04993nam 2200769 a 450 991096368000332120210719162050.09786613661579978128068463012806846319781118226162111822616X(CKB)2550000000103621(EBL)836575(OCoLC)794663330(SSID)ssj0000676789(PQKBManifestationID)12322620(PQKBTitleCode)TC0000676789(PQKBWorkID)10685332(PQKB)11408425(Au-PeEL)EBL836575(CaPaEBR)ebr10565178(CaONFJC)MIL366157(PPN)272714496(OCoLC)816348896(OCoLC)ocn816348896 (FR-PaCSA)88944177(CaSebORM)9781118239377(MiAaPQ)EBC836575(FRCYB88944177)88944177(Perlego)2753049(EXLCZ)99255000000010362120120612d2012 uy 0engur|n|---|||||txtccrBeginning R the statistical programming language /Mark Gardener1st editionIndianapolis John Wiley & Sons20121 online resource (507 p.)Wrox programmer to programmerIncludes index.9781118239377 1118239377 9781118164303 111816430X 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 RSummaryChapter 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; SummaryChapter 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 RegressionMultiple RegressionCurvilinear Regression; Plotting Linear Models and Curve Fitting; Summarizing Regression Models; Summary; Chapter 11: More About Graphs; Adding Elements to Existing Plots; Matrix Plots (Multiple Series on One Graph); Multiple Plots in One Window; Exporting Graphs; Summary; Chapter 12: Writing Your Own Scripts: Beginning to Program; Copy and Paste Scripts; Creating Simple Functions; Making Source Code; Summary; Appendix: Answers to Exercises; Chapter 1; Chapter 2; Chapter 3; Chapter 4; Chapter 5; Chapter 6; Chapter 7; Chapter 8; Chapter 9; Chapter 10; Chapter 11; Chapter 12IndexAdvertisementConquer the complexities of this open source statistical language R 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 sR (Computer program language)StatisticsData processingR (Computer program language)StatisticsData processing.519.50285536Gardener Mark517232MiAaPQMiAaPQMiAaPQBOOK9910963680003321Beginning R4335822UNINA