Advanced Statistics From An Elementary Point Of View

Advanced Statistics from an Elementary Point of View PDF
Author: Michael J Panik
Publisher: Academic Press
ISBN: 9780120884940
Size: 44.74 MB
Format: PDF, ePub, Mobi
Category : Mathematics
Languages : en
Pages : 802
View: 5453

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Clearly explains concepts and stategies in mathematical statistics.

From Voice To Influence

From Voice to Influence PDF
Author: Danielle Allen
Publisher: University of Chicago Press
ISBN: 022626243X
Size: 19.95 MB
Format: PDF, Kindle
Category : Political Science
Languages : en
Pages : 376
View: 3752

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How have online protests—like the recent outrage over the Komen Foundation’s decision to defund Planned Parenthood—changed the nature of political action? How do Facebook and other popular social media platforms shape the conversation around current political issues? The ways in which we gather information about current events and communicate it with others have been transformed by the rapid rise of digital media. The political is no longer confined to the institutional and electoral arenas, and that has profound implications for how we understand citizenship and political participation. With From Voice to Influence, Danielle Allen and Jennifer S. Light have brought together a stellar group of political and social theorists, social scientists, and media analysts to explore this transformation. Threading through the contributions is the notion of egalitarian participatory democracy, and among the topics discussed are immigration rights activism, the participatory potential of hip hop culture, and the porous boundary between public and private space on social media. The opportunities presented for political efficacy through digital media to people who otherwise might not be easily heard also raise a host of questions about how to define “good participation:” Does the ease with which one can now participate in online petitions or conversations about current events seduce some away from serious civic activities into “slacktivism?” Drawing on a diverse body of theory, from Hannah Arendt to Anthony Appiah, From Voice to Influence offers a range of distinctive visions for a political ethics to guide citizens in a digitally connected world.

A Computational Approach To Statistical Learning

A Computational Approach to Statistical Learning PDF
Author: Taylor Arnold
Publisher: CRC Press
ISBN: 1351694758
Size: 64.46 MB
Format: PDF, Docs
Category : Business & Economics
Languages : en
Pages : 362
View: 7705

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A Computational Approach to Statistical Learning gives a novel introduction to predictive modeling by focusing on the algorithmic and numeric motivations behind popular statistical methods. The text contains annotated code to over 80 original reference functions. These functions provide minimal working implementations of common statistical learning algorithms. Every chapter concludes with a fully worked out application that illustrates predictive modeling tasks using a real-world dataset. The text begins with a detailed analysis of linear models and ordinary least squares. Subsequent chapters explore extensions such as ridge regression, generalized linear models, and additive models. The second half focuses on the use of general-purpose algorithms for convex optimization and their application to tasks in statistical learning. Models covered include the elastic net, dense neural networks, convolutional neural networks (CNNs), and spectral clustering. A unifying theme throughout the text is the use of optimization theory in the description of predictive models, with a particular focus on the singular value decomposition (SVD). Through this theme, the computational approach motivates and clarifies the relationships between various predictive models. Taylor Arnold is an assistant professor of statistics at the University of Richmond. His work at the intersection of computer vision, natural language processing, and digital humanities has been supported by multiple grants from the National Endowment for the Humanities (NEH) and the American Council of Learned Societies (ACLS). His first book, Humanities Data in R, was published in 2015. Michael Kane is an assistant professor of biostatistics at Yale University. He is the recipient of grants from the National Institutes of Health (NIH), DARPA, and the Bill and Melinda Gates Foundation. His R package bigmemory won the Chamber's prize for statistical software in 2010. Bryan Lewis is an applied mathematician and author of many popular R packages, including irlba, doRedis, and threejs.

Big Data Analytics

Big Data Analytics PDF
Author: Vasudha Bhatnagar
Publisher: Springer
ISBN: 3319036890
Size: 16.51 MB
Format: PDF
Category : Computers
Languages : en
Pages : 197
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This book constitutes the thoroughly refereed conference proceedings of the Second International Conference on Big Data Analytics, BDA 2013, held in Mysore, India, in December 2013. The 13 revised full papers were carefully reviewed and selected from 49 submissions and cover topics on mining social media data, perspectives on big data analysis, graph analysis, big data in practice.

Effective Grant Writing And Program Evaluation For Human Service Professionals

Effective Grant Writing and Program Evaluation for Human Service Professionals PDF
Author: Francis K. O. Yuen
Publisher: John Wiley & Sons
ISBN: 0470564431
Size: 16.25 MB
Format: PDF, ePub, Mobi
Category : Business & Economics
Languages : en
Pages : 288
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A state-of-the-art guide for developing grants witha strong emphasis on using program outcome measurement to underscore need and accountability Based on the authors' many years of experience in the public and nonprofit sectors, Effective Grant Writing and Program Evaluation for Human Service Professionals integrates the topics of grant proposal writing and program evaluation, offering grant seekers the practical guidance they need to develop quality proposals, obtain funding, and demonstrate service results and accountability. The authors clearly and succinctly illustrate and describe each stage of the grant writing and evaluation process. Problems or issues that arise frequently are highlighted and followed by specific advice. In addition, numerous real-world examples and exercises are included throughout the book to give readers the opportunity for reflection and practice. This timely reference incorporates a strengths perspective, providing: An inside look at the grant writing and evaluation processes, with insights from experienced grant writers, agency administrators, foundation program managers, and grant reviewers Specific examples of successful grant proposals and evaluation plans and instruments serving as models for learning and practice Field-tested individual and group exercises that facilitate the development of grant writing and evaluation skills Discussion of electronic technology in grant writing and evaluation, including writing and submitting grant proposals online, and identifying funding sources This grant writing and program evaluation guide follows a needs-driven, evidence-based, result-oriented, and client-centered perspective. Its authoritative discussion equips human service professionals to effectively develop grants with a strong emphasis on measuring program outcomes.

Probability And Statistical Inference

Probability and Statistical Inference PDF
Author: Nitis Mukhopadhyay
Publisher: CRC Press
ISBN: 9780824703790
Size: 74.81 MB
Format: PDF, Docs
Category : Mathematics
Languages : en
Pages : 665
View: 751

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Priced very competitively compared with other textbooks at this level! This gracefully organized textbook reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, numerous figures and tables, and computer simulations to develop and illustrate concepts. Beginning with an introduction to the basic ideas and techniques in probability theory and progressing to more rigorous topics, Probability and Statistical Inference studies the Helmert transformation for normal distributions and the waiting time between failures for exponential distributions develops notions of convergence in probability and distribution spotlights the central limit theorem (CLT) for the sample variance introduces sampling distributions and the Cornish-Fisher expansions concentrates on the fundamentals of sufficiency, information, completeness, and ancillarity explains Basu's Theorem as well as location, scale, and location-scale families of distributions covers moment estimators, maximum likelihood estimators (MLE), Rao-Blackwellization, and the Cramér-Rao inequality discusses uniformly minimum variance unbiased estimators (UMVUE) and Lehmann-Scheffé Theorems focuses on the Neyman-Pearson theory of most powerful (MP) and uniformly most powerful (UMP) tests of hypotheses, as well as confidence intervals includes the likelihood ratio (LR) tests for the mean, variance, and correlation coefficient summarizes Bayesian methods describes the monotone likelihood ratio (MLR) property handles variance stabilizing transformations provides a historical context for statistics and statistical discoveries showcases great statisticians through biographical notes Employing over 1400 equations to reinforce its subject matter, Probability and Statistical Inference is a groundbreaking text for first-year graduate and upper-level undergraduate courses in probability and statistical inference who have completed a calculus prerequisite, as well as a supplemental text for classes in Advanced Statistical Inference or Decision Theory.

Complex Variables With Applications

Complex Variables with Applications PDF
Author: Saminathan Ponnusamy
Publisher: Springer Science & Business Media
ISBN: 9780817645137
Size: 59.63 MB
Format: PDF, ePub, Mobi
Category : Mathematics
Languages : en
Pages : 514
View: 4755

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Explores the interrelations between real and complex numbers by adopting both generalization and specialization methods to move between them, while simultaneously examining their analytic and geometric characteristics Engaging exposition with discussions, remarks, questions, and exercises to motivate understanding and critical thinking skills Encludes numerous examples and applications relevant to science and engineering students

Theory Of Statistics

Theory of Statistics PDF
Author: Mark J. Schervish
Publisher: Springer Science & Business Media
ISBN: 1461242509
Size: 50.23 MB
Format: PDF, Mobi
Category : Mathematics
Languages : en
Pages : 716
View: 7085

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The aim of this graduate textbook is to provide a comprehensive advanced course in the theory of statistics covering those topics in estimation, testing, and large sample theory which a graduate student might typically need to learn as preparation for work on a Ph.D. An important strength of this book is that it provides a mathematically rigorous and even-handed account of both Classical and Bayesian inference in order to give readers a broad perspective. For example, the "uniformly most powerful" approach to testing is contrasted with available decision-theoretic approaches.

Six Sigma And Beyond

Six Sigma and Beyond PDF
Author: D.H. Stamatis
Publisher: CRC Press
ISBN: 1420000268
Size: 26.33 MB
Format: PDF, Docs
Category : Business & Economics
Languages : en
Pages : 368
View: 2607

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Researchers and professionals in all walks of life need to use the many tools offered by the statistical world, but often do not have the necessary experience in both concept and application. No matter what your profession, sooner or later numbers need to be crunched, and often you need to understand how to do it, and why it is important. Quality control is no different. Six Sigma and Beyond: Statistics and Probability covers the concepts of some useful statistical tools, appropriate formulae for specific tools, the connection of statistics to probability, and how to use them. This volume introduces the relationship of statistics, probability, and reliability as they apply to quality in general and to Six Sigma in particular. The author brings the theoretical into the practical by providing statistical techniques, tests, and methods that the reader can use in any organization. He reviews basic parametric and non-parametric statistics, probability concepts and applications, and addresses topics for both measurable and attribute characteristics. He delineates the importance of collecting, analyzing, and interpreting data not from an academic point of view but from a practical perspective. This is not a textbook but a guide for anyone interested in statistical, probability, and reliability to improve processes and profitability in their organizations. When you begin a study of something, you want to do it well. You want to design a good study, analyze the results properly, and prepare a cogent report that summarizes what you've found. Six Sigma and Beyond: Statistics and Probability shows you how to use statistical tools to improve your processes and give your organization the competitive edge.

Advanced Linear Modeling

Advanced Linear Modeling PDF
Author: Ronald Christensen
Publisher: Springer Science & Business Media
ISBN: 9780387952963
Size: 75.76 MB
Format: PDF, Docs
Category : Mathematics
Languages : en
Pages : 398
View: 3121

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This book introduces several topics related to linear model theory: multivariate linear models, discriminant analysis, principal components, factor analysis, time series in both the frequency and time domains, and spatial data analysis. The second edition adds new material on nonparametric regression, response surface maximization, and longitudinal models. The book provides a unified approach to these disparate subject and serves as a self-contained companion volume to the author's Plane Answers to Complex Questions: The Theory of Linear Models. Ronald Christensen is Professor of Statistics at the University of New Mexico. He is well known for his work on the theory and application of linear models having linear structure. He is the author of numerous technical articles and several books and he is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics. Also Available: Christensen, Ronald. Plane Answers to Complex Questions: The Theory of Linear Models, Second Edition (1996). New York: Springer-Verlag New York, Inc. Christensen, Ronald. Log-Linear Models and Logistic Regression, Second Edition (1997). New York: Springer-Verlag New York, Inc.