Core Statistics

Author: Simon Wood

Publisher: Cambridge University Press

ISBN: 1107071054

Category: Business & Economics

Page: 258

View: 5203

Core Statistics is a compact starter course on the theory, models, and computational tools needed to make informed use of powerful statistical methods.

Basic Concepts in Computational Physics

Author: Benjamin A. Stickler,Ewald Schachinger

Publisher: Springer

ISBN: 3319272659

Category: Science

Page: 409

View: 339

This new edition is a concise introduction to the basic methods of computational physics. Readers will discover the benefits of numerical methods for solving complex mathematical problems and for the direct simulation of physical processes. The book is divided into two main parts: Deterministic methods and stochastic methods in computational physics. Based on concrete problems, the first part discusses numerical differentiation and integration, as well as the treatment of ordinary differential equations. This is extended by a brief introduction to the numerics of partial differential equations. The second part deals with the generation of random numbers, summarizes the basics of stochastics, and subsequently introduces Monte-Carlo (MC) methods. Specific emphasis is on MARKOV chain MC algorithms. The final two chapters discuss data analysis and stochastic optimization. All this is again motivated and augmented by applications from physics. In addition, the book offers a number of appendices to provide the reader with information on topics not discussed in the main text. Numerous problems with worked-out solutions, chapter introductions and summaries, together with a clear and application-oriented style support the reader. Ready to use C++ codes are provided online.

A Course in Mathematical Statistics and Large Sample Theory

Author: Rabi Bhattacharya,Lizhen Lin,Victor Patrangenaru

Publisher: Springer

ISBN: 1493940325

Category: Mathematics

Page: 389

View: 7096

This graduate-level textbook is primarily aimed at graduate students of statistics, mathematics, science, and engineering who have had an undergraduate course in statistics, an upper division course in analysis, and some acquaintance with measure theoretic probability. It provides a rigorous presentation of the core of mathematical statistics. Part I of this book constitutes a one-semester course on basic parametric mathematical statistics. Part II deals with the large sample theory of statistics - parametric and nonparametric, and its contents may be covered in one semester as well. Part III provides brief accounts of a number of topics of current interest for practitioners and other disciplines whose work involves statistical methods.

Theoretical Statistics

Topics for a Core Course

Author: Robert W. Keener

Publisher: Springer Science & Business Media

ISBN: 9780387938394

Category: Mathematics

Page: 538

View: 1016

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.

Computational Bayesian Statistics

Author: M. Antónia Amaral Turkman,Carlos Daniel Paulino,Peter Müller

Publisher: Cambridge University Press

ISBN: 1108481035

Category: Business & Economics

Page: 275

View: 8365

This integrated introduction to fundamentals, computation, and software is your key to understanding and using advanced Bayesian methods.

Theory and Methods of Statistics

Author: P.K. Bhattacharya,Prabir Burman

Publisher: Academic Press

ISBN: 0128041234

Category: Mathematics

Page: 544

View: 1924

Theory and Methods of Statistics covers essential topics for advanced graduate students and professional research statisticians. This comprehensive resource covers many important areas in one manageable volume, including core subjects such as probability theory, mathematical statistics, and linear models, and various special topics, including nonparametrics, curve estimation, multivariate analysis, time series, and resampling. The book presents subjects such as "maximum likelihood and sufficiency," and is written with an intuitive, heuristic approach to build reader comprehension. It also includes many probability inequalities that are not only useful in the context of this text, but also as a resource for investigating convergence of statistical procedures. Codifies foundational information in many core areas of statistics into a comprehensive and definitive resource Serves as an excellent text for select master’s and PhD programs, as well as a professional reference Integrates numerous examples to illustrate advanced concepts Includes many probability inequalities useful for investigating convergence of statistical procedures

Statistics and Scientific Method

An Introduction for Students and Researchers

Author: Peter J. Diggle,Amanda G. Chetwynd

Publisher: Oxford University Press

ISBN: 0199543186

Category: Mathematics

Page: 172

View: 3822

An antidote to technique-orientated approaches, this text avoids the recipe-book style, giving the reader a clear understanding of how core statistical ideas of experimental design, modelling, and data analysis are integral to the scientific method. No prior knowledge of statistics is required and a range of scientific disciplines are covered.

Bayesian Core: A Practical Approach to Computational Bayesian Statistics

Author: Jean-Michel Marin,Christian Robert

Publisher: Springer Science & Business Media

ISBN: 0387389792

Category: Computers

Page: 255

View: 5473

This Bayesian modeling book is intended for practitioners and applied statisticians looking for a self-contained entry to computational Bayesian statistics. Focusing on standard statistical models, it provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical justifications.

Probability, Statistics and Econometrics

Author: Oliver Linton

Publisher: Academic Press

ISBN: 0128104961

Category: Business & Economics

Page: 388

View: 5420

Probability, Statistics and Econometrics provides a concise, yet rigorous, treatment of the field that is suitable for graduate students studying econometrics, very advanced undergraduate students, and researchers seeking to extend their knowledge of the trinity of fields that use quantitative data in economic decision-making. The book covers much of the groundwork for probability and inference before proceeding to core topics in econometrics. Authored by one of the leading econometricians in the field, it is a unique and valuable addition to the current repertoire of econometrics textbooks and reference books. Synthesizes three substantial areas of research, ensuring success in a subject matter than can be challenging to newcomers Focused and modern coverage that provides relevant examples from economics and finance Contains some modern frontier material, including bootstrap and lasso methods not treated in similar-level books Collects the necessary material for first semester Economics PhD students into a single text

Statistik-Workshop für Programmierer

Author: Allen B. Downey

Publisher: O'Reilly Germany

ISBN: 3868993436

Category: Computers

Page: 160

View: 9814

Wenn Sie programmieren können, beherrschen Sie bereits Techniken, um aus Daten Wissen zu extrahieren. Diese kompakte Einführung in die Statistik zeigt Ihnen, wie Sie rechnergestützt, anstatt auf mathematischem Weg Datenanalysen mit Python durchführen können. Praktischer Programmier-Workshop statt grauer Theorie: Das Buch führt Sie anhand eines durchgängigen Fallbeispiels durch eine vollständige Datenanalyse -- von der Datensammlung über die Berechnung statistischer Kennwerte und Identifikation von Mustern bis hin zum Testen statistischer Hypothesen. Gleichzeitig werden Sie mit statistischen Verteilungen, den Regeln der Wahrscheinlichkeitsrechnung, Visualisierungsmöglichkeiten und vielen anderen Arbeitstechniken und Konzepten vertraut gemacht. Statistik-Konzepte zum Ausprobieren: Entwickeln Sie über das Schreiben und Testen von Code ein Verständnis für die Grundlagen von Wahrscheinlichkeitsrechnung und Statistik: Überprüfen Sie das Verhalten statistischer Merkmale durch Zufallsexperimente, zum Beispiel indem Sie Stichproben aus unterschiedlichen Verteilungen ziehen. Nutzen Sie Simulationen, um Konzepte zu verstehen, die auf mathematischem Weg nur schwer zugänglich sind. Lernen Sie etwas über Themen, die in Einführungen üblicherweise nicht vermittelt werden, beispielsweise über die Bayessche Schätzung. Nutzen Sie Python zur Bereinigung und Aufbereitung von Rohdaten aus nahezu beliebigen Quellen. Beantworten Sie mit den Mitteln der Inferenzstatistik Fragestellungen zu realen Daten.

Introduction to Malliavin Calculus

Author: David Nualart,Eulalia Nualart

Publisher: Cambridge University Press

ISBN: 1107039126

Category: Business & Economics

Page: 246

View: 4667

This textbook offers a compact introductory course on Malliavin calculus, an active and powerful area of research. It covers recent applications, including density formulas, regularity of probability laws, central and non-central limit theorems for Gaussian functionals, convergence of densities and non-central limit theorems for the local time of Brownian motion. The book also includes a self-contained presentation of Brownian motion and stochastic calculus, as well as Lvy processes and stochastic calculus for jump processes. Accessible to non-experts, the book can be used by graduate students and researchers to develop their mastery of the core techniques necessary for further study.

Wahrscheinlichkeitstheorie und Stochastische Prozesse

Author: Michael Mürmann

Publisher: Springer-Verlag

ISBN: 364238160X

Category: Mathematics

Page: 428

View: 9484

Dieses Lehrbuch beschäftigt sich mit den zentralen Gebieten einer maßtheoretisch orientierten Wahrscheinlichkeitstheorie im Umfang einer zweisemestrigen Vorlesung. Nach den Grundlagen werden Grenzwertsätze und schwache Konvergenz behandelt. Es folgt die Darstellung und Betrachtung der stochastischen Abhängigkeit durch die bedingte Erwartung, die mit der Radon-Nikodym-Ableitung realisiert wird. Sie wird angewandt auf die Theorie der stochastischen Prozesse, die nach der allgemeinen Konstruktion aus der Untersuchung von Martingalen und Markov-Prozessen besteht. Neu in einem Lehrbuch über allgemeine Wahrscheinlichkeitstheorie ist eine Einführung in die stochastische Analysis von Semimartingalen auf der Grundlage einer geeigneten Stetigkeitsbedingung mit Anwendungen auf die Theorie der Finanzmärkte. Das Buch enthält zahlreiche Übungen, teilweise mit Lösungen. Neben der Theorie vertiefen Anmerkungen, besonders zu mathematischen Modellen für Phänomene der Realität, das Verständnis.​

Statistical Design for Research

Author: Leslie Kish

Publisher: John Wiley & Sons

ISBN: 9780471691204

Category: Mathematics

Page: 267

View: 6999

Addresses basic aspects of research design which are central and common to many related fields in the social sciences, in the health sciences, in education, and in market research. Presents a unified approach to a common core of problems of statistical design that exists in all these fields, along with basic similarities in practical solutions.

Handbook of Statistics

Computational Statistics with R

Author: N.A

Publisher: Elsevier

ISBN: 044463441X

Category: Mathematics

Page: 412

View: 1679

R is open source statistical computing software. Since the R core group was formed in 1997, R has been extended by a very large number of packages with extensive documentation along with examples freely available on the internet. It offers a large number of statistical and numerical methods and graphical tools and visualization of extraordinarily high quality. R was recently ranked in 14th place by the Transparent Language Popularity Index and 6th as a scripting language, after PHP, Python, and Perl. The book is designed so that it can be used right away by novices while appealing to experienced users as well. Each article begins with a data example that can be downloaded directly from the R website. Data analysis questions are articulated following the presentation of the data. The necessary R commands are spelled out and executed and the output is presented and discussed. Other examples of data sets with a different flavor and different set of commands but following the theme of the article are presented as well. Each chapter predents a hands-on-experience. R has superb graphical outlays and the book brings out the essentials in this arena. The end user can benefit immensely by applying the graphics to enhance research findings. The core statistical methodologies such as regression, survival analysis, and discrete data are all covered. Addresses data examples that can be downloaded directly from the R website No other source is needed to gain practical experience Focus on the essentials in graphical outlays

The New Walford

Guide to Reference Resources

Author: Albert John Walford

Publisher: New Walford's Guide to Referen

ISBN: 9781856044950

Category: Language Arts & Disciplines

Page: 827

View: 6641

First published in 1959, Walford''s guide to reference material achieved international recognition as a leading bibliographic tool across all subject areas. But, in the 1990s, the web transformed the information universe; and so we have now transformed Walford. The New Walford (TNW) Volume 1: Science, Technology and Medicine is the first volume of a radically different guide. Published over 3 years, TNW will form the most substantial work of its kind in the English language. This book provides a pathway through the huge quantity of information now accessible via the web. The types of material cited have been greatly widened to reflect the revolution brought about by the use of networked information; but we have made sure that print resources are not ignored where these are still valuable. If you are approaching a subject for the first time, TNW will get you on your way, guiding you to the best starting points for your query. For the information professional, TNW''s new way of categorizing resources reflects the fundamental changes that have taken place in the scientific, business, political and social information landscapes. Who is it for This new reference book will be valuable for professionals worldwide who need to suggest resources to people who are relatively unfamiliar with the nuances of a topic and who need to know where to start. The focus is on resources that are most likely to be found and used within public, government, education or business information services. If you are an LIS professional responsible for developing and revising a reference collection, new to reference work, staffing an enquiry desk, a research worker or student, you''ll welcome publication of this new work - it''s your paper portal to the world of reference resources. Subject coverage mathematics physics & astronomy earth sciences chemistry biological sciences agriculture, forestry, fisheries & food pre-clinical sciences; clinical medicine health natural resources & energy engineering information & communication technology. Subject fields include astrophysics & cosmology biodiversity & conservation genetics, genomics & bioinformatics infectious diseases information system security meteorology & climatology microengineering & nanotechnology palaeontology soil science sports & exercise medicine. Editor-in-Chief Dr Ray Lester held posts in Unilever and a number of university libraries before becoming Director of Information Services at the London Business School and then the Head of Library and Information Services at The Natural History Museum. Subject specialists Catherine Carr, Cranfield University Jim Corlett, Nottingham Trent University Joanne Dunham, University of Leicester Helen Hathaway, University of Reading Dr Jonathan Jeffery, Leiden University Gareth Johnson, University of York Nazma Masud, Royal Society of Chemistry Roger Mills, University of Oxford Lorna Mitchell, Queen Mary, University of London Dr David Newton, The British Library Linda Norbury, University of Birmingham Bob Parry, University of Reading Alison Sutton, University of Reading Elizabeth Tilley, University of Cambridge Dr Barry White, University of Manchester Fenella Whittaker, The Institution of Mechanical Engineers. 010

Basic Concepts in Statistics and Epidemiology

Author: Theodore Harney MacDonald

Publisher: Radcliffe Publishing

ISBN: 9781846191244

Category: Medical

Page: 214

View: 7434

This book is specifically designed to underpin the concpts of statistics and epidemiolgy. It is practical and easy to use and is idea for people who can feel uncomfortable with mathematics.

Business Statistics Made Easy in SAS

Author: Gregory Lee

Publisher: SAS Institute

ISBN: 162960044X

Category: Computers

Page: 384

View: 7247

Learn or refresh core statistical methods for business with SAS® and approach real business analytics issues and techniques using a practical approach that avoids complex mathematics and instead employs easy-to-follow explanations. Business Statistics Made Easy in SAS® is designed as a user-friendly, practice-oriented, introductory text to teach businesspeople, students, and others core statistical concepts and applications. It begins with absolute core principles and takes you through an overview of statistics, data and data collection, an introduction to SAS®, and basic statistics (descriptive statistics and basic associational statistics). The book also provides an overview of statistical modeling, effect size, statistical significance and power testing, basics of linear regression, introduction to comparison of means, basics of chi-square tests for categories, extrapolating statistics to business outcomes, and some topical issues in statistics, such as big data, simulation, machine learning, and data warehousing. The book steers away from complex mathematical-based explanations, and it also avoids basing explanations on the traditional build-up of distributions, probability theory and the like, which tend to lose the practice-oriented reader. Instead, it teaches the core ideas of statistics through methods such as careful, intuitive written explanations, easy-to-follow diagrams, step-by-step technique implementation, and interesting metaphors. With no previous SAS experience necessary, Business Statistics Made Easy in SAS® is an ideal introduction for beginners. It is suitable for introductory undergraduate classes, postgraduate courses such as MBA refresher classes, and for the business practitioner. It is compatible with SAS® University Edition.

Introduction to Statistical Analysis of Laboratory Data

Author: Alfred Bartolucci,Karan P. Singh,Sejong Bae

Publisher: John Wiley & Sons

ISBN: 1118736834

Category: Mathematics

Page: 256

View: 2538

Introduction to Statistical Analysis of Laboratory Data presents a detailed discussion of important statistical concepts and methods of data presentation and analysis Provides detailed discussions on statistical applications including a comprehensive package of statistical tools that are specific to the laboratory experiment process Introduces terminology used in many applications such as the interpretation of assay design and validation as well as “fit for purpose” procedures including real world examples Includes a rigorous review of statistical quality control procedures in laboratory methodologies and influences on capabilities Presents methodologies used in the areas such as method comparison procedures, limit and bias detection, outlier analysis and detecting sources of variation Analysis of robustness and ruggedness including multivariate influences on response are introduced to account for controllable/uncontrollable laboratory conditions