statistical analysis and data display an intermediate course with examples in r springer texts in statistics

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Statistical Analysis And Data Display

Author : Richard M. Heiberger
ISBN : 9781493921225
Genre : Mathematics
File Size : 62. 70 MB
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This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, and accompanying tabular listings—for all the methods they cover. They emphasize how to construct and interpret graphs. They discuss principles of graphical design. They identify situations where visual impressions from graphs may need confirmation from traditional tabular results. All chapters have exercises. The authors provide and discuss R functions for all the new graphical display formats. All graphs and tabular output in the book were constructed using these functions. Complete R scripts for all examples and figures are provided for readers to use as models for their own analyses. This book can serve as a standalone text for statistics majors at the master’s level and for other quantitatively oriented disciplines at the doctoral level, and as a reference book for researchers. In-depth discussions of regression analysis, analysis of variance, and design of experiments are followed by introductions to analysis of discrete bivariate data, nonparametrics, logistic regression, and ARIMA time series modeling. The authors illustrate classical concepts and techniques with a variety of case studies using both newer graphical tools and traditional tabular displays. The Second Edition features graphs that are completely redrawn using the more powerful graphics infrastructure provided by R's lattice package. There are new sections in several of the chapters, revised sections in all chapters and several completely new appendices. New graphical material includes: • an expanded chapter on graphics • a section on graphing Likert Scale Data to build on the importance of rating scales in fields from population studies to psychometrics • a discussion on design of graphics that will work for readers with color-deficient vision • an expanded discussion on the design of multi-panel graphics • expanded and new sections in the discrete bivariate statistics capter on the use of mosaic plots for contingency tables including the n×2×2 tables for which the Mantel–Haenszel–Cochran test is appropriate • an interactive (using the shiny package) presentation of the graphics for the normal and t-tables that is introduced early and used in many chapters The new appendices include discussions of R, the HH package designed for R (the material in the HH package was distributed as a set of standalone functions with the First Edition of this book), the R Commander package, the RExcel system, the shiny package, and a minimal discussion on writing R packages. There is a new appendix on computational precision illustrating and explaining the FAQ (Frequently Asked Questions) about the differences between the familiar real number system and the less-familiar floating point system used in computers. The probability distributions appendix has been expanded to include more distributions (all the distributions in base R) and to include graphs of each. The editing appendix from the First Edition has been split into four expanded appendices—on working style, writing style, use of a powerful editor, and use of LaTeX for document preparation.

An R And S Plus Companion To Multivariate Analysis

Author : Brian S. Everitt
ISBN : 9781846281242
Genre : Mathematics
File Size : 75. 47 MB
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Applied statisticians often need to perform analyses of multivariate data; for these they will typically use one of the statistical software packages, S-Plus or R. This book sets out how to use these packages for these analyses in a concise and easy-to-use way, and will save users having to buy two books for the job. The author is well-known for this kind of book, and so buyers will trust that he’s got it right.

Measure Theory And Probability Theory

Author : Krishna B. Athreya
ISBN : 9780387329031
Genre : Business & Economics
File Size : 30. 69 MB
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This is a graduate level textbook on measure theory and probability theory. The book can be used as a text for a two semester sequence of courses in measure theory and probability theory, with an option to include supplemental material on stochastic processes and special topics. It is intended primarily for first year Ph.D. students in mathematics and statistics although mathematically advanced students from engineering and economics would also find the book useful. Prerequisites are kept to the minimal level of an understanding of basic real analysis concepts such as limits, continuity, differentiability, Riemann integration, and convergence of sequences and series. A review of this material is included in the appendix. The book starts with an informal introduction that provides some heuristics into the abstract concepts of measure and integration theory, which are then rigorously developed. The first part of the book can be used for a standard real analysis course for both mathematics and statistics Ph.D. students as it provides full coverage of topics such as the construction of Lebesgue-Stieltjes measures on real line and Euclidean spaces, the basic convergence theorems, L^p spaces, signed measures, Radon-Nikodym theorem, Lebesgue's decomposition theorem and the fundamental theorem of Lebesgue integration on R, product spaces and product measures, and Fubini-Tonelli theorems. It also provides an elementary introduction to Banach and Hilbert spaces, convolutions, Fourier series and Fourier and Plancherel transforms. Thus part I would be particularly useful for students in a typical Statistics Ph.D. program if a separate course on real analysis is not a standard requirement. Part II (chapters 6-13) provides full coverage of standard graduate level probability theory. It starts with Kolmogorov's probability model and Kolmogorov's existence theorem. It then treats thoroughly the laws of large numbers including renewal theory and ergodic theorems with applications and then weak convergence of probability distributions, characteristic functions, the Levy-Cramer continuity theorem and the central limit theorem as well as stable laws. It ends with conditional expectations and conditional probability, and an introduction to the theory of discrete time martingales. Part III (chapters 14-18) provides a modest coverage of discrete time Markov chains with countable and general state spaces, MCMC, continuous time discrete space jump Markov processes, Brownian motion, mixing sequences, bootstrap methods, and branching processes. It could be used for a topics/seminar course or as an introduction to stochastic processes. Krishna B. Athreya is a professor at the departments of mathematics and statistics and a Distinguished Professor in the College of Liberal Arts and Sciences at the Iowa State University. He has been a faculty member at University of Wisconsin, Madison; Indian Institute of Science, Bangalore; Cornell University; and has held visiting appointments in Scandinavia and Australia. He is a fellow of the Institute of Mathematical Statistics USA; a fellow of the Indian Academy of Sciences, Bangalore; an elected member of the International Statistical Institute; and serves on the editorial board of several journals in probability and statistics. Soumendra N. Lahiri is a professor at the department of statistics at the Iowa State University. He is a fellow of the Institute of Mathematical Statistics, a fellow of the American Statistical Association, and an elected member of the International Statistical Institute.

Einf Hrung In Die Statistik Der Finanzm Rkte

Author : Jürgen Franke
ISBN : 9783642170492
Genre : Business & Economics
File Size : 80. 17 MB
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Amstat News

Author :
ISBN : UOM:39015059084387
Genre : Statistics
File Size : 75. 29 MB
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Statistik Mit Excel F 1 4r Dummies

Author : Joseph Schmuller
ISBN : 9783527811700
Genre : Computers
File Size : 68. 96 MB
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Statistiken und Aussagen zu Wahrscheinlichkeiten begegnen uns heute ï¿1⁄2berall: Die Umsatzentwicklung in Unternehmen, Hochrechnungen fï¿1⁄2r Wahlergebnisse, PISA-Ergebnisse fï¿1⁄2nfzehnjï¿1⁄2hriger Schï¿1⁄2ler sind nur drei von zahlreichen Beispielen. Joseph Schmuller zeigt Ihnen in diesem Buch, wie Sie die Zahlen in den Griff bekommen und Daten, Statistiken und Wahrscheinlichkeiten richtig lesen und interpretieren. Dafï¿1⁄2r brauchen Sie keinen Statistikkurs zu belegen und kein Mathegenie zu sein. Fï¿1⁄2r alles gibt es in Excel die passende Funktion und das passende Werkzeug. So kï¿1⁄2nnen Sie Theorie und Praxis sofort miteinander verbinden.

Journal Of Transportation And Statistics

Author :
ISBN : STANFORD:36105132173399
Genre : Transportation
File Size : 52. 95 MB
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R F R Dummies

Author : Andrie de Vries
ISBN : 9783527812523
Genre : Computers
File Size : 89. 41 MB
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Statistik Workshop F R Programmierer

Author : Allen B. Downey
ISBN : 9783868993431
Genre : Computers
File Size : 20. 25 MB
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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.

American Book Publishing Record

Author :
ISBN : UOM:39015066043202
Genre : American literature
File Size : 36. 54 MB
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