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Applied Statistics, David Cox


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Цена: 12157.00р.
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Автор: David Cox
Название:  Applied Statistics
ISBN: 9780412284106
Издательство: Springer
Классификация:
ISBN-10: 0412284103
Обложка/Формат: Paperback
Страницы: 171
Вес: 0.27 кг.
Дата издания: 18.12.1986
Язык: English
Размер: 234 x 156 x 10
Основная тема: Mathematics
Подзаголовок: A Handbook of BMDP™ Analyses
Ссылка на Издательство: Link
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Поставляется из: Германии


Epidemiology:  Key to Public Health. 2 ed.

Автор: Krickeberg Klaus, Van Trong Pham, Thi My Hanh Pham
Название: Epidemiology: Key to Public Health. 2 ed.
ISBN: 3030163679 ISBN-13(EAN): 9783030163679
Издательство: Springer
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Цена: 13974.00 р.
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Описание: ?This unique textbook presents the field of modern epidemiology as a whole; it does not restrict itself to particular aspects. It stresses the fundamental ideas and their role in any situation of epidemiologic practice. Its structure is largely determined by didactic viewpoints.Epidemiology is the art of defining and investigating the influence of factors on the health of populations. Hence the book starts by sketching the role of epidemiology in public health. It then treats the epidemiology of many particular diseases; mathematical modelling of epidemics and immunity; health information systems; statistical methods and sample surveys; clinical epidemiology including clinical trials; nutritional, environmental, social, and genetic epidemiology; and the habitual tools of epidemiologic studies. The book also reexamines the basic difference between the epidemiology of infectious diseases and that of non-infectious ones.The organization of the topics by didactic aspects makes the book ideal for teaching. All examples and case studies are situated in a single country, namely Vietnam; this provides a particularly vivid picture of the role of epidemiology in shaping the health of a population. It can easily be adapted to other developing or transitioning countries.This volume is well suited for courses on epidemiology and public health at the upper undergraduate and graduate levels, while its specific examples make it appropriate for those who teach these fields in developing or emerging countries. New to this edition, in addition to minor revisions of almost all chapters:• Updated data about infectious and non-infectious diseases• An expanded discussion of genetic epidemiology• A new chapter, based on recent research of the authors, on how to build a coherent system of Public Health by using the insights provided by this volume.

Pattern Recognition and Machine Learning

Автор: Christopher M. Bishop
Название: Pattern Recognition and Machine Learning
ISBN: 1493938436 ISBN-13(EAN): 9781493938438
Издательство: Springer
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Цена: 10480.00 р.
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Описание: Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

The Elements of Statistical Learning

Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman
Название: The Elements of Statistical Learning
ISBN: 0387848576 ISBN-13(EAN): 9780387848570
Издательство: Springer
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Цена: 10480.00 р.
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Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.

Introduction to statistical learning

Автор: James, Gareth Witten, Daniela Hastie, Trevor Tibsh
Название: Introduction to statistical learning
ISBN: 1071614177 ISBN-13(EAN): 9781071614174
Издательство: Springer
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Цена: 8384.00 р.
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Описание: 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 to marketing to 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. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers.

An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naive Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.

Mathematics for Machine Learning

Автор: Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong
Название: Mathematics for Machine Learning
ISBN: 110845514X ISBN-13(EAN): 9781108455145
Издательство: Cambridge Academ
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Цена: 6334.00 р.
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Описание: This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.

Stochastic Processes

Автор: Gallager
Название: Stochastic Processes
ISBN: 1107039754 ISBN-13(EAN): 9781107039759
Издательство: Cambridge Academ
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Цена: 11246.00 р.
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Описание: This definitive textbook provides a solid introduction to stochastic processes, covering both theory and applications. It is written by one of the world`s leading information theorists, evolving over twenty years of graduate classroom teaching, and is accompanied by over 300 exercises, with online solutions for instructors.

Statistical Rethinking

Автор: McElreath, Richard
Название: Statistical Rethinking
ISBN: 036713991X ISBN-13(EAN): 9780367139919
Издательство: Taylor&Francis
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Цена: 12554.00 р.
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Описание: Statistical Rethinking: A Bayesian Course with Examples in R and Stan, Second Edition builds knowledge/confidence in statistical modeling. Pushes readers to perform step-by-step calculations (usually automated.) Unique, computational approach.

Applied statistics in business and economics

Автор: Doane
Название: Applied statistics in business and economics
ISBN: 0071108149 ISBN-13(EAN): 9780071108140
Издательство: McGraw-Hill
Цена: 4288.00 р.
Наличие на складе: Поставка под заказ.

Описание: This new text offers an Excel focused approach to using statistics in business. All statistical concepts are illustrated with applied examples immediately upon introduction. Modern computing tools and applications are introduced, and the text maintains a strong focus on presenting statistical concepts as applied in business --as opposed to providing programming methods used to find a mathematical solution. Interpretation is heavily emphasized, enabling students to take full advantage of Excel to develop and drive problem-solving skills. Key Features Applied Statistics in Business and Economics covers all the basic topics in the standard Business Statistics course, both undergraduate and MBA, using real and realistic data sets and modern technology. Benefit : Students are studying statistics in the same 'environment' in which they can apply it. Visual Statistics, Learning Stats, and MegaStat are integrated within the text and included in the package. Benefit : Because the text package supports these more practical applications of statistics, instructors can -at their option, provide an enriched selection of topics, without math and theory holding the class back. Examples, minicases, exercies are almost completely from published research or real applications. Two key example data sets are a health care management data and a midwest bank collection on Automated teller machines. Benefit : The complete selection of examples and application mirror the current business environment. Students using this text are quite likely to be involved immediately in analysis very much like those used in the text. Exercises are included both at the end of sections, and at the ends of chapters. There are plenty of examples within the chapters, and virtually all of these are available in a technology form on CD. The exercises often include 'encouragement' of experimentation and alternative analysis. Benefit : Because the text and exercises are integrated with techology, this more realistic approach provides students with a better understanding of the applicability of statistics, and more experience in 'doing' analysis. Though nearly 800 pages in length- the text is concise in it's treatment. Much of the length is due to the high frequency of graphic illustrations and instructional screen shots of Excel and MegaStat for Excel. The text is decidedly non-mathematical- in both 'look and feel' and in substance. All but the simplest proofs and derivations are eliminated. Benefit : Students who are frightened or intimidated by mathematics or by technical notation in textbooks will not have that reaction to this text. The text integrates many real world data sets, including two large sets featuring health care management and banking/financial data. Benefit : Many texts use real world material from previously published popular press sources, and many use manufacturing, marketing, and economic data. Doane's use of data, particularly these two original data sets, more accurately matches the state of industry today, with health care and financial services assuming a much larger role. The treatment of confidence intervals and inference emphasizes proportions because they are more important in business applications. The text also thoroughly integrates p-value interpretations of all tests. Benefit : Students have a modern treatment, appropriate with the prevailing application of technology in statistics today. Hypothesis Testing chapters and all examples are presented following a consistent five step format Benefit : This approach helps students develop a logical and consistent approach in their analysis and understanding of inference. Author Biography David Doane David P. Doane is Professor of Quantitative Methods in Oakland University's Department of Decision and Information Sciences. He earned his Bachelor of Arts degree in mathematics and economics at the University of Kansas in 1966 and his PhD from Purdue University's Krannert Graduate School in 1969. His research and teaching interests include applied statistics, forecasting, and statistical education. He is co-recipient of three National Science Foundation grants to develop software to teach statistics and to create a computer classroom. He is a long-time member of the American Statistical Association and INFORMS, serving in 2002 as President of the Detroit ASA chapter, where he remains on the board. He has consulted with government, health care organizations, and local firms. He has published articles in many academic journals and is the author of LearningStats (McGraw-Hill, 2003, 2007) and co-author of Visual Statistics (McGraw-Hill, 1997, 2001). Lori Seward Lori E. Seward is a Senior Instructor of Systems in the Leeds School of Business at the University of Colorado'Boulder. She earned her Bachelor of Science and Master of Science degrees in Industrial Engineering at Virginia Tech in 1984 and 1985. After several years working as a reliability and quality engineer in the paper and automotive industries she earned her PhD from Virginia Tech in 1998. She joined the Leeds faculty in 1998. Her teaching interests include applied statistics, quality management, and supply chain management and she has taken the lead in using advanced technology tools for enhancing the classroom and learning experience in large lecture courses. She served as the Chair of the INFORMS Teachers'Workshop for the annual 2004 meeting. Her most recent article was published in The InternationalJournal of Flexible Manufacturing Systems (Kluwer Academic Publishers, 2004). Table of Contents 1: Overview of Statistics 2: Data Collection 3: Describing Data Visually 4: Descriptive Statistics 5: Probability 6: Discrete Distributions 7: Continuous Distributions 8: Sampling Distributions and Estimation 9: Hypothesis Testing: One Sample 10: Hypothesis Testing: Two Sample Tests 11: Analysis of Variance 12: Bivariate Regression 13: Multiple Regression 14: Time Series Analysis 15: Chi-Square Tests 16: Nonparametric Tests 17: Quality Management

Portfolio theory and arbitrage

Автор: Karatzas, Ioannis Kardaras, Constantinos
Название: Portfolio theory and arbitrage
ISBN: 1470465981 ISBN-13(EAN): 9781470465988
Издательство: Mare Nostrum (Eurospan)
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Цена: 10659.00 р.
Наличие на складе: Нет в наличии.

Описание: This book develops a mathematical theory for finance, based on a simple and intuitive absence-of-arbitrage principle. This posits that it should not be possible to fund a non-trivial liability, starting with initial capital arbitrarily near zero. The principle is easy-to-test in specific models, as it is described in terms of the underlying market characteristics; it is shown to be equivalent to the existence of the so-called ""Kelly"" or growth-optimal portfolio, of the log-optimal portfolio, and of appropriate local martingale deflators. The resulting theory is powerful enough to treat in great generality the fundamental questions of hedging, valuation, and portfolio optimization.The book contains a considerable amount of new research and results, as well as a significant number of exercises. It can be used as a basic text for graduate courses in Probability and Stochastic Analysis, and in Mathematical Finance. No prior familiarity with finance is required, but it is assumed that readers have a good working knowledge of real analysis, measure theory, and of basic probability theory. Familiarity with stochastic analysis is also assumed, as is integration with respect to continuous semimartingales.

An Intermediate Course in Probability

Автор: Allan Gut
Название: An Intermediate Course in Probability
ISBN: 1489984461 ISBN-13(EAN): 9781489984463
Издательство: Springer
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Цена: 7622.00 р.
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Описание: This book covers the basic results and methods in probability theory. This new edition offers updated content, 100 additional problems for solution, and a new chapter glimpsing further topics such as stable distributions, domains of attraction and martingales.

Introduction To Probability And Statistics For Engineers And Scientists

Автор: Ross, Sheldon M.
Название: Introduction To Probability And Statistics For Engineers And Scientists
ISBN: 0128243465 ISBN-13(EAN): 9780128243466
Издательство: Elsevier Science
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Цена: 16505.00 р.
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Описание: Letter Jam is a 2-6 player cooperative word game where players assist each other in composing meaningful words from letters around the table. The trick is holding the letter card so that it`s only visible to other players and not to you.At the start of the game, each player receives a set of face-down letter cards that can be arranged to form an existing word. The setup can be prepared by using a special card scanning app, or by players selecting words for each other. Each player then puts their first card in their stand facing the other players without looking at it, and the game begins.The game is played in turns. Each turn, players simultaneously search other players` letters to see what words they can spell out (telling the others the length of the word they can make up). The player who offers the longest word can then be chosen as the clue giver.The clue giver spells out their clue by putting numbered tokens in front of the other players. Number one goes to the player whose letter comes first in the clue, number two to the second letter etc. They can always use a wild card which can be any letter, but they cannot tell others which letter it represents.Each player with a numbered token (or tokens) in front of them then tries to figure out what their letter is. If they do, they place the card face down before revealing the next letter. At the end of the game, players can then rearrange the cards to try to form an existing word. All players then reveal their cards to see if they were successful or not. The more players who have an existing word in front of them, the bigger their common success.

The Analysis of Biological Data

Автор: Michael C. Whitlock, Dolph Schluter
Название: The Analysis of Biological Data
ISBN: 1319325343 ISBN-13(EAN): 9781319325343
Издательство: Macmillan Learning
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Цена: 13858.00 р.
Наличие на складе: Нет в наличии.

Описание: The evolution of a classicThe new 12th edition of Introduction to Genetic Analysis takes this cornerstone textbook to the next level.


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