralsciences, Numerical Issues in Statistical Computing for the SocialScientist seeks to provide readers with a unique practicalguidebook to the numerical methods underlying computerizedstatistical calculations specific to these fields. The authorsdemonstrate that knowledge of these numerical methods and how theyare used in statistical packages is essential for making accurateinferences. With the aid of key contributors from both the socialand behavioral sciences, the authors have assembled a rich set ofinterrelated chapters designed to guide empirical social scientiststhrough the potential minefield of modern statisticalcomputing. Uniquely accessible and abounding in modern-day tools, tricks,and advice, the text successfully bridges the gap between thecurrent level of social science methodology and the moresophisticated technical coverage usually associated with thestatistical field. Highlights include: A focus on problems occurring in maximum likelihoodestimation Integrated examples of statistical computing (using softwarepackages such as the SAS, Gauss, Splus, R, Stata, LIMDEP, SPSS,WinBUGS, and MATLAB®) A guide to choosing accurate statistical packages Discussions of a multitude of computationally intensivestatistical approaches such as ecological inference, Markov chainMonte Carlo, and spatial regression analysis Emphasis on specific numerical problems, statisticalprocedures, and their applications in the field Replications and re-analysis of published social scienceresearch, using innovative numerical methods Key numerical estimation issues along with the means ofavoiding common pitfalls A related Web site includes test data for use in demonstratingnumerical problems, code for applying the original methodsdescribed in the book, and an online bibliography of Web resourcesfor the statistical computation Designed as an independent research tool, a professionalreference, or a classroom supplement, the book presents awell-thought-out treatment of a complex and multifaceted field.

From Postgraduate To Social Scientist

Author: Nigel Gilbert
Publisher: SAGE
ISBN: 9780761944607
Size: 74.22 MB
Format: PDF
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From Postgraduate to Social Scientist is essential reading for any postgraduate or new researcher who is interested in a career in the social sciences. The book describes the skills needed for success in moving from being a student to becoming an academic or professional social scientist. Written by experts in the field, Gilbert et al., this book offers a unique insider's view of how to make the transition. By adopting a clear and accessible approach, this book encourages students embarking on the journey towards becoming a social scientist to engage with every aspect of the process.

Information Technology For The Social Scientist

Author: Ray Lee University of London.
Publisher: Routledge
ISBN: 1134218141
Size: 20.83 MB
Format: PDF, ePub, Docs
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Accessible and practical overview to help social reseachers make the most of information technology in relation to research design and selection, management and analysis of research data. The book pinpoints current and future trends in computer-assisted methods.; This book is intended for postgraduate and undergraduate social research methods courses and professional social researchers in sociology, social policy and administration, social psychology and geography. Particular appeal to courses in computer applications for social scientists and researchers.

Cooperative Agents

Author: N.J. Saam
Publisher: Springer Science & Business Media
ISBN: 9401711771
Size: 45.86 MB
Format: PDF, ePub
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Agent-based modelling on a computer appears to have a special role to play in the development of social science. It offers a means of discovering general and applicable social theory, and grounding it in precise assumptions and derivations, whilst addressing those elements of individual cognition that are central to human society. However, there are important questions to be asked and difficulties to overcome in achieving this potential. What differentiates agent-based modelling from traditional computer modelling? Which model types should be used under which circumstances? If it is appropriate to use a complex model, how can it be validated? Is social simulation research to adopt a realist epistemology, or can it operate within a social constructionist framework? What are the sociological concepts of norms and norm processing that could either be used for planned implementation or for identifying equivalents of social norms among co-operative agents? Can sustainability be achieved more easily in a hierarchical agent society than in a society of isolated agents? What examples are there of hybrid forms of interaction between humans and artificial agents? These are some of the sociological questions that are addressed.

Introduction To Discrete Event Simulation And Agent Based Modeling

Author: Theodore T. Allen
Publisher: Springer Science & Business Media
ISBN: 9780857291394
Size: 59.10 MB
Format: PDF
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Discrete event simulation and agent-based modeling are increasingly recognized as critical for diagnosing and solving process issues in complex systems. Introduction to Discrete Event Simulation and Agent-based Modeling covers the techniques needed for success in all phases of simulation projects. These include: • Definition – The reader will learn how to plan a project and communicate using a charter. • Input analysis – The reader will discover how to determine defensible sample sizes for all needed data collections. They will also learn how to fit distributions to that data. • Simulation – The reader will understand how simulation controllers work, the Monte Carlo (MC) theory behind them, modern verification and validation, and ways to speed up simulation using variation reduction techniques and other methods. • Output analysis – The reader will be able to establish simultaneous intervals on key responses and apply selection and ranking, design of experiments (DOE), and black box optimization to develop defensible improvement recommendations. • Decision support – Methods to inspire creative alternatives are presented, including lean production. Also, over one hundred solved problems are provided and two full case studies, including one on voting machines that received international attention. Introduction to Discrete Event Simulation and Agent-based Modeling demonstrates how simulation can facilitate improvements on the job and in local communities. It allows readers to competently apply technology considered key in many industries and branches of government. It is suitable for undergraduate and graduate students, as well as researchers and other professionals.