Beginning R : The Statistical Programming Language
Hoboken : John Wiley & Sons,c2012
|ISBN：||9781118226162 111822616X 9781118239377 1118239377|
|注記：||Description based upon print version of record.
|物理形態：||1 online resource (507 p.)|
|コンテンツ：||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 Multiple 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 12|
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,