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Product Description
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Requiring only a background in introductory statistics, calculus, and matrix algebra, Bayesian Methods: A Social and Behavioral Sciences Approach provides detailed explanations of derivations and theories using a computationally oriented approach. The second edition of this popular text features new updates on such topics as MCMC algorithms, perfect sampling, and Bayesian nonparametrics. It emphasizes the R computing environment as well as the Bugs simulation program. It also includes various examples and exercise problems. This text remains an ideal resource for statisticians, and is especially designed to help political and social scientists develop a tool chest for statistical analysis.
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Requiring only a background in introductory statistics, calculus, and matrix algebra, Bayesian Methods: A Social and Behavioral Sciences Approach provides detailed explanations of derivations and theories using a computationally oriented approach. The second edition of this popular text features new updates on such topics as MCMC algorithms, perfect sampling, and Bayesian nonparametrics. It emphasizes the R computing environment as well as the Bugs simulation program. It also includes various examples and exercise problems. This text remains an ideal resource for statisticians, and is especially designed to help political and social scientists develop a tool chest for statistical analysis.
See all Product Description
Requiring only a background in introductory statistics, calculus, and matrix algebra, Bayesian Methods: A Social and Behavioral Sciences Approach provides detailed explanations of derivations and theories using a computationally oriented approach. The second edition of this popular text features new updates on such topics as MCMC algorithms, perfect sampling, and Bayesian nonparametrics. It emphasizes the R computing environment as well as the Bugs simulation program. It also includes various examples and exercise problems. This text remains an ideal resource for statisticians, and is especially designed to help political and social scientists develop a tool chest for statistical analysis.
From the Back Cover
Requiring only a background in introductory statistics, calculus, and matrix algebra, Bayesian Methods: A Social and Behavioral Sciences Approach provides detailed explanations of derivations and theories using a computationally oriented approach. The second edition of this popular text features new updates on such topics as MCMC algorithms, perfect sampling, and Bayesian nonparametrics. It emphasizes the R computing environment as well as the Bugs simulation program. It also includes various examples and exercise problems. This text remains an ideal resource for statisticians, and is especially designed to help political and social scientists develop a tool chest for statistical analysis.
See all Product Description
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First Sentence
Statistical analysis is the process of separating out systematic effects from the random noise inherent in all sets of observations. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
Statistical analysis is the process of separating out systematic effects from the random noise inherent in all sets of observations. Read the first page
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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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