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Applied multivariate analysis
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ISBN: 0070479356 Year: 1972 Publisher: New York

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Data analysis for psychology
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ISBN: 0340691360 Year: 1998 Publisher: London Arnold

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R for dummies
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ISBN: 9781119055808 1119055806 9781119055839 9781119055853 1119055857 1119055830 Year: 2015 Publisher: Hoboken, New Jersey : John Wiley & Sons, Inc.,

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This accessible guide is the ideal introduction to R for complete beginners. Learn to master the programming language of choice among statisticians and data analysts worldwide.

L'analyse quali-quantitative comparée (AQQC-QCA) : approche, techniques et applications en sciences humaines
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ISBN: 2872096639 9782872096633 Year: 2002 Volume: 3 Publisher: Bruxelles : Bruylant,


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An introduction to survey research and data analysis
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ISBN: 0716704846 0716704854 0816704854 9780716704843 Year: 1977 Publisher: San Francisco, CA : W. H. Freeman,

Agent-based models.
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ISBN: 9781412949644 1412949645 1412983258 1452207488 Year: 2008 Volume: 153 Publisher: Thousand Oaks Sage

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Agent-based modeling (ABM) is a technique increasingly used in a broad range of social sciences. It involves building a computational model consisting of agents, each of which represents an actor in the social world, and an "environment" in which the agents act. Agents are able to interact with each other and are programmed to be pro-active, autonomous and able to perceive their virtual world. The techniques of ABM are derived from artificial intelligence and computer science, but are now being developed independently in research centers throughout the world. In Agent-Based Models, Nigel Gilbert reviews a range of examples of agent-based modeling, describes how to design and build your own models, and considers practical issues such as verification, validation, planning a modeling project, and how to structure a scholarly article reporting the results of agent-based modeling. It includes a glossary, an annotated list of resources, advice on which programming environment to use when creating agent-based models, and a worked, step-by-step example of the development of an ABM. This latest volume in the SAGE Quantitative Applications in the Social Sciences series will have wide appeal in the social sciences, including the disciplines of sociology, economics, social psychology, geography, economic history, science studies, and environmental studies. It is appropriate for graduate students, researchers and academics in these fields, for both those wanting to keep up with new developments in their fields and those who are considering using ABM for their research. Aimed at readers who are new to ABMOffers a brief, but thorough, treatment of a cutting-edge techniqueOffers practical advice about how to design and create ABMIncludes carefully chosen examples from different disciplines

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