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Zustand: New. The Laurence and Lynne Brown Democracy Medal is an initiative of the McCourtney Institute for Democracy at Pennsylvania State University. It annually recognizes outstanding individuals, groups, and organizations that produce exceptional innovations to furth.

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Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Micah Altman¿is¿Director of Research¿at the¿Program on Information Science¿for the MIT Libraries. He has authored more than seventy articles, a half-dozen open-source software packages, and several books and monographs correcting computational errors in the social sciences. Michael P. McDonald is Associate Professor of¿Political Science at the University of Florida¿and a Non-Resident Senior Fellow at the¿Brookings Institution.¿He is a coprincipal investigator on the¿Public Mapping Project. Widely published in scholarly journals and law reviews, he is coauthor with Micah Altman and Jeff Gill of Numerical Issues in Statistical Computing for the Social Scientist.

Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Micah Altman¿is¿Director of Research¿at the¿Program on Information Science¿for the MIT Libraries. He has authored more than seventy articles, a half-dozen open-source software packages, and several books and monographs correcting computational errors in the social sciences. Michael P. McDonald is Associate Professor of¿Political Science at the University of Florida¿and a Non-Resident Senior Fellow at the¿Brookings Institution.¿He is a coprincipal investigator on the¿Public Mapping Project. Widely published in scholarly journals and law reviews, he is coauthor with Micah Altman and Jeff Gill of Numerical Issues in Statistical Computing for the Social Scientist.

Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Micah Altman¿is¿Director of Research¿at the¿Program on Information Science¿for the MIT Libraries. He has authored more than seventy articles, a half-dozen open-source software packages, and several books and monographs correcting computational errors in the social sciences. Michael P. McDonald is Associate Professor of¿Political Science at the University of Florida¿and a Non-Resident Senior Fellow at the¿Brookings Institution.¿He is a coprincipal investigator on the¿Public Mapping Project. Widely published in scholarly journals and law reviews, he is coauthor with Micah Altman and Jeff Gill of Numerical Issues in Statistical Computing for the Social Scientist.

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Hardcover. Zustand: new. Hardcover. At lasta 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)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. Serving as a "bridge" to prepare social scientists and students for professional-level use of statistics, this volume outlines the main numerical estimations issues along with various means of avoiding specific common pitfalls. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Zustand: New. pp. xv + 323 Illus.

Hardcover. Zustand: new. Hardcover. At lasta 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)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. Serving as a "bridge" to prepare social scientists and students for professional-level use of statistics, this volume outlines the main numerical estimations issues along with various means of avoiding specific common pitfalls. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Zustand: New. Serving as a "bridge" to prepare social scientists and students for professional-level use of statistics, this volume outlines the main numerical estimations issues along with various means of avoiding specific common pitfalls. Series: Wiley Series in Probability and Statistics. Num Pages: 324 pages, Illustrations. BIC Classification: JHBC; PBT; PBW. Category: (P) Professional & Vocational. Dimension: 243 x 162 x 20. Weight in Grams: 614. . 2003. 1st Edition. Hardcover. . . . .

Zustand: New. pp. xv + 323.

Hardcover. Zustand: Brand New. 1st edition. 323 pages. 9.25x6.25x0.75 inches. In Stock.

Zustand: New. Serving as a "bridge" to prepare social scientists and students for professional-level use of statistics, this volume outlines the main numerical estimations issues along with various means of avoiding specific common pitfalls. Series: Wiley Series in Probability and Statistics. Num Pages: 324 pages, Illustrations. BIC Classification: JHBC; PBT; PBW. Category: (P) Professional & Vocational. Dimension: 243 x 162 x 20. Weight in Grams: 614. . 2003. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.

Buch. Zustand: Neu. Neuware - At last-a social scientist s guide through the pitfalls of modern statistical computingAddressing 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 ® )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.

Hardcover. Zustand: new. Hardcover. At lasta 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)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. Serving as a "bridge" to prepare social scientists and students for professional-level use of statistics, this volume outlines the main numerical estimations issues along with various means of avoiding specific common pitfalls. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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