understanding statistical concepts using s plus

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Understanding Statistical Concepts Using S Plus

Author : Randall E. Schumacker
ISBN : 9781135657031
Genre : Psychology
File Size : 36. 33 MB
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Written as a supplemental text for an introductory or intermediate statistics course, this book is organized along the lines of many popular statistics texts. The chapters provide a good conceptual understanding of basic statistics and include exercises that use S-PLUS simulation programs. Each chapter lists a set of objectives and a summary. The book offers a rich insight into how probability has shaped statistical procedures in the behavioral sciences, as well as a brief history behind the creation of various statistics. Computational skills are kept to a minimum by including S-PLUS programs that run the exercises in the chapters. Students are not required to master the writing of S-PLUS programs, but explanations of how the programs work and program output are included in each chapter. S-PLUS is an advanced statistical package that has an extensive library of functions, which offer flexibility in writing customized routines. The S-PLUS functions provide the capability of programming object and dialog windows, which are commonly used in Windows software applications. The S-PLUS program also contains pull-down menus for the statistical analysis of data. A ZIP file containing programs that work in S-PLUS 6.2 for use with this book is available for download from http://www.psypress.com/resources/9780805836233.zip - please note that these scripts will only run in S-PLUS 6.2 and not later versions due to changes in the programming language syntax.

Using R With Multivariate Statistics

Author : Randall E. Schumacker
ISBN : 9781483377988
Genre : Social Science
File Size : 57. 36 MB
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Using R with Multivariate Statistics by Randall E. Schumacker is a quick guide to using R, free-access software available for Windows and Mac operating systems that allows users to customize statistical analysis. Designed to serve as a companion to a more comprehensive text on multivariate statistics, this book helps students and researchers in the social and behavioral sciences get up to speed with using R. It provides data analysis examples, R code, computer output, and explanation of results for every multivariate statistical application included. In addition, R code for some of the data set examples used in more comprehensive texts is included, so students can run examples in R and compare results to those obtained using SAS, SPSS, or STATA. A unique feature of the book is the photographs and biographies of famous persons in the field of multivariate statistics.

Classical Methods Of Statistics

Author : Otto J.W.F. Kardaun
ISBN : 3540292888
Genre : Science
File Size : 86. 85 MB
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Classical Methods of Statistics is a guidebook combining theory and practical methods. It is especially conceived for graduate students and scientists who are interested in the applications of statistical methods to plasma physics. Thus it provides also concise information on experimental aspects of fusion-oriented plasma physics. In view of the first three basic chapters it can be fruitfully used by students majoring in probability theory and statistics. The first part deals with the mathematical foundation and framework of the subject. Some attention is given to the historical background. Exercises are added to help readers understand the underlying concepts. In the second part, two major case studies are presented which exemplify the areas of discriminant analysis and multivariate profile analysis, respectively. To introduce these case studies, an outline is provided of the context of magnetic plasma fusion research. In the third part an overview is given of statistical software; separate attention is devoted to SAS and S-PLUS. The final chapter presents several datasets and gives a description of their physical setting. Most of these datasets were assembled at the ASDEX Upgrade Tokamak. All of them are accompanied by exercises in form of guided (minor) case studies. The book concludes with translations of key concepts into several languages.

Statistical Analysis Of Financial Data In S Plus

Author : René Carmona
ISBN : 9780387218243
Genre : Business & Economics
File Size : 36. 97 MB
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This is the first book at the graduate textbook level to discuss analyzing financial data with S-PLUS. Its originality lies in the introduction of tools for the estimation and simulation of heavy tail distributions and copulas, the computation of measures of risk, and the principal component analysis of yield curves. The book is aimed at undergraduate students in financial engineering; master students in finance and MBA's, and to practitioners with financial data analysis concerns.

Environmental Statistics With S Plus

Author : Steven P. Millard
ISBN : 9781420037173
Genre : Mathematics
File Size : 80. 57 MB
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A clear, comprehensive treatment of the subject, Environmental Statistics with S-PLUS surveys the vast array of statistical methods used to collect and analyze environmental data. The book explains what these methods are, how to use them, and where to find references to them. In addition, it provides insight into what to think about before you collect environmental data, how to collect the data, and how to make sense of it after collection. A unique and powerful feature of the book is its integration with the commercially available software package S-Plus and the add-on modules EnvironmentalStats for S-PLUS, S+SpatialStats, and S-PLUS for ArcView. The book presents data sets to explain statistical methods, and then shows how to implement these methods by providing the commands for and the results from the software. This survey of statistical methods, definitions, and concepts helps you collect and effectively analyze data for environmental pollution problems. Using the S-PLUS software in conjunction with this text will no doubt increase understanding of the methods.

Learning Statistics Using R

Author : Randall E. Schumacker
ISBN : 9781483324777
Genre : Social Science
File Size : 72. 40 MB
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Providing easy-to-use R script programs that teach descriptive statistics, graphing, and other statistical methods, Learning Statistics Using R shows readers how to run and utilize R, a free integrated statistical suite that has an extensive library of functions. Schumacker’s comprehensive book describes the processing of variables in statistical procedures. Covering a wide range of topics, from probability and sampling distribution to statistical theorems and chi-square, this introductory book helps readers learn not only how to use formulae to calculate statistics, but also how specific statistics fit into the overall research process. Each chapter includes discussion and explanations, tables and graphs, and R functions and outputs to enrich readers' understanding of statistics through statistical computing and modeling.

Choice

Author :
ISBN : UOM:39015066043368
Genre : Academic libraries
File Size : 57. 13 MB
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Modern Applied Biostatistical Methods

Author : Steve Selvin
ISBN : 9780199747733
Genre : Medical
File Size : 38. 20 MB
Format : PDF
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Statistical analysis typically involves applying theoretically generated techniques to the description and interpretation of collected data. In this text, theory, application and interpretation are combined to present the entire biostatistical process for a series of elementary and intermediate analytic methods. The theoretical basis for each method is discussed with a minimum of mathematics and is applied to a research data example using a computer system called S-PLUS. This system produces concrete numerical results and increases one's understanding of the fundamental concepts and methodology of statistical analysis. Combining statistical logic, data and computer tools, the author explores such topics as random number generation, general linear models, estimation, analysis of tabular data, analysis of variance and survival analysis. The end result is a clear and complete explanation of the way statistical methods can help one gain an understanding of collected data. Modern Applied Biostatistical Methods is unlike other statistical texts, which usually deal either with theory or with applications. It integrates the two elements into a single presentation of theoretical background, data, interpretation, graphics, and implementation. This all-around approach will be particularly helpful to students in various biostatistics and advanced epidemiology courses, and will interest all researchers involved in biomedical data analysis. This text is not a computer manual, even though it makes extensive use of computer language to describe and illustrate applied statistical techniques. This makes the details of the statistical process readily accessible, providing insight into how and why a statistical method identifies the properties of sampled data. The first chapter gives a simple overview of the S-PLUS language. The subsequent chapters use this valuable statistical tool to present a variety of analytic approaches.

Statistical Analysis And Data Display

Author : Richard M. Heiberger
ISBN : 9781475742848
Genre : Mathematics
File Size : 87. 88 MB
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This 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 computer listings. They emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how tabular results are used to confirm the visual impressions derived from the graphs. Many of the graphical formats are novel and appear here for the first time in print.

Computing Archaeology For Understanding The Past

Author : Zoran Stančič
ISBN : UVA:X006113172
Genre : Social Science
File Size : 50. 3 MB
Format : PDF
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A series of 51 papers forming the Proceedings of the 28th CAA Conference held at Ljubljana, Slovenia in 2000 focusing on computer applications and quantative methods in European and American archaeology. The papers, which are all in English, are divided into eight sections: Documentation and recording of sites and field survey data; Artefact analysis and classification; National and regional SMR; Intra site spatial analysis; Archaeological regional spatial analysis and predictive modelling; Future trends in spatial analyses; Presentation of archaeological data; Public access to archaeological heritage.

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