Topics In The Foundation Of Statistics
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Topics In The Foundation Of Statistics
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Author : B.C. van Fraassen
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Topics In The Foundation Of Statistics written by B.C. van Fraassen 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 2013-03-09 with Mathematics categories.
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
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Author : B.C. van Fraassen
language : en
Publisher: Springer Science & Business Media
Release Date : 1997-02-28
Topics In The Foundation Of Statistics written by B.C. van Fraassen 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 1997-02-28 with Mathematics categories.
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).
The Foundations Of Statistics A Simulation Based Approach
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Author : Shravan Vasishth
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-11-11
The Foundations Of Statistics A Simulation Based Approach written by Shravan Vasishth 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 2010-11-11 with Mathematics categories.
Statistics and hypothesis testing are routinely used in areas (such as linguistics) that are traditionally not mathematically intensive. In such fields, when faced with experimental data, many students and researchers tend to rely on commercial packages to carry out statistical data analysis, often without understanding the logic of the statistical tests they rely on. As a consequence, results are often misinterpreted, and users have difficulty in flexibly applying techniques relevant to their own research — they use whatever they happen to have learned. A simple solution is to teach the fundamental ideas of statistical hypothesis testing without using too much mathematics. This book provides a non-mathematical, simulation-based introduction to basic statistical concepts and encourages readers to try out the simulations themselves using the source code and data provided (the freely available programming language R is used throughout). Since the code presented in the text almost always requires the use of previously introduced programming constructs, diligent students also acquire basic programming abilities in R. The book is intended for advanced undergraduate and graduate students in any discipline, although the focus is on linguistics, psychology, and cognitive science. It is designed for self-instruction, but it can also be used as a textbook for a first course on statistics. Earlier versions of the book have been used in undergraduate and graduate courses in Europe and the US. ”Vasishth and Broe have written an attractive introduction to the foundations of statistics. It is concise, surprisingly comprehensive, self-contained and yet quite accessible. Highly recommended.” Harald Baayen, Professor of Linguistics, University of Alberta, Canada ”By using the text students not only learn to do the specific things outlined in the book, they also gain a skill set that empowers them to explore new areas that lie beyond the book’s coverage.” Colin Phillips, Professor of Linguistics, University of Maryland, USA
Topics In The Foundation Of Statistics
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Author : B. C. Van Fraassen
language : en
Publisher:
Release Date : 2014-01-15
Topics In The Foundation Of Statistics written by B. C. Van Fraassen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.
Statistical Foundations Reasoning And Inference
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Author : Göran Kauermann
language : en
Publisher: Springer Nature
Release Date : 2021-09-30
Statistical Foundations Reasoning And Inference written by Göran Kauermann and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-30 with Mathematics categories.
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.
Foundations Of Data Science
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Author : Avrim Blum
language : en
Publisher: Cambridge University Press
Release Date : 2020-01-23
Foundations Of Data Science written by Avrim Blum 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 2020-01-23 with Computers categories.
Covers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks.
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.
Openintro Statistics
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Author : David Diez
language : en
Publisher:
Release Date : 2015-07-02
Openintro Statistics written by David Diez and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-02 with categories.
The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.
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.