Topics In The Foundation Of Statistics

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Topics in the Foundation of Statistics

Author : B.C. van Fraassen
Publisher : Springer Science & Business Media
ISBN 13 : 9780792344056
Total Pages : 178 pages
Book Rating : 4.3/5 (44 download)

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Book Synopsis Topics in the Foundation of Statistics by : B.C. van Fraassen

Download or read book Topics in the Foundation of Statistics written by B.C. van Fraassen and published by Springer Science & Business Media. This book was released on 1997-02-28 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundational research focuses on the theory, but theories are to be related also to other theories, experiments, facts in their domains, data, and to their uses in applications, whether of prediction, control, or explanation. A theory is to be identified through its class of models, but not so narrowly as to disallow these roles. The language of science is to be studied separately, with special reference to the relations listed above, and to the consequent need for resources other than for theoretical description. Peculiar to the foundational level are questions of completeness (specifically in the representation of measurement), and of interpretation (a topic beset with confusions of truth and evidence, and with inappropriate metalinguistic abstraction).

Topics in the Foundation of Statistics

Author : B. C. Van Fraassen
Publisher :
ISBN 13 : 9789401588171
Total Pages : 172 pages
Book Rating : 4.5/5 (881 download)

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Book Synopsis Topics in the Foundation of Statistics by : B. C. Van Fraassen

Download or read book Topics in the Foundation of Statistics written by B. C. Van Fraassen and published by . This book was released on 2014-01-15 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Topics in the Foundation of Statistics

Author : B.C. van Fraassen
Publisher : Springer Science & Business Media
ISBN 13 : 9401588163
Total Pages : 161 pages
Book Rating : 4.4/5 (15 download)

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Book Synopsis Topics in the Foundation of Statistics by : B.C. van Fraassen

Download or read book Topics in the Foundation of Statistics written by B.C. van Fraassen and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundational research focuses on the theory, but theories are to be related also to other theories, experiments, facts in their domains, data, and to their uses in applications, whether of prediction, control, or explanation. A theory is to be identified through its class of models, but not so narrowly as to disallow these roles. The language of science is to be studied separately, with special reference to the relations listed above, and to the consequent need for resources other than for theoretical description. Peculiar to the foundational level are questions of completeness (specifically in the representation of measurement), and of interpretation (a topic beset with confusions of truth and evidence, and with inappropriate metalinguistic abstraction).

Foundations and Applications of Statistics

Author : Randall Pruim
Publisher : American Mathematical Soc.
ISBN 13 : 1470428482
Total Pages : 820 pages
Book Rating : 4.4/5 (74 download)

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Book Synopsis Foundations and Applications of Statistics by : Randall Pruim

Download or read book Foundations and Applications of Statistics written by Randall Pruim and published by American Mathematical Soc.. This book was released on 2018-04-04 with total page 820 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations and Applications of Statistics simultaneously emphasizes both the foundational and the computational aspects of modern statistics. Engaging and accessible, this book is useful to undergraduate students with a wide range of backgrounds and career goals. The exposition immediately begins with statistics, presenting concepts and results from probability along the way. Hypothesis testing is introduced very early, and the motivation for several probability distributions comes from p-value computations. Pruim develops the students' practical statistical reasoning through explicit examples and through numerical and graphical summaries of data that allow intuitive inferences before introducing the formal machinery. The topics have been selected to reflect the current practice in statistics, where computation is an indispensible tool. In this vein, the statistical computing environment R is used throughout the text and is integral to the exposition. Attention is paid to developing students' mathematical and computational skills as well as their statistical reasoning. Linear models, such as regression and ANOVA, are treated with explicit reference to the underlying linear algebra, which is motivated geometrically. Foundations and Applications of Statistics discusses both the mathematical theory underlying statistics and practical applications that make it a powerful tool across disciplines. The book contains ample material for a two-semester course in undergraduate probability and statistics. A one-semester course based on the book will cover hypothesis testing and confidence intervals for the most common situations. In the second edition, the R code has been updated throughout to take advantage of new R packages and to illustrate better coding style. New sections have been added covering bootstrap methods, multinomial and multivariate normal distributions, the delta method, numerical methods for Bayesian inference, and nonlinear least squares. Also, the use of matrix algebra has been expanded, but remains optional, providing instructors with more options regarding the amount of linear algebra required.

Foundations of Mathematics and Statistics

Author : Timothy C. Kearns
Publisher :
ISBN 13 : 9781546277484
Total Pages : 538 pages
Book Rating : 4.2/5 (774 download)

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Book Synopsis Foundations of Mathematics and Statistics by : Timothy C. Kearns

Download or read book Foundations of Mathematics and Statistics written by Timothy C. Kearns and published by . This book was released on 2019-01-26 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Mathematics and Statistics is a summary of the basic principles of math and statistics for students that are interested in pursuing studies in the mathematical sciences. The first goal is to provide a good foundation of knowledge and ability with the basics of mathematics. This includes logic, sets, number systems, algebra, geometry, trigonometry, and the calculus. Then the remainder of the book deals with the fundamental topics of applied and mathematical statistics, including probability, random variables, expected value, samples, distributions, hypothesis testing, confidence intervals, and an introduction to linear regression and correlation. The book can be used by all students that need a summary of math fundamentals, with a sound introduction to the basics of statistical thinking and methodology. Those that need a good familiarity with math and statistics would find this book a valuable supplemental reading, along with the fair amount of exercises that are included in order to reinforce the important ideas.

Foundations of Statistics for Data Scientists

Author : Alan Agresti
Publisher : CRC Press
ISBN 13 : 1000462919
Total Pages : 486 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Foundations of Statistics for Data Scientists by : Alan Agresti

Download or read book Foundations of Statistics for Data Scientists written by Alan Agresti and published by CRC Press. This book was released on 2021-11-22 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Statistics for Data Scientists: With R and Python is designed as a textbook for a one- or two-term introduction to mathematical statistics for students training to become data scientists. It is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modeling. The book assumes knowledge of basic calculus, so the presentation can focus on "why it works" as well as "how to do it." Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python. The book also introduces modern topics that do not normally appear in mathematical statistics texts but are highly relevant for data scientists, such as Bayesian inference, generalized linear models for non-normal responses (e.g., logistic regression and Poisson loglinear models), and regularized model fitting. The nearly 500 exercises are grouped into "Data Analysis and Applications" and "Methods and Concepts." Appendices introduce R and Python and contain solutions for odd-numbered exercises. The book's website has expanded R, Python, and Matlab appendices and all data sets from the examples and exercises.

Foundations of Statistics for Data Scientists

Author : ALAN. KATERI AGRESTI (MARIA.)
Publisher : CRC Press
ISBN 13 : 9780367748432
Total Pages : 488 pages
Book Rating : 4.7/5 (484 download)

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Book Synopsis Foundations of Statistics for Data Scientists by : ALAN. KATERI AGRESTI (MARIA.)

Download or read book Foundations of Statistics for Data Scientists written by ALAN. KATERI AGRESTI (MARIA.) and published by CRC Press. This book was released on 2024-09-15 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed as a textbook for a one or two-term introduction to mathematical statistics for students training to become data scientists, Foundations of Statistics for Data Scientists: With R and Python is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modelling. The book assumes knowledge of basic calculus, so the presentation can focus on 'why it works' as well as 'how to do it.' Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python. The book also introduces modern topics that do not normally appear in mathematical statistics texts but are highly relevant for data scientists, such as Bayesian inference, generalized linear models for non-normal responses (e.g., logistic regression and Poisson loglinear models), and regularized model fitting. The nearly 500 exercises are grouped into "Data Analysis and Applications" and "Methods and Concepts." Appendices introduce R and Python and contain solutions for odd-numbered exercises. The book's website has expanded R, Python, and Matlab appendices and all data sets from the examples and exercises. Alan Agresti, Distinguished Professor Emeritus at the University of Florida, is the author of seven books, including Categorical Data Analysis (Wiley) and Statistics: The Art and Science of Learning from Data (Pearson), and has presented short courses in 35 countries. His awards include an honorary doctorate from De Montfort University (UK) and the Statistician of the Year from the American Statistical Association (Chicago chapter). Maria Kateri, Professor of Statistics and Data Science at the RWTH Aachen University, authored the monograph Contingency Table Analysis: Methods and Implementation Using R (Birkhäuser/Springer) and a textbook on mathematics for economists (in German). She has a long-term experience in teaching statistics courses to students of Data Science, Mathematics, Statistics, Computer Science, and Business Administration and Engineering. "The main goal of this textbook is to present foundational statistical methods and theory that are relevant in the field of data science. The authors depart from the typical approaches taken by many conventional mathematical statistics textbooks by placing more emphasis on providing the students with intuitive and practical interpretations of those methods with the aid of R programming codes...I find its particular strength to be its intuitive presentation of statistical theory and methods without getting bogged down in mathematical details that are perhaps less useful to the practitioners" (Mintaek Lee, Boise State University) "The aspects of this manuscript that I find appealing: 1. The use of real data. 2. The use of R but with the option to use Python. 3. A good mix of theory and practice. 4. The text is well-written with good exercises. 5. The coverage of topics (e.g. Bayesian methods and clustering) that are not usually part of a course in statistics at the level of this book." (Jason M. Graham, University of Scranton)

Biostatistics

Author : Wayne W. Daniel
Publisher : Wiley
ISBN 13 : 1119282373
Total Pages : 720 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Biostatistics by : Wayne W. Daniel

Download or read book Biostatistics written by Wayne W. Daniel and published by Wiley. This book was released on 2018-11-13 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ability to analyze and interpret enormous amounts of data has become a prerequisite for success in allied healthcare and the health sciences. Now in its 11th edition, Biostatistics: A Foundation for Analysis in the Health Sciences continues to offer in-depth guidance toward biostatistical concepts, techniques, and practical applications in the modern healthcare setting. Comprehensive in scope yet detailed in coverage, this text helps students understand—and appropriately use—probability distributions, sampling distributions, estimation, hypothesis testing, variance analysis, regression, correlation analysis, and other statistical tools fundamental to the science and practice of medicine. Clearly-defined pedagogical tools help students stay up-to-date on new material, and an emphasis on statistical software allows faster, more accurate calculation while putting the focus on the underlying concepts rather than the math. Students develop highly relevant skills in inferential and differential statistical techniques, equipping them with the ability to organize, summarize, and interpret large bodies of data. Suitable for both graduate and advanced undergraduate coursework, this text retains the rigor required for use as a professional reference.

Statistical Foundations, Reasoning and Inference

Author : Göran Kauermann
Publisher : Springer Nature
ISBN 13 : 3030698270
Total Pages : 361 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Statistical Foundations, Reasoning and Inference by : Göran Kauermann

Download or read book Statistical Foundations, Reasoning and Inference written by Göran Kauermann and published by Springer Nature. This book was released on 2021-09-30 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science. The topics covered include likelihood-based inference, Bayesian statistics, regression, statistical tests and the quantification of uncertainty. Moreover, the book addresses statistical ideas that are useful in modern data analytics, including bootstrapping, modeling of multivariate distributions, missing data analysis, causality as well as principles of experimental design. The textbook includes sufficient material for a two-semester course and is intended for master’s students in data science, statistics and computer science with a rudimentary grasp of probability theory. It will also be useful for data science practitioners who want to strengthen their statistics skills.

All of Statistics

Author : Larry Wasserman
Publisher : Springer Science & Business Media
ISBN 13 : 0387217363
Total Pages : 446 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis All of Statistics by : Larry Wasserman

Download or read book All of Statistics written by Larry Wasserman and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.

Introductory Statistics

Author : Douglas S. Shafer
Publisher :
ISBN 13 : 9781453388945
Total Pages : 0 pages
Book Rating : 4.3/5 (889 download)

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Book Synopsis Introductory Statistics by : Douglas S. Shafer

Download or read book Introductory Statistics written by Douglas S. Shafer and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Statistical Foundations of Data Science

Author : Jianqing Fan
Publisher : CRC Press
ISBN 13 : 1466510854
Total Pages : 752 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Statistical Foundations of Data Science by : Jianqing Fan

Download or read book Statistical Foundations of Data Science written by Jianqing Fan and published by CRC Press. This book was released on 2020-09-21 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.

More Damned Lies and Statistics

Author : Joel Best
Publisher : Univ of California Press
ISBN 13 : 0520930029
Total Pages : 222 pages
Book Rating : 4.5/5 (29 download)

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Book Synopsis More Damned Lies and Statistics by : Joel Best

Download or read book More Damned Lies and Statistics written by Joel Best and published by Univ of California Press. This book was released on 2004-09-06 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this sequel to the acclaimed Damned Lies and Statistics, which the Boston Globe said "deserves a place next to the dictionary on every school, media, and home-office desk," Joel Best continues his straightforward, lively, and humorous account of how statistics are produced, used, and misused by everyone from researchers to journalists. Underlining the importance of critical thinking in all matters numerical, Best illustrates his points with examples of good and bad statistics about such contemporary concerns as school shootings, fatal hospital errors, bullying, teen suicides, deaths at the World Trade Center, college ratings, the risks of divorce, racial profiling, and fatalities caused by falling coconuts. More Damned Lies and Statistics encourages all of us to think in a more sophisticated and skeptical manner about how statistics are used to promote causes, create fear, and advance particular points of view. Best identifies different sorts of numbers that shape how we think about public issues: missing numbers are relevant but overlooked; confusing numbers bewilder when they should inform; scary numbers play to our fears about the present and the future; authoritative numbers demand respect they don’t deserve; magical numbers promise unrealistic, simple solutions to complex problems; and contentious numbers become the focus of data duels and stat wars. The author's use of pertinent, socially important examples documents the life-altering consequences of understanding or misunderstanding statistical information. He demystifies statistical measures by explaining in straightforward prose how decisions are made about what to count and what not to count, what assumptions get made, and which figures are brought to our attention. Best identifies different sorts of numbers that shape how we think about public issues. Entertaining, enlightening, and very timely, this book offers a basis for critical thinking about the numbers we encounter and a reminder that when it comes to the news, people count—in more ways than one.

Foundations of Statistical Natural Language Processing

Author : Christopher Manning
Publisher : MIT Press
ISBN 13 : 0262303795
Total Pages : 719 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Foundations of Statistical Natural Language Processing by : Christopher Manning

Download or read book Foundations of Statistical Natural Language Processing written by Christopher Manning and published by MIT Press. This book was released on 1999-05-28 with total page 719 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.

Foundations of Biostatistics

Author : M. Ataharul Islam
Publisher : Springer
ISBN 13 : 9811086273
Total Pages : 475 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Foundations of Biostatistics by : M. Ataharul Islam

Download or read book Foundations of Biostatistics written by M. Ataharul Islam and published by Springer. This book was released on 2018-06-15 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a comprehensive guide to essential techniques and methods in biostatistics, addressing the underlying concepts to aid in comprehension. The use of biostatistics techniques has increased manifold in the recent past, due to their suitability for applications in a wide range of problems in various fields. This book helps learners grasp the materials in detail, equipping them to use biostatistics techniques independently and confidently. The book starts with a summary of background materials, followed by methods and techniques. As such, with only minimum guidance from teachers, this book can provide materials for self-learning of biostatistics techniques with a deeper level of understanding. The first two chapters focus on fundamental concepts, sources of data, data types, organization of data, and descriptive statistics, followed by the basic probability concepts, distributions and sampling distributions needed in order to combine descriptive statistics with inferential techniques. Estimation and tests of hypotheses are illustrated in two separate chapters. Important measures of association, linear regression, analysis of variance and logistic regression, and proportional hazards models are then presented systematically, ensuring that the book covers the topics most essential to students and users of biostatistics in connection with a wide range of applications in various fields. The book has been carefully structured, and the content is presented in a sequence covering the essential background in a highly systematic manner, supporting the learning process by presenting theory and applications that complement one another.

Introductory Statistics 2e (hardcover, Full Color)

Author : Barbara Illowsky
Publisher :
ISBN 13 : 9781998295470
Total Pages : 0 pages
Book Rating : 4.2/5 (954 download)

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Book Synopsis Introductory Statistics 2e (hardcover, Full Color) by : Barbara Illowsky

Download or read book Introductory Statistics 2e (hardcover, Full Color) written by Barbara Illowsky and published by . This book was released on 2023-12-14 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Book Publication Date: Dec 13, 2023. Full color. Introductory Statistics 2e provides an engaging, practical, and thorough overview of the core concepts and skills taught in most one-semester statistics courses. The text focuses on diverse applications from a variety of fields and societal contexts, including business, healthcare, sciences, sociology, political science, computing, and several others. The material supports students with conceptual narratives, detailed step-by-step examples, and a wealth of illustrations, as well as collaborative exercises, technology integration problems, and statistics labs. The text assumes some knowledge of intermediate algebra, and includes thousands of problems and exercises that offer instructors and students ample opportunity to explore and reinforce useful statistical skills.

Statistical Foundations, Reasoning and Inference

Author : Göran Kauermann
Publisher :
ISBN 13 : 9783030698287
Total Pages : 0 pages
Book Rating : 4.6/5 (982 download)

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Book Synopsis Statistical Foundations, Reasoning and Inference by : Göran Kauermann

Download or read book Statistical Foundations, Reasoning and Inference written by Göran Kauermann and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science. The topics covered include likelihood-based inference, Bayesian statistics, regression, statistical tests and the quantification of uncertainty. Moreover, the book addresses statistical ideas that are useful in modern data analytics, including bootstrapping, modeling of multivariate distributions, missing data analysis, causality as well as principles of experimental design. The textbook includes sufficient material for a two-semester course and is intended for master's students in data science, statistics and computer science with a rudimentary grasp of probability theory. It will also be useful for data science practitioners who want to strengthen their statistics skills.