Monte Carlo Simulation (Quantitative Applications in the Social Sciences) 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2025
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Mooney, Christopher Z. 作者
Sage Publications, Inc
译者
1997-04-07 出版日期
112 页数
USD 17.95 价格
Paperback
Quantitative Applications in the Social Sciences 丛书系列
9780803959439 图书编码
Monte Carlo Simulation (Quantitative Applications in the Social Sciences) 在线电子书 图书标签:
统计学
数学
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发表于2025-03-01
Monte Carlo Simulation (Quantitative Applications in the Social Sciences) 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2025
Monte Carlo Simulation (Quantitative Applications in the Social Sciences) 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2025
Monte Carlo Simulation (Quantitative Applications in the Social Sciences) 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2025
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Monte Carlo Simulation (Quantitative Applications in the Social Sciences) 在线电子书 著者简介
Monte Carlo Simulation (Quantitative Applications in the Social Sciences) 在线电子书 图书目录
Monte Carlo Simulation (Quantitative Applications in the Social Sciences) 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载
Monte Carlo Simulation (Quantitative Applications in the Social Sciences) 在线电子书 图书描述
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. The author explains the logic behind the method and demonstrates its uses for social and behavioural 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, Christopher Z Mooney carefully demonstrates how to prepare computer algorithms using GAUSS code and uses several research examples to demonstrate these principles. This volume will enable researchers to execute Monte Carlo simulation effectively and to interpret the estimated sampling distribution generated from its use.
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