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Applied Statistics: Examining Global Economic and Social Problems, Allen Webster


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Автор: Allen Webster
Название:  Applied Statistics: Examining Global Economic and Social Problems
ISBN: 9781516535644
Издательство: Mare Nostrum (Eurospan)
Классификация:


ISBN-10: 1516535642
Обложка/Формат: Paperback
Страницы: 964
Вес: 2.18 кг.
Дата издания: 30.07.2018
Язык: English
Размер: 280 x 216 x 48
Читательская аудитория: Professional & vocational
Ключевые слова: Social research & statistics,Probability & statistics
Подзаголовок: Examining global economic and social problems
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Поставляется из: Англии
Описание: Applied Statistics: Examining Global Economic and Social Problems introduces students to the complex and relevant social, economic, and political problems that we face today through the use and application of foundational concepts in statistics. The text uses live data to show students the nature of and solutions to global issues such as income inequality, consumer and student debt, government deficits, corporate crime, and many other common dilemmas, illustrating the applied nature of statistics in a meaningful and concrete way. Over the course of 13 chapters, the book addresses topics including statistical analysis, graphs, computer applications, numerical measures, probability, and probability distribution. Students learn about sampling means and techniques, confidence intervals, hypothesis tests, the meaning of two populations, and simple regression and correlation analysis. Each chapter contains problems and exercises to help students better understand the role of statistics within the context of global challenges. Applied Statistics is well-suited for undergraduate and graduate business statistic courses, as well as social science courses with emphasis in statistical data.
Дополнительное описание: Probability and statistics|Social research and statistics


Stochastic Processes

Автор: Gallager
Название: Stochastic Processes
ISBN: 1107039754 ISBN-13(EAN): 9781107039759
Издательство: Cambridge Academ
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Цена: 74970.00 T
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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.

An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems

Автор: Luis Tenorio
Название: An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems
ISBN: 1611974917 ISBN-13(EAN): 9781611974911
Издательство: Mare Nostrum (Eurospan)
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Цена: 61870.00 T
Наличие на складе: Невозможна поставка.
Описание: Inverse problems are found in many applications, such as medical imaging, engineering, astronomy, and geophysics, among others. To solve an inverse problem is to recover an object from noisy, usually indirect observations. Solutions to inverse problems are subject to many potential sources of error introduced by approximate mathematical models, regularization methods, numerical approximations for efficient computations, noisy data, and limitations in the number of observations; thus it is important to include an assessment of the uncertainties as part of the solution. Such assessment is interdisciplinary by nature, as it requires, in addition to knowledge of the particular application, methods from applied mathematics, probability, and statistics.This book bridges applied mathematics and statistics by providing a basic introduction to probability and statistics for uncertainty quantification in the context of inverse problems, as well as an introduction to statistical regularization of inverse problems. The author covers basic statistical inference, introduces the framework of ill-posed inverse problems, and explains statistical questions that arise in their applications.An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems includes:many examples that explain techniques which are useful to address general problems arising in uncertainty quantification; Bayesian and non-Bayesian statistical methods and discussions of their complementary roles; and analysis of a real data set to illustrate the methodology covered throughout the book.Audience: This book is intended for senior undergraduates and beginning graduate students in mathematics, engineering and physical sciences. The material spans from undergraduate statistics and probability to data analysis for inverse problems and probability distributions on infinite-dimensional spaces. It is also intended for researchers working on inverse problems and uncertainty quantification in geophysics, astrophysics, physics, and engineering. Because the statistical and probability methods covered have applications beyond inverse problems, the book may also be of interest to those people working in data science or in other applications of uncertainty quantification.

Computational Uncertainty Quantification for Inverse Problems

Автор: Johnathan M. Bardsley
Название: Computational Uncertainty Quantification for Inverse Problems
ISBN: 1611975379 ISBN-13(EAN): 9781611975376
Издательство: Mare Nostrum (Eurospan)
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Цена: 53090.00 T
Наличие на складе: Невозможна поставка.
Описание: This book is an introduction to both computational inverse problems and uncertainty quantification (UQ) for inverse problems. The book also presents more advanced material on Bayesian methods and UQ, including Markov chain Monte Carlo sampling methods for UQ in inverse problems. Each chapter contains MATLAB® code that implements the algorithms and generates the figures, as well as a large number of exercises accessible to both graduate students and researchers. Computational Uncertainty Quantification for Inverse Problems is intended for graduate students, researchers, and applied scientists. It is appropriate for courses on computational inverse problems, Bayesian methods for inverse problems, and UQ methods for inverse problems.

Автор: Dirk Damsma
Название: How Language Informs Mathematics: Bridging Hegelian Dialectics and Marxian Models
ISBN: 900433730X ISBN-13(EAN): 9789004337305
Издательство: Brill
Цена: 164700.00 T
Наличие на складе: Невозможна поставка.
Описание: In How Language Informs Mathematics Dirk Damsma shows how Hegel’s and Marx’s systematic dialectical analysis of mathematical and economic language helps us understand the structure and nature of mathematical and capitalist systems. More importantly, Damsma shows how knowledge of the latter can inform model assumptions and help improve models. His book provides a blueprint for an approach to economic model building that does away with arbitrarily chosen assumptions and is sensitive to the institutional structures of capitalism. In light of the failure of mainstream economics to understand systemic failures like the financial crisis and given the arbitrary character of most assumptions in mainstream models, such an approach is desperately needed.

Economic Survey of Latin America and the Caribbean 2019: The New Global Financial Context - Effects and Transmission Mechanisms in the Region

Название: Economic Survey of Latin America and the Caribbean 2019: The New Global Financial Context - Effects and Transmission Mechanisms in the Region
ISBN: 9211220203 ISBN-13(EAN): 9789211220209
Издательство: Mare Nostrum (Eurospan)
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Цена: 97950.00 T
Наличие на складе: Нет в наличии.
Описание: Outlines the region`s economic performance in 2018 and analyses trends in the early months of 2019, as well as the outlook for the rest of the year. Coverage includes the factors that have influenced the region`s economic performance, the characteristics of growth, prices and the labour market, and macroeconomic policy challenges.

Fundamentals of Nonparametric Bayesian Inference

Автор: Ghosal, Subhashis.
Название: Fundamentals of Nonparametric Bayesian Inference
ISBN: 0521878268 ISBN-13(EAN): 9780521878265
Издательство: Cambridge Academ
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Цена: 86590.00 T
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Описание: Written by top researchers, this self-contained text is the authoritative account of Bayesian nonparametrics, a nearly universal framework for inference in statistics and machine learning, with practical use in all areas of science, including economics and biostatistics. Appendices with prerequisites and numerous exercises support its use for graduate courses.

Financial Econometrics: Models and Methods

Автор: Linton Oliver
Название: Financial Econometrics: Models and Methods
ISBN: 1316630331 ISBN-13(EAN): 9781316630334
Издательство: Cambridge Academ
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Цена: 54910.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This thorough exploration of the models and methods of financial econometrics is written by one of the world`s leading financial econometricians. The up-to-date content covers developments in econometrics and finance over the last twenty years while ensuring a solid grounding in the fundamental principles of the subject.

Fat chance :

Автор: Gross, Benedict H.,
Название: Fat chance :
ISBN: 1108728189 ISBN-13(EAN): 9781108728188
Издательство: Cambridge Academ
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Цена: 25350.00 T
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Описание: Designed for the intellectually curious, this book provides a solid foundation in basic probability theory in a charming style, without technical jargon. This text will immerse the reader in a mathematical view of the world, and teach them techniques to solve real-world problems both inside and outside the casino.

Mathematical Statistics for Applied Econometrics

Автор: Moss
Название: Mathematical Statistics for Applied Econometrics
ISBN: 1466594098 ISBN-13(EAN): 9781466594098
Издательство: Taylor&Francis
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Цена: 112290.00 T
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Описание:

An Introductory Econometrics Text

Mathematical Statistics for Applied Econometrics covers the basics of statistical inference in support of a subsequent course on classical econometrics. The book shows students how mathematical statistics concepts form the basis of econometric formulations. It also helps them think about statistics as more than a toolbox of techniques.

Uses Computer Systems to Simplify Computation

The text explores the unifying themes involved in quantifying sample information to make inferences. After developing the necessary probability theory, it presents the concepts of estimation, such as convergence, point estimators, confidence intervals, and hypothesis tests. The text then shifts from a general development of mathematical statistics to focus on applications particularly popular in economics. It delves into matrix analysis, linear models, and nonlinear econometric techniques.

Students Understand the Reasons for the Results

Avoiding a cookbook approach to econometrics, this textbook develops students' theoretical understanding of statistical tools and econometric applications. It provides them with the foundation for further econometric studies.


Income Distribution Dynamics of Economic Systems: An Econophysical Approach

Автор: Marcelo Byrro Ribeiro
Название: Income Distribution Dynamics of Economic Systems: An Econophysical Approach
ISBN: 1107092531 ISBN-13(EAN): 9781107092532
Издательство: Cambridge Academ
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Цена: 77090.00 T
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Описание: Econophysics has been used to study a range of economic and financial systems. This book uses the econophysical perspective to focus on the income distributive dynamics of economic systems. It will be of interest to physicists interested in economic problems, economists who deal with inequality issues, statisticians and applied mathematicians.

Computer Age Statistical Inference

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
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Цена: 60190.00 T
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Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

Advances in Economics and Econometrics vol I

Автор: Honore Bo
Название: Advances in Economics and Econometrics vol I
ISBN: 1108400000 ISBN-13(EAN): 9781108400008
Издательство: Cambridge Academ
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Цена: 63350.00 T
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Описание: This first volume includes papers presented at the Eleventh World Congress of the Econometric Society, addressing topics such as dynamic mechanism design, agency problems, and networks.


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