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

Mathematical Statistics and Data Analysis

Mathematical Statistics and Data Analysis PDF

Author: John A. Rice

Publisher: Duxbury Resource Center

Published: 1995

Total Pages: 680

ISBN-13:

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Re-examines the purpose of the math statistics course. The approach of the text, interweaving traditional topics with data analysis, reflects the use of the computer and is closely tied to the practice of statistics.

Mathematical Statistics With Applications

Mathematical Statistics With Applications PDF

Author: Asha Seth Kapadia

Publisher: CRC Press

Published: 2017-07-12

Total Pages: 648

ISBN-13: 1420056476

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Mathematical statistics typically represents one of the most difficult challenges in statistics, particularly for those with more applied, rather than mathematical, interests and backgrounds. Most textbooks on the subject provide little or no review of the advanced calculus topics upon which much of mathematical statistics relies and furthermore contain material that is wholly theoretical, thus presenting even greater challenges to those interested in applying advanced statistics to a specific area. Mathematical Statistics with Applications presents the background concepts and builds the technical sophistication needed to move on to more advanced studies in multivariate analysis, decision theory, stochastic processes, or computational statistics. Applications embedded within theoretical discussions clearly demonstrate the utility of the theory in a useful and relevant field of application and allow readers to avoid sudden exposure to purely theoretical materials. With its clear explanations and more than usual emphasis on applications and computation, this text reaches out to the many students and professionals more interested in the practical use of statistics to enrich their work in areas such as communications, computer science, economics, astronomy, and public health.

Mathematical Statistics

Mathematical Statistics PDF

Author: A A Borokov

Publisher: CRC Press

Published: 1999-01-27

Total Pages: 620

ISBN-13: 9789056990183

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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 of estimation theory, hypothesis testing theory and statistical game theory. He then considers statistical problems for two or more samples, and those in which observations are taken from different distributions. Methods of finding optimal and asymptotically optimal statistical procedures are given, along with treatments of homogeneity testing, regression, variance analysis and pattern recognition. The author also posits a number of methodological improvements that simplify proofs, and brings together a number of new results which have never before been published in a single monograph.

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