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Beginning R : the Statistical Programming Language.

Autor: Mark Gardener
Editorial: Hoboken : John Wiley & Sons, 2012.
Edición/Formato:   Libro-e : Documento : Inglés (eng)Ver todas las ediciones y todos los formatos
Base de datos:WorldCat
Resumen:
Chapter 3: Starting Out: Working; Manipulating Objects; Viewing Objects within Objects; Constructing Data Objects; Forms of Data Objects: Testing and Converting; Summary; Chapter 4: Data: Descriptive Statistics and Tabulation; Summary Commands; Summarizing Samples; Summary Tables; Summary; Chapter 5: Data: Distribution; Looking at the Distribution of Data; Summary; Chapter 6: Simple Hypothesis Testing; Using the
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Detalles

Género/Forma: Electronic books
Formato físico adicional: Print version:
Gardener, Mark.
Beginning R : The Statistical Programming Language.
Hoboken : John Wiley & Sons, ©2012
Tipo de material: Documento, Recurso en Internet
Tipo de documento: Recurso en Internet, Archivo de computadora
Todos autores / colaboradores: Mark Gardener
ISBN: 9781118226162 111822616X 9781118239377 1118239377
Número OCLC: 794663330
Notas: IndexAdvertisement.
Descripción: 1 online resource (507 pages)
Contenido: Beginning R; Contents; Introduction; Who This Book Is For; What This Book Covers; How This Book Is Structured; What You Need to Use This Book; Conventions; Source Code; Errata; p2p.wrox.com; Chapter 1: Introducing R: What It Is and How to Get It; Getting the Hang of R; Running the R Program; Finding Your Way with R; Command Packages; Summary; Chapter 2: Starting Out: Becoming Familiar with R; Some Simple Math; Reading and Getting Data into R; Viewing Named Objects; Types of Data Items; The Structure of Data Items; Examining Data Structure; Working with History Commands; Saving Your Work in R. Chapter 7: Introduction to Graphical AnalysisBox-whisker Plots; Scatter Plots; Pairs Plots (Multiple Correlation Plots); Line Charts; Pie Charts; Cleveland Dot Charts; Bar Charts; Copy Graphics to Other Applications; Summary; Chapter 8: Formula Notation and Complex Statistics; Examples of Using Formula Syntax for Basic Tests; Formula Notation in Graphics; Analysis of Variance (ANOVA); Summary; Chapter 9: Manipulating Data and Extracting Components; Creating Data for Complex Analysis; Summarizing Data; Summary; Chapter 10: Regression (Linear Modeling); Simple Linear Regression.

Resumen:

Chapter 3: Starting Out: Working; Manipulating Objects; Viewing Objects within Objects; Constructing Data Objects; Forms of Data Objects: Testing and Converting; Summary; Chapter 4: Data: Descriptive Statistics and Tabulation; Summary Commands; Summarizing Samples; Summary Tables; Summary; Chapter 5: Data: Distribution; Looking at the Distribution of Data; Summary; Chapter 6: Simple Hypothesis Testing; Using the Student's t-test; The Wilcoxon U-Test (Mann-Whitney); Paired t- and U-Tests; Correlation and Covariance; Tests for Association; Summary.

Conquer the complexities of this open source statistical languageR is fast becoming the de facto standard for statistical computing and analysis in science, business, engineering, and related fields. This book examines this complex language using simple statistical examples, showing how R operates in a user-friendly context. Both students and workers in fields that require extensive statistical analysis will find this book helpful as they learn to use R for simple summary statistics, hypothesis testing, creating graphs, regression, and much more. It covers formula notation, complex statistics.

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