An Introduction to Mathematical Statistics and Its Applications


Author: Richard J. Larsen,Morris L. Marx
Publisher: Pearson College Division
ISBN: 9780139223037
Category: Mathematics
Page: 790
View: 8675
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Using high-quality, real-world case studies and examples, this introduction to mathematical statistics shows how to use statistical methods and when to use them. This book can be used as a brief introduction to design of experiments. This successful, calculus-based book of probability and statistics, was one of the first to make real-world applications an integral part of motivating discussion. The number of problem sets has increased in all sections. Some sections include almost 50% new problems, while the most popular case studies remain. For anyone needing to develop proficiency with Mathematical Statistics.

Student Solutions Manual

An Introduction to Mathematical Statistics and Its Applications
Author: Richard J. Larsen,Morris L. Marx
Publisher: Prentice Hall
ISBN: N.A
Category: Education
Page: 121
View: 4879
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An Introduction to Mathematical Statistics and Its Applications


Author: Richard J. Larsen,Morris L. Marx
Publisher: Pearson
ISBN: 0134114248
Category: Mathematics
Page: 768
View: 5747
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This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For courses in Mathematical Statistics Introducing the principles of statistics and data modeling Introduction to Mathematical Statistics and Its Applications , 6th Edition is a high-level calculus student’s first exposure to mathematical statistics. This book provides students who have already taken three or more semesters of calculus with the background to apply statistical principles. Meaty enough to guide a two-semester course, the book touches on both statistics and experimental design, which teaches students various ways to analyze data. It gives computational-minded students a necessary and realistic exposure to identifying data models.

Grundbegriffe der Wahrscheinlichkeitsrechnung


Author: A. Kolomogoroff
Publisher: Springer-Verlag
ISBN: 3642498884
Category: Mathematics
Page: 62
View: 874
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Dieser Buchtitel ist Teil des Digitalisierungsprojekts Springer Book Archives mit Publikationen, die seit den Anfängen des Verlags von 1842 erschienen sind. Der Verlag stellt mit diesem Archiv Quellen für die historische wie auch die disziplingeschichtliche Forschung zur Verfügung, die jeweils im historischen Kontext betrachtet werden müssen. Dieser Titel erschien in der Zeit vor 1945 und wird daher in seiner zeittypischen politisch-ideologischen Ausrichtung vom Verlag nicht beworben.

Introduction to Mathematical Statistics and Its Applications


Author: Richard J. Larsen,Morris L. Marx
Publisher: N.A
ISBN: 9781292023557
Category: Mathematical statistics
Page: 744
View: 645
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Noted for its integration of real-world data and case studies, this text offers sound coverage of the theoretical aspects of mathematical statistics. The authors demonstrate how and when to use statistical methods, while reinforcing the calculus that students have mastered in previous courses. Throughout theFifth Edition, the authors have added and updated examples and case studies, while also refining existing features that show a clear path from theory to practice.

Introduction to Mathematical Statistics and Its Applications: Pearson New International Edition


Author: Richard J. Larsen,Morris L. Marx
Publisher: Pearson Higher Ed
ISBN: 1292036729
Category: Mathematics
Page: 744
View: 6779
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Noted for its integration of real-world data and case studies, this text offers sound coverage of the theoretical aspects of mathematical statistics. The authors demonstrate how and when to use statistical methods, while reinforcing the calculus that students have mastered in previous courses. Throughout theFifth Edition, the authors have added and updated examples and case studies, while also refining existing features that show a clear path from theory to practice.

Studyguide for an Introduction to Mathematical Statistics and Its Applications by Larsen, Richard J., ISBN 9780321831460


Author: Cram101 Textbook Reviews
Publisher: Cram101
ISBN: 9781497090231
Category: Education
Page: 138
View: 7384
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Never HIGHLIGHT a Book Again! Includes all testable terms, concepts, persons, places, and events. Cram101 Just the FACTS101 studyguides gives all of the outlines, highlights, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanies: 9780321831460. This item is printed on demand.

An Introduction to Probability Theory and Its Applications


Author: William Feller
Publisher: John Wiley & Sons
ISBN: N.A
Category: Mathematics
Page: 704
View: 9720
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The exponential and the uniform densities; Special densities. Randomization; Densities in higher dimensions. Normal densities and processes; Probability measures and spaces; Probability distributions in Rr; A survey of some important distributions and processes; Laws of large numbers. Aplications in analysis; The basic limit theorems; Infinitely divisible distributions and semi-groups; Markov processes and semi-groups; Renewal theory; Random walks in R1; Laplace transforms. Tauberian theorems. Resolvents; Aplications of Laplace transforms; Characteristic functions; Expansions related to the central limit theorem; Infinitely divisible distributions; Applications of Fourier methods to ramdom walks; harmonic analysis; Answers to problems.

Student's Solutions Manual for an Introduction to Mathematical Statistics and Its Applications


Author: Richard J. Larsen,Morris L. Marx
Publisher: Pearson
ISBN: 9780134114262
Category:
Page: 144
View: 2371
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This manual contains completely worked-out solutions for all the odd-numbered exercises in the text.

An introduction to probability theory and its applications


Author: William Feller
Publisher: John Wiley & Sons
ISBN: 9780471257080
Category: Mathematics
Page: 528
View: 6986
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Major changes in this edition include the substitution of probabilistic arguments for combinatorial artifices, and the addition of new sections on branching processes, Markov chains, and the De Moivre-Laplace theorem.

An introduction to probability and its applications


Author: Richard J. Larsen,Morris L. Marx
Publisher: Prentice Hall
ISBN: N.A
Category: Business & Economics
Page: 404
View: 7310
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Drawing heavily on real-world examples and case studies, this volume offers a calculus-based, non-measure theoretic, problem-solving-oriented introduction to probability.

Stochastik

Einführung in die Wahrscheinlichkeitstheorie und Statistik
Author: Hans-Otto Georgii
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110359707
Category: Mathematics
Page: 448
View: 5907
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Dieses Lehrbuch gibt eine Einführung in die "Mathematik des Zufalls", bestehend aus den beiden Teilbereichen Wahrscheinlichkeitstheorie und Statistik. Die stochastischen Konzepte, Modelle und Methoden werden durch typische Anwendungsbeispiele motiviert und anschließend systematisch entwickelt. Der dafür notwendige maßtheoretische Rahmen wird gleich zu Beginn auf elementarem Niveau bereitgestellt. Zahlreiche Übungsaufgaben, zum Teil mit Lösungsskizzen, illustrieren und ergänzen den Text. Zielgruppe sind Studierende der Mathematik ab dem dritten Semester, sowie Naturwissenschaftler und Informatiker mit Interesse an den mathematischen Grundlagen der Stochastik. Die 5. Auflage wurde nochmals bearbeitet und maßvoll ergänzt.

Einführung in Statistik und Messwertanalyse für Physiker

Monographie
Author: G. Bohm,G. Zech
Publisher: N.A
ISBN: 9783540257592
Category:
Page: 400
View: 5906
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Die Einf]hrung in die Statistik und Messwertanalyse f]r Physiker richtet sich weniger an mathematischen \berlegungen aus, sondern stellt die praktische Anwendung in den Vordergrund und schdrft die Intuition experimentelle Ergebnisse richtig einzuschdtzen. Zahlreiche ausf]hrlich betrachtete Beispiele dienen dazu, hdufig bei der Datenanalyse gemachte Fehler zu vermeiden (unsinnige Anwendung des Chi-Quadrattests, Funktionenanpassung bei falscher Parametrisierung, Entfaltung mit willk]rlicher Regularisierung). Ein besonderes Augenmerk wird auf den Vergleich von Daten mit Monte-Carlo-Simulationen gelenkt. Moderne Experimente kommen nicht ohne Simulation aus. Deshalb ist es wichtig zu wissen, wie Parameteranpassungen und Entfaltungen in diesem Fall durchgef]rt werden. Au_erdem werden den Studierenden moderne Entwicklungen der Statistik nahegebracht, die in dlteren Lehrb]chern nicht behandelt werden.

An Introduction to Statistical Inference and Its Applications with R


Author: Michael W. Trosset
Publisher: CRC Press
ISBN: 9781584889489
Category: Mathematics
Page: 496
View: 9375
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Emphasizing concepts rather than recipes, An Introduction to Statistical Inference and Its Applications with R provides a clear exposition of the methods of statistical inference for students who are comfortable with mathematical notation. Numerous examples, case studies, and exercises are included. R is used to simplify computation, create figures, and draw pseudorandom samples—not to perform entire analyses. After discussing the importance of chance in experimentation, the text develops basic tools of probability. The plug-in principle then provides a transition from populations to samples, motivating a variety of summary statistics and diagnostic techniques. The heart of the text is a careful exposition of point estimation, hypothesis testing, and confidence intervals. The author then explains procedures for 1- and 2-sample location problems, analysis of variance, goodness-of-fit, and correlation and regression. He concludes by discussing the role of simulation in modern statistical inference. Focusing on the assumptions that underlie popular statistical methods, this textbook explains how and why these methods are used to analyze experimental data.

Statistik II für Dummies


Author: Deborah J. Rumsey
Publisher: John Wiley & Sons
ISBN: 3527669248
Category: Mathematics
Page: 372
View: 319
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Vom Absolutrang bis zum Zweifach-Varianzanalysemodell – alles, was Sie über weiterführende Statistik wissen sollten Es gibt Qualen, große Qualen und Statistik, so sehen es viele Studenten. Mit diesem Buch lernen Sie weiterführende Statistik so leicht wie möglich. Deborah Rumsey zeigt Ihnen, wie Sie Varianzanalysen und Chi-Quadrat-Tests berechnen, wie Sie mit Regressionen arbeiten, ein Modell erstellen, Korrelationen bilden, nichtparametrische Prozeduren durchführen und vieles mehr. Aber auch die Grundlagen der Statistik bleiben nicht außen vor und deshalb erklärt Ihnen die Autorin, was Sie zu Mittelwerten, Vertrauensintervallen und Co wissen sollten. So lernen Sie die Methoden, die Sie brauchen, und erhalten das Handwerkszeug, um erfolgreich Ihre Statistikprüfungen zu bestehen. Sie erfahren: • Wie Sie mit multiplen Regressionen umgehen • Was es mit dem Vorzeichentest und dem Vorzeichenrangtest auf sich hat • Wie Sie sich innerhalb der statistischen Techniken zurechtfinden • Was das richtige Regressionsmodell für Ihre Analyse ist • Wie Regression und ANOVA zusammenhängen

Problems in Probability Theory, Mathematical Statistics and Theory of Random Functions


Author: Aram Aruti?u?novich Sveshnikov,Bernard R. Gelbaum
Publisher: Courier Corporation
ISBN: 9780486637174
Category: Mathematics
Page: 481
View: 5666
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Approximately 1,000 problems — with answers and solutions included at the back of the book — illustrate such topics as random events, random variables, limit theorems, Markov processes, and much more.

Linear Statistical Models


Author: James H. Stapleton
Publisher: John Wiley & Sons
ISBN: 0470317760
Category: Mathematics
Page: 472
View: 5121
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Linear Statistical Models Developed and refined over a period of twenty years, the material in this book offers an especially lucid presentation of linear statistical models. These models lead to what is usually called "multiple regression" or "analysis of variance" methodology, which, in turn, opens up a wide range of applications to the physical, biological, and social sciences, as well as to business, agriculture, and engineering. Unlike similar books on this topic, Linear Statistical Models emphasizes the geometry of vector spaces because of the intuitive insights this approach brings to an understanding of the theory. While the focus is on theory, examples of applications, using the SAS and S-Plus packages, are included. Prerequisites include some familiarity with linear algebra, and probability and statistics at the postcalculus level. Major topics covered include: * Methods of study of random vectors, including the multivariate normal, chi-square, t and F distributions, central and noncentral * The linear model and the basic theory of regression analysis and the analysis of variance * Multiple regression methods, including transformations, analysis of residuals, and asymptotic theory for regression analysis. Separate sections are devoted to robust methods and to the bootstrap. * Simultaneous confidence intervals: Bonferroni, Scheffe, Tukey, and Bechhofer * Analysis of variance, with two- and three-way analysis of variance * Random component models, nested designs, and balanced incomplete block designs * Analysis of frequency data through log-linear models, with emphasis on vector space viewpoint. This chapter alone is sufficient for a course on the analysis of frequency data.

Mathematical Statistics with Applications in R


Author: Kandethody M. Ramachandran,Chris P. Tsokos
Publisher: Elsevier
ISBN: 012417132X
Category: Mathematics
Page: 826
View: 1635
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Mathematical Statistics with Applications in R, Second Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation concepts that are not covered in other texts, such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. By combining the discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem solving in a logical manner. This book provides a step-by-step procedure to solve real problems, making the topic more accessible. It includes goodness of fit methods to identify the probability distribution that characterizes the probabilistic behavior or a given set of data. Exercises as well as practical, real-world chapter projects are included, and each chapter has an optional section on using Minitab, SPSS and SAS commands. The text also boasts a wide array of coverage of ANOVA, nonparametric, MCMC, Bayesian and empirical methods; solutions to selected problems; data sets; and an image bank for students. Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course will find this book extremely useful in their studies. Step-by-step procedure to solve real problems, making the topic more accessible Exercises blend theory and modern applications Practical, real-world chapter projects Provides an optional section in each chapter on using Minitab, SPSS and SAS commands Wide array of coverage of ANOVA, Nonparametric, MCMC, Bayesian and empirical methods