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E-raamat: Beginner's Guide to R

  • Formaat: EPUB+DRM
  • Sari: Use R!
  • Ilmumisaeg: 24-Jun-2009
  • Kirjastus: Springer-Verlag New York Inc.
  • Keel: eng
  • ISBN-13: 9780387938370
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  • Formaat: EPUB+DRM
  • Sari: Use R!
  • Ilmumisaeg: 24-Jun-2009
  • Kirjastus: Springer-Verlag New York Inc.
  • Keel: eng
  • ISBN-13: 9780387938370
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Based on their extensive experience with teaching R and statistics to applied scientists, the authors provide a beginner's guide to R. To avoid the difficulty of teaching R and statistics at the same time, statistical methods are kept to a minimum. The text covers how to download and install R, import and manage data, elementary plotting, an introduction to functions, advanced plotting, and common beginner mistakes. This book contains everything you need to know to get started with R."Its biggest advantage is that it aims only to teach R...It organizes R commands very efficiently, with much teaching guidance included. I would describe this book as being handy--it's the kind of book that you want to keep in your jacket pocket or backpack all the time, ready for use, like a Swiss Army knife." (Loveday Conquest, University of Washington)"Whilst several books focus on learning statistics in R..., the authors of this book fill a gap in the market by focusing on learning R whilst almost completely avoiding any statistical jargon...The fact that the authors have very extensive experience of teaching R to absolute beginners shines throughout." (Mark Mainwaring, Lancaster University) "Exactly what is needed...This is great, nice work. I love the ecological/biological examples; they will be an enormous help." (Andrew J. Tyne, University of Nebraska-Lincoln)

Arvustused

From the reviews:

A Beginners Guide to R is just what its title implies, a quick-start guide for the newest R users. A unique feature of this welcome addition to Springers Use R! series is that it is devoted solely to getting the user up and running on R. Unlike other texts geared towards R beginners, this text does not make the mistake of trying to simultaneously teach statistics. there are straightforward homework exercises provided throughout, and the data sets can be downloaded from the authors website A Beginners Guide to R is an essential resource for the R novice, whether an undergraduate learning statistics for the first time or a seasoned statistician biting the bullet and making the switch to R. (The R Journal Vol. 2/1, June 2010)

most suitable for an advanced beginner or a user who needs an introduction to a wide variety of graphical methods. Overall, the book does most things quite well. It shows the beginner how to install R. how to load data into R, how to perform some subsetting operations including the sorting of data and most of all how to plot data using a variety of methods. Throughout, all methods and code are will illustrated and can be easily replicated by anyone using the book. I learned quite a number of things about R that I did not previously know. Consequently, I would recommend the book not only for the students who need to learn R, but for professionals who need to enhance their basic working knowledge of R." (Math Geosci 2010, 42: 133137)

The book has many admirable features. It introduces key commands in easy stages. Each chapter has a number of illustrative examples, lucidly explained, and ends with a review of what has been covered. Chapters also contain exercises at the end that reinforce the examples provided. useful work for self-study or for an introductory course, allowing readers to apply their knowledge of the language to begin learning how to use R for statistical analysis or other purposes. Summing Up: Highly recommended. All levels of readership. (R. Bharath, Choice, Vol. 47 (11), July, 2010)

This book explains how to create datasets, variables, functions and plots using R. It is not a simple book though. somewhat dense and covers each topic thoroughly. best to follow every example. I found this book to be well written for its intended audience and purpose. I had no difficulty reading it or following the examples. This approach will give you a good foundation for using R in your own work and advancing to other books about specific analyses and procedures. (Mark Bailey, Technometrics, Vol. 53 (1), February, 2011)

This book has a very clear objective. this is a popular book about the R statistical software. The book is true to its goal of being a text for the absolute beginner with easy to follow explanations, examples to program, and exercises to build skill. The reader who takes advantages of the available data files and R text editors will find this to be a very instructive book. It will definitely increase your desire to learn and use R in the future. (Brandon Alleman, The American Statistician, May, 2011)

Preface vii
Acknowledgements ix
1 Introduction 1
1.1 What Is R?
1
1.2 Downloading and Installing R
2
1.3 An Initial Impression
4
1.4 Script Code
7
1.4.1 The Art of Programming
7
1.4.2 Documenting Script Code
8
1.5 Graphing Facilities in R
10
1.6 Editors
12
1.7 Help Files and Newsgroups
13
1.8 Packages
16
1.8.1 Packages Included with the Base Installation
16
1.8.2 Packages Not Included with the Base Installation
17
1.9 General Issues in R
19
1.9.1 Quitting R and Setting the Working Directory
21
1.10 A History and a Literature Overview
22
1.10.1 A Short Historical Overview of R
22
1.10.2 Books on R and Books Using R
22
1.11 Using This Book
24
1.11.1 If You Are an Instructor
25
1.11.2 If You Are an Interested Reader with Limited R Experience
25
1.11.3 If You Are an R Expert
25
1.11.4 If You Are Afraid of R
25
1.12 Citing R and Citing Packages
26
1.13 Which R Functions Did We Learn"
27
2 Getting Data into R 29
2.1 First Steps in R
29
2.1.1 Typing in Small Datasets
29
2.1.2 Concatenating Data with the c Function
31
2.1.3 Combining Variables with the c, cbind, and rbind Functions
34
2.1.4 Combining Data with the vector Function*
39
2.1.5 Combining Data Using a Matrix*
39
2.1.6 Combining Data with the data. frame Function
42
2.1.7 Combining Data Using the list Function*
43
2.2 Importing Data
46
2.2.1 Importing Excel Data
47
2.2.2 Accessing Data from Other Statistical Packages**
51
2.2.3 Accessing a Database***
52
2.3 Which R Functions Did We Learn?
54
2.4 Exercises
54
3 Accessing Variables and Managing Subsets of Data 57
3.1 Accessing Variables from a Data Frame
57
3.1.1 The str Function
59
3.1.2 The Data Argument in a Function
60
3.1.3 The $ Sign
61
3.1.4 The attach Function
62
3.2 Accessing Subsets of Data
63
3.2.1 Sorting the Data
66
3.3 Combining Two Datasets with a Common Identifier
67
3.4 Exporting Data
69
3.5 Recoding Categorical Variables
71
3.6 Which R Functions Did We Learn?
74
3.7 Exercises
74
4 Simple Functions 77
4.1 The tapply Function
77
4.1.1 Calculating the Mean Per Transect
78
4.1.2 Calculating the Mean Per Transect More Efficiently
79
4.2 The sapply and lapply Functions
80
4.3 The summary Function
81
4.4 The table Function
82
4.5 Which R Functions Did We Learn?
84
4.6 Exercises
84
5 An Introduction to Basic Plotting Tools 85
5.1 The plot Function
85
5.2 Symbols, Colours, and Sizes
88
5.2.1 Changing Plotting Characters
88
5.2.2 Changing the Colour of Plotting Symbols
92
5.2.3 Altering the Size of Plotting Symbols
93
5.3 Adding a Smoothing Line
95
5.4 Which R Functions Did We Learn?
97
5.5 Exercises
97
6 Loops and Functions 99
6.1 Introduction to Loops
99
6.2 Loops
101
6.2.1 Be the Architect of Your Code
102
6.2.2 Step 1: Importing the Data
102
6.2.3 Steps 2 and 3: Making the Scatterplot and Adding Labels
103
6.2.4 Step 4: Designing General Code
104
6.2.5 Step 5: Saving the Graph
105
6.2.6 Step 6: Constructing the Loop
107
6.3 Functions
108
6.3.1 Zeros and NAs
108
6.3.2 Technical Information
110
6.3.3 A Second Example: Zeros and NAs
111
6.3.4 A Function with Multiple Arguments
113
6.3.5 Foolproof Functions
115
6.4 More on Functions and the if Statement
117
6.4.1 Playing the Architect Again
118
6.4.2 Step 1: Importing and Assessing the Data
118
6.4.3 Step 2: Total Abundance per Site
119
6.4.4 Step 3: Richness per Site
120
6.4.5 Step 4: Shannon Index per Site
121
6.4.6 Step 5: Combining Code
122
6.4.7 Step 6: Putting the Code into a Function
122
6.5 Which R Functions Did We Learn?
125
6.6 Exercises
125
7 Graphing Tools 127
7.1 The Pie Chart
127
7.1.1 Pie Chart Showing Avian Influenza Data
127
7.1.2 The par Function
130
7.2 The Bar Chart and Strip Chart
131
7.2.1 The Bar Chart Using the Avian Influenza Data
131
7.2.2 A Bar Chart Showing Mean Values with Standard Deviations
133
7.2.3 The Strip Chart for the Bcnthic Data
135
7.3 Boxplot
137
7.3.1 Boxplots Showing the Owl Data
137
7.3.2 Boxplots Showing the Bcnthic Data
140
7.4 Cleveland Dotplots
141
7.4.1 Adding the Mean to a Cleveland Dotplot
143
7.5 Revisiting the plot Function
145
7.5.1 The Generic plot Function
145
7.5.2 More Options for the plot Function
146
7.5.3 Adding Extra Points, Text, and Lines
148
7.5.4 Using type = "n"
149
7.5.5 Legends
150
7.5.6 Identifying Points
152
7.5.7 Changing Fonts and Font Size*
153
7.5.8 Adding Special Characters
153
7.5.9 Other Useful Functions
154
7.6 The Pairplot
155
7.6.1 Panel Functions
156
7.7 The Coplot
157
7.7.1 A Coplot with a Single Conditioning Variable
157
7.7.2 The Coplot with Two Conditioning Variables
161
7.7.3 Jazzing Up the Coplot*
162
7.8 Combining Types of Plots*
164
7.9 Which R Functions Did We Learn?
166
7.10 Exercises
167
8 An Introduction to the Lattice Package 169
8.1 High-Level Lattice Functions
169
8.2 Multipanel Scatterplots: xyplot
170
8.3 Multipanel Boxplots: bwplot
173
8.4 Multipanel Cleveland Dotplots: dotplot
174
8.5 Multipanel Histograms: histogram
176
8.6 Panel Functions
177
8.6.1 First Panel Function Example
177
8.6.2 Second Panel Function Example
179
8.6.3 Third Panel Function Example*
181
8.7 3-D Scatterplots and Surface and Contour Plots
184
8.8 Frequently Asked Questions
185
8.8.1 How to Change the Panel Order?
186
8.8.2 How to Change Axes Limits and Tick Marks?
188
8.8.3 Multiple Graph Lines in a Single Panel
189
8.8.4 Plotting from Within a Loop*
190
8.8.5 Updating a Plot
191
8.9 Where to Go from Here?
191
8.10 Which R Functions Did We Learn?
192
8.11 Exercises
192
9 Common R Mistakes 195
9.1 Problems Importing Data
195
9.1.1 Errors in the Source File
195
9.1.2 Decimal Point or Comma Separation
195
9.1.3 Directory Names
197
9.2 Attach Misery
197
9.2.1 Entering the Same attach Command Twice
197
9.2.2 Attaching Two Data Frames Containing the Same Variable Names
198
9.2.3 Attaching a Data Frame and Demo Data
199
9.2.4 Making Changes to a Data Frame After Applying the attach Function
200
9.3 Non-attach Misery
201
9 4 The Log of Zero
202
9.5 Miscellaneous Errors
203
9.5.1 The Difference Between 1 and 1
203
9.5.2 The Colour of 0
203
9.6 Mistakenly Saved the R Workspace
204
References 207
Index 211
Alain F. Zuur is senior statistician and director of Highland Statistics Ltd., a statistical consultancy company based in the UK. He has taught statistics to more than 5000 ecologists. He is honorary research fellow in the School of Biological Sciences, Oceanlab, at the University of Aberdeen, UK.Elena N. Ieno is senior marine biologist and co-director at Highland Statistics Ltd. She has been involved in guiding PhD students on the design and analysis of ecological data. She is honorary research fellow in the School of Biological Sciences, Oceanlab, at the University of Aberdeen, UK.

Erik H.W.G. Meesters is a researcher at the Dutch Institute for Marine Resources and Ecosystem Studies (IMARES). He specializes in coral reef ecology and applied statistics and conducts research on North Sea benthos and seal ecology.