Topics In Statistical Methodology
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Topics In Statistical Methodology
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Author : Suddhendu Biswas
language : en
Publisher: New Age International
Release Date : 1991
Topics In Statistical Methodology written by Suddhendu Biswas and has been published by New Age International this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Mathematics categories.
The Text Book Covers All Traditional As Well As Newly Emerging Topics In Statistical Methodology. A Broad General Description Of The Book Consists Of(I) A Lucid Presentation To The Motivation Of The Modern Axiomatic Approach To Probability.(Ii) Study Of All Major Distributions (Inclusive Of Circular, Log-Normal Singular) With New Interpretations Ofsome Distributions (Ex. Pareto, Logistic Etc.)(Iii) Model Oriented Approach To The Generations Of Normal, Log-Normal, Cauchy, Exponential, Gamma And Other Waiting Distributions And Their Characterizations.(Iv) Techniques Of Truncated And Censored Distributions Vis-À-Vis Parametric, Non-Parametric, Bayesian And Sequential Inference Procedures, The Backgrounds Of Which Have Been Provided.(V) Inclusion Of Classical Topics As Pearsonian Curves, Gram-Charlier Series And Orthogonal Polynomials.Some Of The Distinguishing Features Are As Follows: * Introducing The Concept Of Correlation As A Milestone In The Development Of Regression Theory. * A Large Number Of Solved Examples And A Wide Collection Of Unsolved Problems With Occasional Hints. * A Geometrical Treatment Of Non-Central X2.
An Introduction To Statistical Learning
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Author : Gareth James
language : en
Publisher: Springer Nature
Release Date : 2023-06-30
An Introduction To Statistical Learning written by Gareth James and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-30 with Mathematics categories.
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Statistical Research Methods
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Author : Roy Sabo
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-10-22
Statistical Research Methods written by Roy Sabo and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-22 with Medical categories.
This textbook will help graduate students in non-statistics disciplines, advanced undergraduate researchers, and research faculty in the health sciences to learn, use and communicate results from many commonly used statistical methods. The material covered, and the manner in which it is presented, describe the entire data analysis process from hypothesis generation to writing the results in a manuscript. Chapters cover, among other topics: one and two-sample proportions, multi-category data, one and two-sample means, analysis of variance, and regression. Throughout the text, the authors explain statistical procedures and concepts using a non-statistical language. This accessible approach is complete with real-world examples and sample write-ups for the Methods and Results sections of scholarly papers. The text also allows for the concurrent use of the programming language R, which is an open-source program created, maintained and updated by the statistical community. R is freely available and easy to download.
Theoretical Statistics
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Author : Robert W. Keener
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-09-08
Theoretical Statistics written by Robert W. Keener and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-08 with Mathematics categories.
Intended as the text for a sequence of advanced courses, this book covers major topics in theoretical statistics in a concise and rigorous fashion. The discussion assumes a background in advanced calculus, linear algebra, probability, and some analysis and topology. Measure theory is used, but the notation and basic results needed are presented in an initial chapter on probability, so prior knowledge of these topics is not essential. The presentation is designed to expose students to as many of the central ideas and topics in the discipline as possible, balancing various approaches to inference as well as exact, numerical, and large sample methods. Moving beyond more standard material, the book includes chapters introducing bootstrap methods, nonparametric regression, equivariant estimation, empirical Bayes, and sequential design and analysis. The book has a rich collection of exercises. Several of them illustrate how the theory developed in the book may be used in various applications. Solutions to many of the exercises are included in an appendix.
Modern Statistical Methods For Health Research
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Author : Yichuan Zhao
language : en
Publisher: Springer
Release Date : 2022-10-15
Modern Statistical Methods For Health Research written by Yichuan Zhao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-15 with Medical categories.
This book brings together the voices of leading experts in the frontiers of biostatistics, biomedicine, and the health sciences to discuss the statistical procedures, useful methods, and novel applications in biostatistics research. It also includes discussions of potential future directions of biomedicine and new statistical developments for health research, with the intent of stimulating research and fostering the interactions of scholars across health research related disciplines. Topics covered include: Health data analysis and applications to EHR data Clinical trials, FDR, and applications in health science Big network analytics and its applications in GWAS Survival analysis and functional data analysis Graphical modelling in genomic studies The book will be valuable to data scientists and statisticians who are working in biomedicine and health, other practitioners in the health sciences, and graduate students and researchers in biostatistics and health.
All Of Statistics
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Author : Larry Wasserman
language : en
Publisher: Springer Science & Business Media
Release Date : 2004-09-17
All Of Statistics written by Larry Wasserman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-09-17 with Computers categories.
This book is for people who want to learn probability and statistics quickly. It brings together many of the main ideas in modern statistics in one place. The book is suitable for students and researchers in statistics, computer science, data mining and machine learning. This book covers a much wider range of topics than a typical introductory text on mathematical statistics. It includes modern topics like nonparametric curve estimation, bootstrapping and classification, topics that are usually relegated to follow-up courses. The reader is assumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. The text can be used at the advanced undergraduate and graduate level. Larry Wasserman is Professor of Statistics at Carnegie Mellon University. He is also a member of the Center for Automated Learning and Discovery in the School of Computer Science. His research areas include nonparametric inference, asymptotic theory, causality, and applications to astrophysics, bioinformatics, and genetics. He is the 1999 winner of the Committee of Presidents of Statistical Societies Presidents' Award and the 2002 winner of the Centre de recherches mathematiques de Montreal–Statistical Society of Canada Prize in Statistics. He is Associate Editor of The Journal of the American Statistical Association and The Annals of Statistics. He is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics.
Modern Statistical Methods For Spatial And Multivariate Data
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Author : Norou Diawara
language : en
Publisher: Springer
Release Date : 2019-07-11
Modern Statistical Methods For Spatial And Multivariate Data written by Norou Diawara and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-11 with Mathematics categories.
This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques. Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important resource on the latest developments in the field. In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration.
Statistical Methods Of Analysis
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Author : Chin Long Chiang
language : en
Publisher: World Scientific Publishing Company
Release Date : 2003-10-01
Statistical Methods Of Analysis written by Chin Long Chiang and has been published by World Scientific Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-10-01 with Mathematics categories.
This textbook systematically presents fundamental methods of statistical analysis: from probability and statistical distributions, through basic concepts of statistical inference, to a collection of methods of analysis useful for scientific research. It is rich in tables, diagrams, and examples, in addition to theoretical justification of the methods of analysis introduced. Each chapter has a section entitled “Exercises and Problems” to accompany the text. There are altogether about 300 exercises and problems, answers to the selected problems are given. A section entitled “Proof of the Results in This Chapter” in each chapter provides interested readers with material for further study.
Introduction To Statistics And Data Analysis
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Author : Christian Heumann
language : en
Publisher: Springer Nature
Release Date : 2023-01-30
Introduction To Statistics And Data Analysis written by Christian Heumann and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-30 with Mathematics categories.
Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference. The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications.
Statistical Methods For Climate Scientists
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Author : Timothy DelSole
language : en
Publisher: Cambridge University Press
Release Date : 2022-02-24
Statistical Methods For Climate Scientists written by Timothy DelSole and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-24 with Mathematics categories.
An accessible introduction to statistical methods for students in the climate sciences.