Mathematica Laboratories for Mathematical Statistics

Mathematica Laboratories for Mathematical Statistics PDF

Author: Jenny A. Baglivo

Publisher: SIAM

Published: 2005-01-01

Total Pages: 273

ISBN-13: 0898718414

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Integrating computers into mathematical statistics courses allows students to simulate experiments and visualize their results, handle larger data sets, analyze data more quickly, and compare the results of classical methods of data analysis with those using alternative techniques. This text presents a concise introduction to the concepts of probability theory and mathematical statistics. The accompanying in-class and take-home computer laboratory activities reinforce the techniques introduced in the text and are accessible to students with little or no experience with Mathematica. These laboratory materials present applications in a variety of real-world settings, with data from epidemiology, environmental sciences, medicine, social sciences, physical sciences, manufacturing, engineering, marketing, and sports. Mathematica Laboratories for Mathematical Statistics: Emphasizing Simulation and Computer Intensive Methods includes parametric, nonparametric, permutation, bootstrap and diagnostic methods. Chapters on permutation and bootstrap techniques follow the formal inference chapters and precede the chapters on intermediate-level topics. Permutation and bootstrap methods are discussed side by side with classical methods in the later chapters.

Mathematica Laboratories for Mathematical Statistics with CD-ROM

Mathematica Laboratories for Mathematical Statistics with CD-ROM PDF

Author: Jenny A. Baglivo

Publisher: Society for Industrial and Applied Mathematics

Published: 2004-11-01

Total Pages: 184

ISBN-13: 9780898715668

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Integrating computers into mathematical statistics courses allows students to simulate experiments and visualize their results, handle larger data sets, analyze data more quickly, and compare the results of classical methods of data analysis with those using alternative techniques. This text presents a concise introduction to the concepts of probability theory and mathematical statistics. The accompanying in-class and take-home computer laboratory activities reinforce the techniques introduced in the text and are accessible to students with little or no experience with Mathematica. These laboratory materials present applications in a variety of real-world settings, with data from epidemiology, environmental sciences, medicine, social sciences, physical sciences, manufacturing, engineering, marketing, and sports. Included in the book are parametric, nonparametric, permutation, bootstrap and diagnostic methods. Permutation and bootstrap methods are discussed side by side with classical methods in the later chapters. Includes a CD-ROM with 238 laboratory problems written as Mathematica notebooks.

Statistics with Mathematica

Statistics with Mathematica PDF

Author: Martha L. Abell

Publisher: Academic Press

Published: 1999

Total Pages: 654

ISBN-13: 9780120415540

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Covers the use of Mathematica for applications ranging from descriptive statistics, through multiple regression and nonparametric methods; uses virtually all of Mathematica's built-in statistical commands, as well as those contained in various Mathematica packages; Additionally, the authors have written numerous procedures to extend Mathematica's capabilities, which are also included on the CD-ROM

Introduction to Probability with Mathematica

Introduction to Probability with Mathematica PDF

Author: Kevin J. Hastings

Publisher: CRC Press

Published: 2000-11-27

Total Pages: 398

ISBN-13: 9781584881094

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Newcomers to the world of probability face several potential stumbling blocks. They often struggle with key concepts-sample space, random variable, distribution, and expectation; they must regularly confront integration, infrequently mastered in calculus classes; and they must labor over lengthy, cumbersome calculations. Introduction to Probability with Mathematica is a groundbreaking text that uses a powerful computer algebra system as a pedagogical tool for learning and using probability. Its clever use of simulation to illustrate concepts and motivate important theorems gives it an important and unique place in the library of probability theory. The author smoothly integrates the technology with the traditional approach and subject matter, thereby augmenting rather than overpowering it. This book lives and breathes in the sense that not only can it be read and studied in an armchair, but each section also exists as a fully executable Mathematica® notebook on the CRC Web site. Students will find Introduction to Probability with Mathematica an engaging, accessible, yet challenging way to venture into the fascinating subject of probability.

Mathematica for Bioinformatics

Mathematica for Bioinformatics PDF

Author: George Mias

Publisher: Springer

Published: 2018-03-16

Total Pages: 384

ISBN-13: 3319723774

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This book offers a comprehensive introduction to using Mathematica and the Wolfram Language for Bioinformatics. The chapters build gradually from basic concepts and the introduction of the Wolfram Language and coding paradigms in Mathematica, to detailed worked examples derived from typical research applications using Wolfram Language code. The coding examples range from basic sequence analysis, accessing genomic databases, differential gene expression, and machine learning implementations to time series analysis of longitudinal omics experiments, multi-omics integration and building dynamic interactive bioinformatics tools using the Wolfram Language. The topics address the daily bioinformatics needs of a broad audience: experimental users looking to understand and visualize their data, beginner bioinformaticians acquiring coding expertise in providing biological research solutions, and practicing expert bioinformaticians working on omics who wish to expand their toolset to include the Wolfram Language.

Mathematical Statistics

Mathematical Statistics PDF

Author: A A Borokov

Publisher: Routledge

Published: 2019-01-22

Total Pages: 614

ISBN-13: 1351433091

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A wide-ranging, extensive overview of modern mathematical statistics, this work reflects the current state of the field while being succinct and easy to grasp. The mathematical presentation is coherent and rigorous throughout. The author presents classical results and methods that form the basis of modern statistics, and examines the foundations o

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