Monte Carlo Simulation

AvChristopher Z. Mooney,Christopher Z. Mooney

Häftad, Engelska, 1997

Del 116 i serien Quantitative Applications in the Social Sciences

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Beskrivning

Monte Carlo Simulation is a method of evaluating substantive hypotheses and statistical estimators by developing a computer algorithm to simulate a population, drawing multiple samples from this pseudo-population, and evaluating estimates obtained from these samples. Christopher Z. Mooney explains the logic behind Monte Carlo Simulation and demonstrates its uses for social and behavioral research in conducting inference using statistics with only weak mathematical theory, testing null hypotheses under a variety of plausible conditions, assessing the robustness of parametric inference to violations of its assumptions, assessing the quality of inferential methods, and comparing the properties of two or more estimators. In addition, Mooney carefully demonstrates how to prepare computer algorithms using GAUSS code and illustrates these principles using several research examples.
is a method of evaluating substantive hypotheses and statistical estimators by developing a computer algorithm to simulate a population, drawing multiple samples from this pseudo-population, and evaluating estimates obtained from these samples. Christopher Z. Mooney explains the logic behind and demonstrates its uses for social and behavioral research in conducting inference using statistics with only weak mathematical theory, testing null hypotheses under a variety of plausible conditions, assessing the robustness of parametric inference to violations of its assumptions, assessing the quality of inferential methods, and comparing the properties of two or more estimators. In addition, Mooney carefully demonstrates how to prepare computer algorithms using GAUSS code and illustrates these principles using several research examples. Monte Carlo Simulation will enable researchers to effectively execute Monte Carlo Simulation and to interpret the estimated sampling distribution generated from its use.

will enable researchers to effectively execute Monte Carlo Simulation and to interpret the estimated sampling distribution generated from its use.

Produktinformation

Utgivningsdatum:1997-05-16
Mått:139 x 215 x 6 mm
Vikt:140 g
Format:Häftad
Språk:Engelska
Serie:Quantitative Applications in the Social Sciences
Antal sidor:112
Upplaga:1
Förlag:SAGE Publications
ISBN:9780803959439

Utforska kategorier

Sociologi inom Samhälle och politik

Mer om författaren

Christopher Z. Mooney is a professor of political studies with a joint appointment in the Institute of Government and Public Affairs.Mooney studies U.S. state politics and policy, with special focus on legislative decision making, morality policy, and legislative term limits.He is the founding editor of State Politics and Policy Quarterly, the premier academic journal in its field and has published dozens of articles and books, including Lobbying Illinois - How You Can Make a Difference in Public Policy.Prior to arriving at UIS in 1999, he taught at West Virginia University and the University of Essex in the United Kingdom

Innehållsförteckning

IntroductionGenerating Individual Samples from a Pseudo-PopulationUsing the Pseudo-Population in Monte Carlo SimulationUsing Monte Carlo Simulation in the Social SciencesConclusion