Numerical Issues in Statistical Computing for the Social Scientist (Wiley Series in Probability and Statistics)

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9780471236337: Numerical Issues in Statistical Computing for the Social Scientist (Wiley Series in Probability and Statistics)
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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.

"synopsis" may belong to another edition of this title.

From the Author:

If you have any interest in creating statistical analyses that are accurate, I hope you will read the full reviews on the website, our sample chapters, and, eventually, our book. If you read it, I hope that you will find it both provocative and useful. Our web site provides related papers, all of the computer code used in the book, links to resources useful for accurate statistical computing, and links to every independent review we have located.

About the Author:

MICAH ALTMAN is Associate Director of the Harvard-MIT DataCenter in Cambridge, Massachusetts.

JEFF GILL is Associate Professor of Political Science atthe University of California, Davis.

MICHAEL P. McDONALD is Assistant Professor of Governmentand Politics at George Mason University in Fairfax, Virginia.

"About this title" may belong to another edition of this title.

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Book Description John Wiley and Sons Ltd, United States, 2003. Hardback. Condition: New. Language: English. Brand new Book. At last a social scientist's guide through the pitfalls of modern statistical computing Addressing the current deficiency in the literature on statistical methods as they apply to the social and behavioral sciences, Numerical Issues in Statistical Computing for the Social Scientist seeks to provide readers with a unique practical guidebook to the numerical methods underlying computerized statistical calculations specific to these fields. The authors demonstrate that knowledge of these numerical methods and how they are used in statistical packages is essential for making accurate inferences. With the aid of key contributors from both the social and behavioral sciences, the authors have assembled a rich set of interrelated chapters designed to guide empirical social scientists through the potential minefield of modern statistical computing. Uniquely accessible and abounding in modern-day tools, tricks, and advice, the text successfully bridges the gap between the current level of social science methodology and the more sophisticated technical coverage usually associated with the statistical field. Highlights include: A focus on problems occurring in maximum likelihood estimationIntegrated examples of statistical computing (using software packages such as the SAS, Gauss, Splus, R, Stata, LIMDEP, SPSS, WinBUGS, and MATLAB (R))A guide to choosing accurate statistical packagesDiscussions of a multitude of computationally intensive statistical approaches such as ecological inference, Markov chain Monte Carlo, and spatial regression analysisEmphasis on specific numerical problems, statistical procedures, and their applications in the fieldReplications and re-analysis of published social science research, using innovative numerical methodsKey numerical estimation issues along with the means of avoiding common pitfallsA related Web site includes test data for use in demonstrating numerical problems, code for applying the original methods described in the book, and an online bibliography of Web resources for the statistical computation Designed as an independent research tool, a professional reference, or a classroom supplement, the book presents a well-thought-out treatment of a complex and multifaceted field. Seller Inventory # AAH9780471236337

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Book Description John Wiley and Sons Ltd, United States, 2003. Hardback. Condition: New. New. Language: English . Brand New Book. At last a social scientist s guide through the pitfalls of modern statistical computing Addressing the current deficiency in the literature on statistical methods as they apply to the social and behavioral sciences, Numerical Issues in Statistical Computing for the Social Scientist seeks to provide readers with a unique practical guidebook to the numerical methods underlying computerized statistical calculations specific to these fields. The authors demonstrate that knowledge of these numerical methods and how they are used in statistical packages is essential for making accurate inferences. With the aid of key contributors from both the social and behavioral sciences, the authors have assembled a rich set of interrelated chapters designed to guide empirical social scientists through the potential minefield of modern statistical computing. Uniquely accessible and abounding in modern-day tools, tricks, and advice, the text successfully bridges the gap between the current level of social science methodology and the more sophisticated technical coverage usually associated with the statistical field. Highlights include: A focus on problems occurring in maximum likelihood estimationIntegrated examples of statistical computing (using software packages such as the SAS, Gauss, Splus, R, Stata, LIMDEP, SPSS, WinBUGS, and MATLAB (R))A guide to choosing accurate statistical packagesDiscussions of a multitude of computationally intensive statistical approaches such as ecological inference, Markov chain Monte Carlo, and spatial regression analysisEmphasis on specific numerical problems, statistical procedures, and their applications in the fieldReplications and re-analysis of published social science research, using innovative numerical methodsKey numerical estimation issues along with the means of avoiding common pitfallsA related Web site includes test data for use in demonstrating numerical problems, code for applying the original methods described in the book, and an online bibliography of Web resources for the statistical computation Designed as an independent research tool, a professional reference, or a classroom supplement, the book presents a well-thought-out treatment of a complex and multifaceted field. Seller Inventory # AAH9780471236337

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Book Description John Wiley and Sons Ltd, United States, 2003. Hardback. Condition: New. Language: English. Brand new Book. At last a social scientist's guide through the pitfalls of modern statistical computing Addressing the current deficiency in the literature on statistical methods as they apply to the social and behavioral sciences, Numerical Issues in Statistical Computing for the Social Scientist seeks to provide readers with a unique practical guidebook to the numerical methods underlying computerized statistical calculations specific to these fields. The authors demonstrate that knowledge of these numerical methods and how they are used in statistical packages is essential for making accurate inferences. With the aid of key contributors from both the social and behavioral sciences, the authors have assembled a rich set of interrelated chapters designed to guide empirical social scientists through the potential minefield of modern statistical computing. Uniquely accessible and abounding in modern-day tools, tricks, and advice, the text successfully bridges the gap between the current level of social science methodology and the more sophisticated technical coverage usually associated with the statistical field. Highlights include: A focus on problems occurring in maximum likelihood estimationIntegrated examples of statistical computing (using software packages such as the SAS, Gauss, Splus, R, Stata, LIMDEP, SPSS, WinBUGS, and MATLAB (R))A guide to choosing accurate statistical packagesDiscussions of a multitude of computationally intensive statistical approaches such as ecological inference, Markov chain Monte Carlo, and spatial regression analysisEmphasis on specific numerical problems, statistical procedures, and their applications in the fieldReplications and re-analysis of published social science research, using innovative numerical methodsKey numerical estimation issues along with the means of avoiding common pitfallsA related Web site includes test data for use in demonstrating numerical problems, code for applying the original methods described in the book, and an online bibliography of Web resources for the statistical computation Designed as an independent research tool, a professional reference, or a classroom supplement, the book presents a well-thought-out treatment of a complex and multifaceted field. Seller Inventory # LIE9780471236337

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