lynch scott m m (30 Ergebnisse)

Hardcover. Zustand: Near Fine. First Edition; First Printing. 4to 11" - 13" tall; 32 pages; [SIGNED] 2007 Paulist Press. Oversize HC in glossy color pictorial boards. Signed on the title page with non personalized inscriptions by both Lynch and Oatman. Tightly bound and fresh copy feels and appears unread. Issued without dust wrapper. About as new. Fine ; Signed by Author & Illustrator.

Paperback. Zustand: Good. 1. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New.

XXIII, 229 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.

hardcover. Zustand: Very Good. Cover and edges may have some wear.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Hardcover. Zustand: Brand New. illustrated edition. 32 pages. 10.00x8.00x0.50 inches. In Stock.

Zustand: New. In.

Paperback. Zustand: Brand New. 187 pages. 8.25x5.50x0.50 inches. In Stock.

Zustand: New. 2022. 1st Edition. Paperback. . . . . . Books ship from the US and Ireland.

Zustand: New. In.

Zustand: NEW.

Kartoniert / Broschiert. Zustand: New. Applied Bayesian Statistics provides a broad, but in-depth introduction to Bayesian statistics, both in terms of its basic theoretical underpinnings and its contemporary methods of application. The book is highly applied more of a how to .

Zustand: New. In.

Taschenbuch. Zustand: Neu. Neuware - Bayesian statistical analyses have become increasingly common over the last two decades. The rapid increase in computing power that facilitated their implementation coincided with major changes in the research interests of, and data availability for, social scientists. Specifically, the last two decades have seen an increase in the availability of panel data sets, other hierarchically structured data sets including spatially organized data, along with interests in life course processes and the influence of context on individual behavior and outcomes. The Bayesian approach to statistics is well-suited for these types of data and research questions. Applied Bayesian Statistics is an introduction to these methods that is geared toward social scientists. Author Scott M. Lynch makes the material accessible by emphasizing application more than theory, explaining the math in a step-by-step fashion, and demonstrating the Bayesian approach in analyses of U.S. political trends drawing on data from the General Social Survey.

Zustand: New. In.

Taschenbuch. Zustand: Neu. Neuware -This book covers applied statistics for the social sciences with upper-level undergraduate students in mind. The chapters are based on lecture notes from an introductory statistics course the author has taught for a number of years. The book integrates statistics into the research process, with early chapters covering basic philosophical issues underpinning the process of scientific research. These include the concepts of deductive reasoning and the falsifiability of hypotheses, the development of a research question and hypotheses, and the process of data collection and measurement. Probability theory is then covered extensively with a focus on its role in laying the foundation for statistical reasoning and inference. After illustrating the Central Limit Theorem, later chapters address the key, basic statistical methods used in social science research, including various z and t tests and confidence intervals, nonparametric chi square tests, one-way analysis of variance, correlation, simple regression, and multiple regression, with a discussion of the key issues involved in thinking about causal processes.Concepts and topics are illustrated using both real and simulated data.The penultimate chapter presents rules and suggestions for the successful presentation of statistics in tabular and graphic formats, and the final chapter offers suggestions for subsequent reading and study.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 256 pp. Englisch.

Paperback. Zustand: Brand New. reprint edition. 252 pages. 9.25x6.10x0.58 inches. In Stock.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book covers applied statistics for the social sciences with upper-level undergraduate students in mind. The chapters are based on lecture notes from an introductory statistics course the author has taught for a number of years. The book integrates statistics into the research process, with early chapters covering basic philosophical issues underpinning the process of scientific research. These include the concepts of deductive reasoning and the falsifiability of hypotheses, the development of a research question and hypotheses, and the process of data collection and measurement. Probability theory is then covered extensively with a focus on its role in laying the foundation for statistical reasoning and inference. After illustrating the Central Limit Theorem, later chapters address the key, basic statistical methods used in social science research, including various z and t tests and confidence intervals, nonparametric chi square tests, one-way analysis of variance, correlation, simple regression, and multiple regression, with a discussion of the key issues involved in thinking about causal processes. Concepts and topics are illustrated using both real and simulated data. The penultimate chapter presents rules and suggestions for the successful presentation of statistics in tabular and graphic formats, and the final chapter offers suggestions for subsequent reading and study.

Buch. Zustand: Neu. Neuware -This book covers applied statistics for the social sciences with upper-level undergraduate students in mind. The chapters are based on lecture notes from an introductory statistics course the author has taught for a number of years. The book integrates statistics into the research process, with early chapters covering basic philosophical issues underpinning the process of scientific research. These include the concepts of deductive reasoning and the falsifiability of hypotheses, the development of a research question and hypotheses, and the process of data collection and measurement. Probability theory is then covered extensively with a focus on its role in laying the foundation for statistical reasoning and inference. After illustrating the Central Limit Theorem, later chapters address the key, basic statistical methods used in social science research, including various z and t tests and confidence intervals, nonparametric chi square tests, one-way analysis of variance, correlation, simple regression, and multiple regression, with a discussion of the key issues involved in thinking about causal processes.Concepts and topics are illustrated using both real and simulated data.The penultimate chapter presents rules and suggestions for the successful presentation of statistics in tabular and graphic formats, and the final chapter offers suggestions for subsequent reading and study.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 256 pp. Englisch.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book covers applied statistics for the social sciences with upper-level undergraduate students in mind. The chapters are based on lecture notes from an introductory statistics course the author has taught for a number of years. The book integrates statistics into the research process, with early chapters covering basic philosophical issues underpinning the process of scientific research. These include the concepts of deductive reasoning and the falsifiability of hypotheses, the development of a research question and hypotheses, and the process of data collection and measurement. Probability theory is then covered extensively with a focus on its role in laying the foundation for statistical reasoning and inference. After illustrating the Central Limit Theorem, later chapters address the key, basic statistical methods used in social science research, including various z and t tests and confidence intervals, nonparametric chi square tests, one-way analysis of variance, correlation, simple regression, and multiple regression, with a discussion of the key issues involved in thinking about causal processes. Concepts and topics are illustrated using both real and simulated data. The penultimate chapter presents rules and suggestions for the successful presentation of statistics in tabular and graphic formats, and the final chapter offers suggestions for subsequent reading and study.

Zustand: New. In.

Taschenbuch. Zustand: Neu. Neuware -'Introduction to Applied Bayesian Statistics and Estimation for Social Scientists' covers the complete process of Bayesian statistical analysis in great detail from the development of a model through the process of making statistical inference. The key feature of this book is that it covers models that are most commonly used in social science research - including the linear regression model, generalized linear models, hierarchical models, and multivariate regression models - and it thoroughly develops each real-data example in painstaking detail.The first part of the book provides a detailed introduction to mathematical statistics and the Bayesian approach to statistics, as well as a thorough explanation of the rationale for using simulation methods to construct summaries of posterior distributions. Markov chain Monte Carlo (MCMC) methods - including the Gibbs sampler and the Metropolis-Hastings algorithm - are then introduced as general methods for simulating samples from distributions. Extensive discussion of programming MCMC algorithms, monitoring their performance, and improving them is provided before turning to the larger examples involving real social science models and data.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 388 pp. Englisch.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 'Introduction to Applied Bayesian Statistics and Estimation for Social Scientists' covers the complete process of Bayesian statistical analysis in great detail from the development of a model through the process of making statistical inference. The key feature of this book is that it covers models that are most commonly used in social science research - including the linear regression model, generalized linear models, hierarchical models, and multivariate regression models - and it thoroughly develops each real-data example in painstaking detail.The first part of the book provides a detailed introduction to mathematical statistics and the Bayesian approach to statistics, as well as a thorough explanation of the rationale for using simulation methods to construct summaries of posterior distributions. Markov chain Monte Carlo (MCMC) methods - including the Gibbs sampler and the Metropolis-Hastings algorithm - are then introduced as general methods for simulating samples from distributions. Extensive discussion of programming MCMC algorithms, monitoring their performance, and improving them is provided before turning to the larger examples involving real social science models and data.

Paperback. Zustand: Brand New. 364 pages. 8.80x6.00x1.10 inches. In Stock.

Gebunden. Zustand: New. First book written at an introductory level for social scientists interested in learning about MCMCThis book outlines Bayesian statistical analysis in great detail, from the development of a model through the process of making statistical inference. .

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 'Introduction to Applied Bayesian Statistics and Estimation for Social Scientists' covers the complete process of Bayesian statistical analysis in great detail from the development of a model through the process of making statistical inference. The key feature of this book is that it covers models that are most commonly used in social science research - including the linear regression model, generalized linear models, hierarchical models, and multivariate regression models - and it thoroughly develops each real-data example in painstaking detail.The first part of the book provides a detailed introduction to mathematical statistics and the Bayesian approach to statistics, as well as a thorough explanation of the rationale for using simulation methods to construct summaries of posterior distributions. Markov chain Monte Carlo (MCMC) methods - including the Gibbs sampler and the Metropolis-Hastings algorithm - are then introduced as general methods for simulating samples from distributions. Extensive discussion of programming MCMC algorithms, monitoring their performance, and improving them is provided before turning to the larger examples involving real social science models and data.

Hardcover. Slight wear to dustjacket, otherwise very good condition. B/W illus. Includes papers on Shakespeare and the Medieval Theatre of Cruelty; Cosmos and History: Shakespeare's Representation of Nature and Rebellion in Henry IV Part One; The Plague of Christendom: Discord and Chastity on Othello; Othello's Exsufflations; Bearded Women and the Cultural Moment in Macbeth; Marlowe, Maps and Might; Ben Jonson and 'the proper passion of Mettals'; Madness in A Yorkshire Tragedy and The Pilgrim; Paradises Lost: Invaded Houses in Donne's Poetry; Andrew Marvell and the Tree of Life; Disgrace as J.M. Coetzee's Tempest etc. 353pp. ISBN 9781847186102.