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Author: August Meitzen
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 264
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Book Description
Author: August Meitzen
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 264
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Book Description
Author: Stephen M. Stigler
Publisher: Harvard University Press
ISBN: 0674256859
Category : History
Languages : en
Pages : 436
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Book Description
This magnificent book is the first comprehensive history of statistics from its beginnings around 1700 to its emergence as a distinct and mature discipline around 1900. Stephen M. Stigler shows how statistics arose from the interplay of mathematical concepts and the needs of several applied sciences including astronomy, geodesy, experimental psychology, genetics, and sociology. He addresses many intriguing questions: How did scientists learn to combine measurements made under different conditions? And how were they led to use probability theory to measure the accuracy of the result? Why were statistical methods used successfully in astronomy long before they began to play a significant role in the social sciences? How could the introduction of least squares predate the discovery of regression by more than eighty years? On what grounds can the major works of men such as Bernoulli, De Moivre, Bayes, Quetelet, and Lexis be considered partial failures, while those of Laplace, Galton, Edgeworth, Pearson, and Yule are counted as successes? How did Galton’s probability machine (the quincunx) provide him with the key to the major advance of the last half of the nineteenth century? Stigler’s emphasis is upon how, when, and where the methods of probability theory were developed for measuring uncertainty in experimental and observational science, for reducing uncertainty, and as a conceptual framework for quantitative studies in the social sciences. He describes with care the scientific context in which the different methods evolved and identifies the problems (conceptual or mathematical) that retarded the growth of mathematical statistics and the conceptual developments that permitted major breakthroughs. Statisticians, historians of science, and social and behavioral scientists will gain from this book a deeper understanding of the use of statistical methods and a better grasp of the promise and limitations of such techniques. The product of ten years of research, The History of Statistics will appeal to all who are interested in the humanistic study of science.
Author: P.K. Bhattacharya
Publisher: Academic Press
ISBN: 0128041234
Category : Mathematics
Languages : en
Pages : 546
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Book Description
Theory and Methods of Statistics covers essential topics for advanced graduate students and professional research statisticians. This comprehensive resource covers many important areas in one manageable volume, including core subjects such as probability theory, mathematical statistics, and linear models, and various special topics, including nonparametrics, curve estimation, multivariate analysis, time series, and resampling. The book presents subjects such as "maximum likelihood and sufficiency," and is written with an intuitive, heuristic approach to build reader comprehension. It also includes many probability inequalities that are not only useful in the context of this text, but also as a resource for investigating convergence of statistical procedures. - Codifies foundational information in many core areas of statistics into a comprehensive and definitive resource - Serves as an excellent text for select master's and PhD programs, as well as a professional reference - Integrates numerous examples to illustrate advanced concepts - Includes many probability inequalities useful for investigating convergence of statistical procedures
Author: Carol S. Aneshensel
Publisher: SAGE
ISBN: 1412994357
Category : Reference
Languages : en
Pages : 473
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Book Description
This book presents the elaboration model for the multivariate analysis of observational quantitative data. This model entails the systematic introduction of "third variables" to the analysis of a focal relationship between one independent and one dependent variable to ascertain whether an inference of causality is justified. Two complementary strategies are used: an exclusionary strategy that rules out alternative explanations such as spuriousness and redundancy with competing theories, and an inclusive strategy that connects the focal relationship to a network of other relationships, including the hypothesized causal mechanisms linking the focal independent variable to the focal dependent variable. The primary emphasis is on the translation of theory into a logical analytic strategy and the interpretation of results. The elaboration model is applied with case studies drawn from newly published research that serve as prototypes for aligning theory and the data analytic plan used to test it; these studies are drawn from a wide range of substantive topics in the social sciences, such as emotion management in the workplace, subjective age identification during the transition to adulthood, and the relationship between religious and paranormal beliefs. The second application of the elaboration model is in the form of original data analysis presented in two Analysis Journals that are integrated throughout the text and implement the full elaboration model. Using real data, not contrived examples, the text provides a step-by-step guide through the process of integrating theory with data analysis in order to arrive at meaningful answers to research questions.
Author: Ricardo A. Maronna
Publisher: John Wiley & Sons
ISBN: 1119214688
Category : Mathematics
Languages : en
Pages : 466
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Book Description
A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation of methodology using the increasingly popular open-source software R. Classical statistics fail to cope well with outliers associated with deviations from standard distributions. Robust statistical methods take into account these deviations when estimating the parameters of parametric models, thus increasing the reliability of fitted models and associated inference. This new, second edition of Robust Statistics: Theory and Methods (with R) presents a broad coverage of the theory of robust statistics that is integrated with computing methods and applications. Updated to include important new research results of the last decade and focus on the use of the popular software package R, it features in-depth coverage of the key methodology, including regression, multivariate analysis, and time series modeling. The book is illustrated throughout by a range of examples and applications that are supported by a companion website featuring data sets and R code that allow the reader to reproduce the examples given in the book. Unlike other books on the market, Robust Statistics: Theory and Methods (with R) offers the most comprehensive, definitive, and up-to-date treatment of the subject. It features chapters on estimating location and scale; measuring robustness; linear regression with fixed and with random predictors; multivariate analysis; generalized linear models; time series; numerical algorithms; and asymptotic theory of M-estimates. Explains both the use and theoretical justification of robust methods Guides readers in selecting and using the most appropriate robust methods for their problems Features computational algorithms for the core methods Robust statistics research results of the last decade included in this 2nd edition include: fast deterministic robust regression, finite-sample robustness, robust regularized regression, robust location and scatter estimation with missing data, robust estimation with independent outliers in variables, and robust mixed linear models. Robust Statistics aims to stimulate the use of robust methods as a powerful tool to increase the reliability and accuracy of statistical modelling and data analysis. It is an ideal resource for researchers, practitioners, and graduate students in statistics, engineering, computer science, and physical and social sciences.
Author: Thomas J. Archdeacon
Publisher: Univ of Wisconsin Press
ISBN: 9780299136543
Category : History
Languages : en
Pages : 380
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Book Description
A blueprint for historians to understand and evaluate the variables and discusses the fundamentals of regression analysis. 2 looks at procedures for assessing the level of association among diagnostic methods for identifying and correcting shortcomings Finally, part 3 presents more advanced topics, including in regression models. quantitative analyses they're likely to encounter in journal literature and monographs on research in the social sciences. ignore the fact that most historians have little background in mathematics would be folly, to decipher equations and follow their logic. Concepts are introduced carefully, and the operation of equations is explained step by step. Annotation copyright by Book News, Inc., Portland, OR
Author: David A. Freedman
Publisher: Cambridge University Press
ISBN: 1139477315
Category : Mathematics
Languages : en
Pages : 459
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Book Description
This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized around published studies, as are many of the exercises. Relevant journal articles are reprinted at the back of the book. Freedman makes a thorough appraisal of the statistical methods in these papers and in a variety of other examples. He illustrates the principles of modelling, and the pitfalls. The discussion shows you how to think about the critical issues - including the connection (or lack of it) between the statistical models and the real phenomena. The book is written for advanced undergraduates and beginning graduate students in statistics, as well as students and professionals in the social and health sciences.
Author: Robert Emmet Chaddock
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 498
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Book Description
Author: Johann Pfanzagl
Publisher: Springer
ISBN: 3642310842
Category : Mathematics
Languages : en
Pages : 321
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Book Description
This book presents a detailed description of the development of statistical theory. In the mid twentieth century, the development of mathematical statistics underwent an enduring change, due to the advent of more refined mathematical tools. New concepts like sufficiency, superefficiency, adaptivity etc. motivated scholars to reflect upon the interpretation of mathematical concepts in terms of their real-world relevance. Questions concerning the optimality of estimators, for instance, had remained unanswered for decades, because a meaningful concept of optimality (based on the regularity of the estimators, the representation of their limit distribution and assertions about their concentration by means of Anderson’s Theorem) was not yet available. The rapidly developing asymptotic theory provided approximate answers to questions for which non-asymptotic theory had found no satisfying solutions. In four engaging essays, this book presents a detailed description of how the use of mathematical methods stimulated the development of a statistical theory. Primarily focused on methodology, questionable proofs and neglected questions of priority, the book offers an intriguing resource for researchers in theoretical statistics, and can also serve as a textbook for advanced courses in statisticc.
Author: Lee J. Bain
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 474
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Book Description
Probabilistic models; Basic statistical inference; The exponential distribution; The weibull distribution; The gamma distribution; Extreme-value distribution; The logistic and other distribution; Goodness-of-fit tests.
