This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key concepts and models used in meta-analysis. It also includes chapters on the following advanced topics: publication bias and small study effects; missing data; multivariate meta-analysis, network meta-analysis; and meta-analysis of diagnostic studies.

Some probability problems are so difficult that they stump the smartest mathematicians. But even the hardest of these problems can often be solved with a computer and a Monte Carlo simulation, in which a random-number generator simulates a physical process, such as a million rolls of a pair of dice. This is what "Digital Dice" is all about: how to get numerical answers to difficult probability problems without having to solve complicated mathematical equations.

Popular-math writer Paul Nahin challenges readers to solve twenty-one difficult but fun problems, from determining the odds of coin-flipping games to figuring out the behavior of elevators. Problems build from relatively easy (deciding whether a dishwasher who breaks most of the dishes at a restaurant during a given week is clumsy or just the victim of randomness) to the very difficult (tackling branching processes of the kind that had to be solved by Manhattan Project mathematician Stanislaw Ulam). In his characteristic style, Nahin brings the problems to life with interesting and odd historical anecdotes. Readers learn, for example, not just how to determine the optimal stopping point in any selection process but that astronomer Johannes Kepler selected his second wife by interviewing eleven women.

The book shows readers how to write elementary computer codes using any common programming language, and provides solutions and line-by-line walk-throughs of a MATLAB code for each problem.

"Digital Dice" will appeal to anyone who enjoys popular math or computer science. In a new preface, Nahin wittily addresses some of the responses he received to the first edition.

Das UEbungsbuch stellt eine ausgesuchte Sammlung von Problemstellungen und Loesungen bereit, die durch eine Formelsammlung mit den wichtigsten im Buch verwendeten Formeln abgerundet wird. Zusatzlich wird ein umfangreiches Set von Programmen in R zur Verfugung gestellt, die zur Aufgabenstellung und Loesung geschrieben wurden. Der Anhang des Buches beinhaltet daher auch eine kurze Einfuhrung in die Statistik-Software R. Der Inhalt, Organisation inklusive Kapitelaufteilung orientiert sich an dem bei Springer erschienenem Werk "Statistik fur Bachelor- und Masterstudenten: Eine Einfuhrung fur Wirtschafts- und Sozialwissenschaftler"

The book presents a comprehensive vision of the impact of ICT on the contemporary city, heritage, public spaces and meta-cities on both urban and metropolitan scales, not only in producing innovative perspectives but also related to newly discovered scientific methods, which can be used to stimulate the emerging reciprocal relations between cities and information technologies. Using the principles established by multi-disciplinary interventions as examples and then expanding on them, this book demonstrates how by using ICT and new devices, metropolises can be organized for a future that preserves the historic nucleus of the city and the environment while preparing the necessary expansion of transportation, housing and industrial facilities.

Anlasslich des 25jahrigen Jubilaums des Deutschen Krebsforschungszentrums (DKFZ) in Heidelberg geben die Autoren einen Uberblick uber Institutionen und Organisationsformen der Krebsforschung in Deutschland, speziell der Vorgeschichte und Geschichte des DKFZ seit Anfang des 20. Jahrhunderts."

Si tratta di un'opera introduttiva al campionamento da popolazioni finite. Si ritiene che un'opera su questo argomento sia adatta alle lauree triennali, ma contiene anche una parte di materiale avanzato da utilizzare per lauree specialistiche. L'opera e ricca di esempi, ed e accessibile anche a chi abbia seguito un corso elementare di statistica e probabilita, del tipo di quelli impartiti in lauree triennali di economia. Il volume e adatto non solo a studenti di corsi di laurea in statistica, ma anche a studenti di altre facolta che vogliano usare i metodi di campionamento con taglio elementare e applicativo senza rinunciare ad un modicum di teoria."

Learn statistical methods quickly and easily with the discovery method
With its emphasis on the discovery method, this publication encourages readers to discover solutions on their own rather than simply copy answers or apply a formula by rote. Readers quickly master and learn to apply statistical methods, such as bootstrap, decision trees, t-test, and permutations to better characterize, report, test, and classify their research findings. In addition to traditional methods, specialized methods are covered, allowing readers to select and apply the most effective method for their research, including:
* Tests and estimation procedures for one, two, and multiple samples
* Model building
* Multivariate analysis
* Complex experimental design
Throughout the text, Microsoft Office Excel(r) is used to illustrate new concepts and assist readers in completing exercises. An Excel Primer is included as an Appendix for readers who need to learn or brush up on their Excel skills.
Written in an informal, highly accessible style, this text is an excellent guide to descriptive statistics, estimation, testing hypotheses, and model building. All the pedagogical tools needed to facilitate quick learning are provided:
* More than 100 exercises scattered throughout the text stimulate readers' thinking and actively engage them in applying their newfound skills
* Companion FTP site provides access to all data sets discussed in the text
* An Instructor's Manual is available upon request from the publisher
* Dozens of thought-provoking questions in the final chapter assist readers in applying statistics to solve real-life problems
* Helpful appendices include an index to Excel and Excel add-in functions
This text serves as an excellent introduction to statistics for students in all disciplines. The accessible style and focus on real-life problem solving are perfectly suited to both students and practitioners.

Computeralgebra-Systeme spielen in Zukunft im Mathematikunterricht der Sekundarstufe II eine wichtige Rolle. Dieses Buch ist auf den Schulstoff der Sekundarstufe II ausgerichtet und richtet sich an Lehramtsstudenten und interessierte Lehrer, die sich in das Programm DERIVE einarbeiten mochten, um es dann im Unterricht, insbesondere in Leistungskursen Mathematik, zu verwenden."

In statistics, fitting linear models to data is a general theme. This manual describes how GLIM 4--the popular software package--may be used for statistical analysis, including data manipulation and display, model fitting, and prediction. The manual has been divided into three distinct guides. The User Guide introduces and illustrates all the facilities in GLIM 4. Each chapter describes the directives relevant to a particular type of activity involved in the statistical modelling of data. The Modelling Guide presents a broad array of examples which comprise an effective introduction for new users. The Reference Guide contains a formal description of the syntax and semantics of the GLIM 4 language, of the data structures it handles, and of the directives provided, constituting a reference manual for the experienced user. This book is sure to be useful to research statisticians wherever GLIM is used.

The aim of stochastic programming is to find optimal decisions in problems which involve uncertain data. This field is currently developing rapidly with contributions from many disciplines including operations research, mathematics, and probability. At the same time, it is now being applied in a wide variety of subjects ranging from agriculture to financial planning and from industrial engineering to computer networks. This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability. The authors aim to present a broad overview of the main themes and methods of the subject. Its prime goal is to help students develop an intuition on how to model uncertainty into mathematical problems, what uncertainty changes bring to the decision process, and what techniques help to manage uncertainty in solving the problems. In this extensively updated new edition there is more material on methods and examples including several new approaches for discrete variables, new results on risk measures in modeling and Monte Carlo sampling methods, a new chapter on relationships to other methods including approximate dynamic programming, robust optimization and online methods. The book is highly illustrated with chapter summaries and many examples and exercises. Students, researchers and practitioners in operations research and the optimization area will find it particularly of interest. Review of First Edition: "The discussion on modeling issues, the large number of examples used to illustrate the material, and the breadth of the coverage make 'Introduction to Stochastic Programming' an ideal textbook for the area." (Interfaces, 1998)

Think you can't have fun learning statistics? Think again.

"The Manga Guide to Statistics" will teach you everything you need to know about this essential discipline, while entertaining you at the same time. With its unique combination of Japanese-style comics called manga and serious educational content, the EduManga format is already a hit in Japan.

In "The Manga Guide to Statistics," our heroine Rui is determined to learn about statistics to impress the dreamy Mr. Igarashi and begs her father for a tutor. Soon she's spending her Saturdays with geeky, bespectacled Mr. Yamamoto, who patiently teaches her all about the fundamentals of statistics: topics like data categorization, averages, graphing, and standard deviation.

After all her studying, Rui is confident in her knowledge of statistics, including complex concepts like probability, coefficients of correlation, hypothesis tests, and tests of independence. But is it enough to impress her dream guy? Or maybe there's someone better, right in front of her?

Reluctant statistics students of all ages will enjoy learning along with Rui in this charming, easy-to-read guide, which uses real-world examples like teen magazine quizzes, bowling games, test scores, and ramen noodle prices. Examples, exercises, and answer keys help you follow along and check your work. An appendix showing how to perform statistics calculations in Microsoft Excel makes it easy to put Rui's lessons into practice.

This EduManga book is a translation from a bestselling series in Japan, co-published with Ohmsha, Ltd. of Tokyo, Japan.

The first seven chapters use R for probability simulation and computation, including random number generation, numerical and Monte Carlo integration, and finding limiting distributions of Markov Chains with both discrete and continuous states. Applications include coverage probabilities of binomial confidence intervals, estimation of disease prevalence from screening tests, parallel redundancy for improved reliability of systems, and various kinds of genetic modeling. These initial chapters can be used for a non-Bayesian course in the simulation of applied probability models and Markov Chains. Chapters 8 through 10 give a brief introduction to Bayesian estimation and illustrate the use of Gibbs samplers to find posterior distributions and interval estimates, including some examples in which traditional methods do not give satisfactory results. WinBUGS software is introduced with a detailed explanation of its interface and examples of its use for Gibbs sampling for Bayesian estimation. No previous experience using R is required. An appendix introduces R, and complete R code is included for almost all computational examples and problems (along with comments and explanations). Noteworthy features of the book are its intuitive approach, presenting ideas with examples from biostatistics, reliability, and other fields; its large number of figures; and its extraordinarily large number of problems (about a third of the pages), ranging from simple drill to presentation of additional topics. Hints and answers are provided for many of the problems. These features make the book ideal for students of statistics at the senior undergraduate and at the beginning graduate levels.

How to Use SPSS (R) is designed with the novice computer user in mind and for people who have no previous experience using SPSS. Each chapter is divided into short sections that describe the statistic being used, important underlying assumptions, and how to interpret the results and express them in a research report. The book begins with the basics, such as starting SPSS, defining variables, and entering and saving data. It covers all major statistical techniques typically taught in beginning statistics classes, such as descriptive statistics, graphing data, prediction and association, parametric inferential statistics, nonparametric inferential statistics and statistics for test construction. More than 270 screenshots (including sample output) throughout the book show students exactly what to expect as they follow along using SPSS. The book includes a glossary of statistical terms and practice exercises. A complete set of online resources including video tutorials and output files for students, and PowerPoint slides and test bank questions for instructors, make How to Use SPSS (R) the definitive, field-tested resource for learning SPSS. New to this edition: Now in full color with additional screenshots Fully updated to the reflect SPSS version 26 (and prior versions) Changes in nonparametric tests Model View incorporated Data and real output are now available for all Phrasing Results sections - eliminating hypothetical output or hypothetical data

Das Arbeitsbuch f hrt in die Nutzung der Software Statistiklabor ein. Die Funktionalit t wird im ersten Teil detailliert beschrieben, der zweite Teil illustriert Standardauswertungen. Die Software kann kostenfrei unter www.statistiklabor.de heruntergeladen werden. Sie bietet eine interaktive Arbeitsumgebung, um statistische Funktionen und Darstellungsm glichkeiten leicht und intuitiv bearbeiten zu k nnen, und erlaubt einen wesentlich einfacheren Zugang zu der umfangreichen Funktionalit t der Statistik-Programmierumgebung R.

Optionen, Futures, Swaps, strukturierte Investments - auf den heutigen Finanzmarkten werden eine Fulle so genannter derivativer (abgeleiteter) Finanzinstrumente gehandelt. Deren Bewertung und Risikomanagement sind Gegenstand der modernen Finanzmathematik. Dieses Buch fuhrt an entsprechende Fragestellungen, Denkweisen und Losungskonzepte heran und legt dabei besonderes Augenmerk auf praxisrelevante Aspekte und Modelle. Die algorithmische Umsetzung der Losungskonzepte wird in zahlreichen Beispielen mit dem Software-Paket "UnRisk" illustriert. Dieses wird Dozenten und Studierenden (zeitlich begrenzt) zur Verfugung gestellt und bietet uber die Plattform "Mathematica" eine graphisch ansprechende Oberflache.

Die vorliegende Einfuhrung ist speziell fur Veranstaltungen in Bachelor-Studiengangen konzipiert."

Written by the author of the lattice system, this book describes lattice in considerable depth, beginning with the essentials and systematically delving into specific low levels details as necessary. No prior experience with lattice is required to read the book, although basic familiarity with R is assumed. The book contains close to 150 figures produced with lattice. Many of the examples emphasize principles of good graphical design; almost all use real data sets that are publicly available in various R packages. All code and figures in the book are also available online, along with supplementary material covering more advanced topics.

Michael Mitchell's A Visual Guide to Stata Graphics, Fourth Edition provides an essential introduction and reference for Stata graphics. The fourth edition retains the features that made the first three editions so useful: A complete guide to Stata's graph command Exhaustive examples of customized graphs Visual indexing of features-just look for a picture that matches what you want to do This edition includes new discussions of color, Unicode characters, export formats, sizing of graph elements, and schemes. The section on colors has been greatly expanded to include over 50 examples that demonstrate how to modify colors, add transparency, and change intensity. In the discussion of text modifications, Mitchell now shows how to include Unicode characters such as Greek letters, symbols, and emojis. New examples have also been added that show how to change the size of graph elements such as text, markers, and line widths using both absolute units (points, inches, and centimeters) as well as relative units (line large or *2 for two times the original size). Finally, the look of graphs throughout the book has changed-most graphs are now created using a common updated scheme. The book's visual style makes it easy to find exactly what you need. A color-coded, visual table of contents runs along the edge of every page and shows readers exactly where they are in the book. You can see the color-coded chapter tabs without opening the book, providing quick visual access to each chapter. The heart of each chapter is a series of entries that are typically formatted three to a page. Each entry shows a graph command (with the emphasized portion of the command highlighted in red), the resulting graph, a description of what is being done, and the dataset used. Because every feature, option, and edit is demonstrated with a graph, you can often flip through a section of the book to find exactly the effect you are seeking. The book begins with an introduction to Stata graphs that includes an overview of graphs types, schemes, and options and the process of building a graph. Then, it turns to detailed discussions of many graph types-scatterplots, regression fit plots, line plots, contour plots, bar graphs, box plots, and many others. Mitchell shows how to create each type of graph and how to use options to control the look of the graph. Because Stata's graph command will let you customize any aspect of the graph, Mitchell spends ample time showing you the most valuable options for obtaining the look you want. If you are in a hurry to discover one special option, you can skim the chapter until you see the effect you want and then glance at the command to see what is highlighted in red. After focusing on specific types of graphs, Mitchell undertakes an in-depth presentation of the options available across almost all graph types. This includes options that add and change the look of titles, notes, and such; control the number of ticks on axes; control the content and appearance of the numbers and labels on axes; control legends; add and change the look of annotations; graph over subgroups; change the look of markers and their labels; size graphs and their elements; and more. To complete the graphical journey, Mitchell discusses and demonstrates the 12 styles that unite and control the appearance of the myriad graph objects. These styles are angles, colors, clock positions, compass directions, connecting points, line patterns, line widths, margins, marker sizes, orientations, marker symbols, and text sizes. You won't want to overlook the appendix in this book. There Mitchell first gives a quick overview of the dozens of statistical graph commands that are not strictly the subject of the book. Even so, these commands use the graph command as an engine to draw their graphs; therefore, almost all that Mitchell has discussed applies to them. He also addresses combining graphs-showing you how to create complex and multipart images from previously created graphs. In a crucial section titled "Putting it all together", Mitchell shows us how to do just that. We learn more about overlaying twoway plots, and we learn how to combine data management and graphics to create plots such as bar charts of rates with capped confidence intervals. Mitchell concludes by warning us about mistakes that can be made when typing graph commands and how to correct them. The fourth edition of A Visual Guide to Stata Graphics is a complete guide to Stata's graph command and the associated Graph Editor. Whether you want to tame the Stata graph command, quickly find out how to produce a graphical effect, or learn approaches that can be used to construct custom graphs, this is the book to read.

Unter Computeralgebra versteht man den Grenzbereich zwischen Algebra und Informatik, der sich mit Entwurf, Analyse, Implementierung und Anwendung algebraischer Algorithmen befasst. Entsprechend dieser Sichtweise stellt der Autor einige Computeralgebra-Systeme vor und zeigt an Beispielen deren LeistungsfAhigkeit. Grundlegende Techniken, wie etwa das Rechnen mit groAen ganzen Zahlen, werden untersucht. FA1/4r komplexe Fragestellungen wie das Faktorisieren von Polynomen, werden mehrere Algorithmen angeboten, da diese verschiedene StArken haben. HAufig ist der vermeintliche Umweg A1/4ber andere mathematische Strukturen der schnellste Weg. In den ersten Kapiteln werden die nAtigen mathematischen Grundlagen zur VerfA1/4gung gestellt. Die folgenden Kapitel kAnnen dann weitestgehend unabhAngig voneinander gelesen werden. Alle vorgestellten Algorithmen werden begrA1/4ndet und teilweise in einer Pseudoprogrammiersprache dargestellt. Das Buch richtet sich gleichermaAen an Studierende der Mathematik und der Informatik.

Dynamische Systeme stellen einen unverzichtbaren Bestandteil mathematischer
Modellbildung fur Anwendungen aller Art dar, angefangen von Physik uber Biologie
bis hin zur Informatik. Dieser Band fuhrt in diese Theorie ein und beschreibt Methoden und Dynamiken, wie sie fur eine systematische Modellbildung auch in den Anwendungen notwendig erscheinen. Wesentliche Grundzuge der Theorie werden beispielhaft im ersten Kapitel erlautert. Es schliesst sich eine Einfuhrung in niedrig-dimensionale Dynamiken an (u.a. rationale Funktionen), gefolgt von topologischer Dynamik (z.B. Attraktoren, Entropie und chaotisches Verhalten), differenzierbarer Dynamik (z.B. Liapunoff-Exponenten, Strukturstabilitat und Hyperbolizitat), Ergodentheorie (z.B. Ergodensatze, invariante Masse, Konservativitat) und schliesslich thermodynamischer Formalismus (z.B. Gibbs-Theorie, Zetafunktionen)."

Ce livre est une introduction a la theorie de la complexite algebrique basee sur un panorama des methodes algorithmiques en algebre lineaire exacte. Il donne en particulier les principaux algorithmes pour le calcul du polynome caracteristique. Ce livre se remarque par l'etendue des sujets traites tout en restant tres lisible.

MuPAD ist ein Computeralgebra-System, mit dem nicht nur Problemstellungen der Mathematik sondern auch mathematische Aufgaben in den Natur- und Ingenieurwissenschaften behandelt werden konnen. Das Tutorium fur Einsteiger fuhrt grundlegend in MuPAD ein (ab Version 3.0.). In nachvollziehbaren Schritten werden die wichtigsten Bausteine vorgestellt. Systemfunktionen, Graphik sowie Programmierung konnen Nutzer anhand zahlreicher Beispiele einuben. Zukunftige Anderungen und Erweiterungen werden unter http: //www.mupad.de/doc.html dokumentiert."

Dieses zweibandige Lehrbuch umfasst einen Kanon von Themen, der an vielen Universitaten unter dem Titel "Diskrete Strukturen" fester Bestandteil des Informatik-Grundstudiums geworden ist. Bei der Darstellung wird neben der mathematischen Exaktheit besonderer Wert darauf gelegt, auch das intuitive Verstandnis zu fordern, um so das Verstehen und Einordnen des Stoffs zu erleichtern. Unterstutzt wird dies durch zahlreiche Beispiele und Aufgaben, vorwiegend aus dem Bereich der Informatik. Das Lehrbuch basiert auf Vorlesungen, die seit mehreren Jahren an der Technischen Universitat Munchen gehalten werden.
Themen des zweiten Bandes: Endliche und unendliche Wahrscheinlichkeitsraume, Markov-Ketten, Warteschlangen, Induktive Statistik."

Ce didacticiel explique les bases de l'utilisation du programme MuPAD et donne un apercu de la puissance du systeme. Les principales caracteristiques et les outils de base en sont presentes au cours d'etapes simples. Beaucoup d'exemples et d'exercices illustrent comment utiliser les fonctions, les methodes graphiques, et le langage de programmation du systeme. Ce didactciel se rapporte aux versions 1.4, 2.0 ou ulterieures des MuPAD.

Das Buch befasst sich mit der nichtkooperativen Spieltheorie unter Zuhilfenahme eines Computer-Algebra-Systems (Mathematica). Der Schwerpunkt des Buches liegt bei der Bestimmung von Techniken und Algorithmen fur die Loesung von Zweipersonenspielen und deren Implementierung am Rechner. Die Ideen werden anhand von Standardbeispielen wie das Gefangenendilemma, Krieg der Geschlechter oder Falke-Taube-Spiel illustriert und erklart. Aber auch praktische Probleme, vor allem Inspektionssituationen, werden mittels Spieltheorie modelliert und mit Mathematica geloest. Durch den algorithmischen Ansatz, und durch die enge Verknupfung des Textes mit Mathematica-Notebooks wird dem Leser ein unterhaltsamer und nachvollziehbarer Zugang zu den grundlegenden Prinzipien der nichtkooperativen Spieltheorie geboten. Auf einer begleitenden Diskette befinden sich Mathematica-Notebooks sowie ein Mathematica-Package mit Implementierungen zu allen im Text entwickelten Algorithmen.