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J. Owen  \nDepartment of Mathematics and Computer Science University of Richmond  \nVolume  \n10 20 30 40 50 60 70  \nBlack Cherry Trees  \n\n| | \u003Cbr>large residual |\n| --- | --- |\n| |  |\n\n65 70 75 80 85  \nHeight  \nConsider a log transform on Volume  \n􀂔 W. J. Owen 2010. A license is granted for personal study and classroom use. Redistribution in any other form is prohibited. Comments/questions can be sent to[wowen@richmond.edu](wowen@richmond.edu) .  \n“Humans are good, she knew, at discerning subtle patterns that are really there, but equally so at imagining them when they are altogether absent.” --Carl Sagan (1985) Contact  \nPreface  \nThis document is an introduction to the program R. Although it could be a companion manuscript for an introductory statistics course, it is designed to be used in a course on mathematical statistics.  \nThe purpose of this document is to introduce many of the basic concepts and nuances of the language so that users can avoid a slow learning curve. The best way to use this manual is to use a “learn by doing” approach. Try the examples and exercises in the Chapters and aim to understand what works and what doesn’t. In addition, some topics and special features of R have been added for the interested reader and to facilitate the subject matter.  \nThe most up-to-date version of this manuscript can be found at [http://www.mathcs.richmond.edu/](http://www.mathcs.richmond.edu/)~wowen/TheRGuide.pdf.  \nFont Conventions  \nThis document is typed using Times New Roman font. However, when R code is presented, referenced, or when R output is given, we use 10 point Bold Courier New Font.  \nAcknowledgements  \nMuch of this document started from class handouts. Those were augmented by including new material and prose to add continuity between the topics and to expand on various themes. We thank the large group of R contributors and other existing sources of documentation where some inspiration and ideas used in this document were borrowed. We also acknowledge the R Core team for their hard work with the software.  \nContents  \nPage  \n1. Overview and history  \n1.1 What is R?  \n1.2 Starting and Quitting R  \n1.3 A Simple Example: the c() Function and Vector Assignment  \n1.4 The Workspace  \n1.5 Getting Help  \n1.6 More on Functions in R  \n1.7 Printing and Saving Your Work  \n1.8 Other Sources of Reference  \n1.9 Exercises  \n2. My Big Fat Greek Calculator  \n2.1 Basic Math  \n2.2 Vector Arithmetic  \n2.3 Matrix Operations  \n2.4 Exercises  \n3. Getting Data into R  \n3.1 Sequences  \n3.2 Reading in Data: Single Vectors  \n3.3 Data frames  \n3.3.1 Creating Data Frames  \n3.3.2 Datasets Included with R  \n3.3.3 Accessing Portions of a Data Frame  \n3.3.4 Reading in Datasets  \n3.3.5 Data files in formats other than ASCII text  \n3.4 Exercises  \n4. Introduction to Graphics  \n4.1 The Graphics Window  \n4.2 Two Generic Graphing Functions  \n4.2.1 The plot() function  \n4.2.2 The curve() function  \n4.3 Graph Embellishments  \n4.4 Changing Graphics Parameters  \n4.5 Exercises  \n1  \n1  \n1  \n2  \n3  \n4  \n5  \n6  \n7  \n7  \n8  \n8  \n9  \n10  \n11  \n12  \n12  \n13  \n14  \n14  \n15  \n16  \n18  \n18  \n18  \n19  \n19  \n19  \n19  \n20  \n21  \n21  \n22  \n5. Summarizing Data 23  \n5.1 Numerical Summaries 23  \n5.2 Graphical Summaries 24  \n5.3 Exercises 28  \n6. Probability, Distributions, and Simulation 29  \n6.1 Distribution Functions in R 29  \n6.2 A Simulation Application: Monte Carlo Integration 30  \n6.3 Graphing Distributions 30  \n6.3.1 Discrete Distributions 31  \n6.3.2 Continuous Distributions 32  \n6.4 Random Sampling 33  \n6.5 Exercises 34  \n7. Statistical Methods 35  \n7.1 One and Two-sample t-tests 35  \n7.2 Analysis of Variance (ANOVA) 37  \n7.2.1 Factor Variables 37  \n7.2.2 The ANOVA Table 39  \n7.2.3 Multiple Comparisons 39  \n7.3 Linear Regression 40  \n7.4 Chi-square Tests 44  \n7.4.1 Goodness ofFit 44  \n7.4.2 Contingency Tables 45  \n7.5 Other Tests 46  \n8. Advanced Topics 48  \n8.1 Scripts 48  \n8.2 Control Flow 48  \n8.3 Writing Functions 50  \n8.4 Numer","cbCaiqpXqKMWTBj5","https://ap.wps.com/l/cbCaiqpXqKMWTBj5","pdf",249026,61,"English","# Overview and history\n## What is R?\n## Starting and Quitting R\n## Getting Help\n# My Big Fat Greek Calculator\n## Basic Math\n## Vector Arithmetic\n## Matrix Operations\n# Getting Data into R\n## Sequences\n## Reading in Data: Single Vectors\n## Data frames\n# Introduction to Graphics\n## The Graphics Window\n## Two Generic Graphing Functions\n## Graph Embellishments\n# Summarizing Data\n## Numerical Summaries\n## Graphical Summaries\n# Probability, Distributions, and Simulation\n## Distribution Functions in R\n## A Simulation Application: Monte Carlo Integration\n## Random Sampling\n# Statistical Methods\n## One and Two-sample t-tests\n## Analysis of Variance (ANOVA)\n## Linear Regression\n## Chi-square Tests\n# Advanced Topics\n## Scripts\n## Control Flow\n## Writing Functions","[{\"question\":\"What is the purpose of The R Guide and who is it designed for?\",\"answer\":\"It introduces R and is designed for a course on mathematical statistics. 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