Introductory statistics with R:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer
[2008]
|
| Ausgabe: | Second edition |
| Schriftenreihe: | Statistics and computing
|
| Schlagworte: | |
| Online-Zugang: | Inhaltstext Inhaltsverzeichnis |
| Beschreibung: | xvi, 363 Seiten Illustrationen, Diagramme |
| ISBN: | 9780387790534 0387790535 |
Internformat
MARC
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| 100 | 1 | |a Dalgaard, Peter |d 1959- |e Verfasser |0 (DE-588)1229995811 |4 aut | |
| 245 | 1 | 0 | |a Introductory statistics with R |c Peter Dalgaard |
| 250 | |a Second edition | ||
| 264 | 1 | |a New York, NY |b Springer |c [2008] | |
| 264 | 4 | |c © 2008 | |
| 300 | |a xvi, 363 Seiten |b Illustrationen, Diagramme | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Statistics and computing | |
| 650 | 7 | |a Estatística computacional |2 larpcal | |
| 650 | 4 | |a R (Langage de programmation) | |
| 650 | 7 | |a R (computerprogramma) |2 gtt | |
| 650 | 7 | |a Software estatístico para microcomputadores |2 larpcal | |
| 650 | 7 | |a Statistiek |2 gtt | |
| 650 | 4 | |a Statistique - Informatique | |
| 650 | 4 | |a Datenverarbeitung | |
| 650 | 4 | |a Statistik | |
| 650 | 4 | |a R (Computer program language) | |
| 650 | 4 | |a Statistics |x Data processing | |
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Datensatz im Suchindex
| DE-BY-863_location | 1000 |
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| DE-BY-FWS_katkey | 629186 |
| DE-BY-FWS_media_number | 083101386973 |
| _version_ | 1806528638147887104 |
| adam_text |
Contents
Preface
vii
1 Basics 1
1.1
First
steps
. 1
1.1.1
An overgrown calculator
. 3
1.1.2
Assignments
. 3
1.1.3
Vectorized arithmetic
. 4
1.1.4
Standard procedures
. 6
1.1.5
Graphics
. 7
1.2
R
language essentials
. 9
1.2.1
Expressions and objects
. 9
1.2.2
Functions and arguments
. 11
1.2.3
Vectors
. 12
1.2.4
Quoting and escape sequences
. 13
1.2.5
Missing values
. 14
1.2.6
Functions that create vectors
. 14
1.2.7
Matrices and arrays
. 16
1.2.8
Factors
. 18
1.2.9
Lists
. 19
1.2.10
Data frames
. 20
1.2.11
Indexing
. 21
1.2.12
Conditional selection
. 22
1.2.13
Indexing of data frames
. 23
1.2.14
Grouped data and data frames
. 25
xii Contents
1.2.15
Implicit
loops
. 26
1.2.16
Sorting
. 27
1.3
Exercises
. 28
2
The
R
environment
31
2.1
Session management
. 31
2.1.1
The workspace
. 31
2.1.2
Textual output
. 32
2.1.3
Scripting
. 33
2.1.4
Getting help
. 34
2.1.5
Packages
. 35
2.1.6
Built-in data
. 35
2.1.7
attach and detach
. 36
2.1.8
subset, transform, and within
. 37
2.2
The graphics subsystem
. 39
2.2.1
Plotlayout
. 39
2.2.2
Building a plot from pieces
. 40
2.2.3
Using par
. 42
2.2.4
Combining plots
. 42
2.3
R
programming
. 44
2.3.1
Flow control
. 44
2.3.2
Classes and generic functions
. 46
2.4
Data entry
. 46
2.4.1
Reading from a text file
. 47
2.4.2
Further details on read, table
. 50
2.4.3
The data editor
. 51
2.4.4
Interfacing to other programs
. 52
2.5
Exercises
. 53
3
Probability and distributions
55
3.1
Random sampling
. 55
3.2
Probability calculations and combinatorics
. 56
3.3
Discrete distributions
. 57
3.4
Continuous distributions
. 58
3.5
The built-in distributions in
R
. 59
3.5.1
Densities
. 59
3.5.2
Cumulative distribution functions
. 62
3.5.3
Quantiles
. 63
3.5.4
Random numbers
. 64
3.6
Exercises
. 65
4
Descriptive statistics and graphics
67
4.1
Summary statistics for a single group
. 67
4.2
Graphical display of distributions
. 71
4.2.1
Histograms
. 71
Contents xiii
4.2.2
Empirical cumulative distribution
. 73
4.2.3
Q-Q plots
. 74
4.2.4
Boxplots
. 75
4.3
Summary statistics by groups
. 75
4.4
Graphics for grouped data
. 79
4.4.1
Histograms
. 79
4.4.2
Parallel boxplots
. 80
4.4.3 Stripcharts. 81
4.5
Tables
. 83
4.5.1
Generating tables
. 83
4.5.2
Marginal tables and relative frequency
. 87
4.6
Graphical display of tables
. 89
4.6.1
Barplots
. 89
4.6.2
Dotcharts
. 91
4.6.3
Piecharts
. 92
4.7
Exercises
. 93
5
One- and two-sample tests
95
5.1
One-sample
t
test
. 95
5.2
Wilcoxon signed-rank test
. 99
5.3
Two-sample
ŕ
test
. 100
5.4
Comparison of variances
. 103
5.5
Two-sample Wilcoxon test
. 103
5.6
The paired
t
test
. 104
5.7
The matched-pairs Wilcoxon test
. 106
5.8
Exercises
. 107
6
Regression and correlation
109
6.1
Simple linear regression
. 109
6.2
Residuals and fitted values
. 113
6.3
Prediction and confidence bands
. 117
6.4
Correlation
. 120
6.4.1
Pearson correlation
. 121
6.4.2
Spearman's
p
. 123
6.4.3
Kendall's
τ
. 124
6.5
Exercises
. 124
7
Analysis of variance and the Kruskal-Wallis test
127
7.1
One-way analysis of variance
. 127
7.1.1
Pairwise comparisons and multiple testing
. . . 131
7.1.2
Relaxing the variance assumption
. 133
7.1.3
Graphical presentation
. 134
7.1.4
Bartlett's test
. 136
7.2
Kruskal-Wallis test
. 136
7.3
Two-way analysis of variance
. 137
xiv Contents
7.3.1 Graphics
for repeated measurements
. 140
7.4
The Friedman test
. 141
7.5
The ANOVA table in regression analysis
. 141
7.6
Exercises
. 143
8
Tabular data
145
8.1
Single proportions
. 145
8.2
Two independent proportions
. 147
8.3
к
proportions, test for trend
. 149
8.4
r
xc
tables
. 151
8.5
Exercises
. 153
9
Power and the computation of sample size
155
9.1
The principles of power calculations
. 155
9.1.1
Power of one-sample and paired
t
tests
. 156
9.1.2
Power of two-sample
ŕ
test
. 158
9.1.3
Approximate methods
. 158
9.1.4
Power of comparisons of proportions
. 159
9.2
Two-sample problems
. 159
9.3
One-sample problems and paired tests
. 161
9.4
Comparison of proportions
. 161
9.5
Exercises
. 162
10
Advanced data handling
163
10.1
Recoding variables
. 163
10.1.1
The cut function
. 163
10.1.2
Manipulating factor levels
. 165
10.1.3
Working with dates
. 166
10.1.4
Recoding multiple variables
. 169
10.2
Conditional calculations
. 170
10.3
Combining and restructuring data frames
. 171
10.3.1
Appending frames
. 172
10.3.2
Merging data frames
. 173
10.3.3
Reshaping data frames
. 175
10.4
Per-group and per-case procedures
. 178
10.5
Time splitting
. 179
10.6
Exercises
. 183
11
Multiple regression
185
11.1
Plotting multivariate data
. 185
11.2
Model specification and output
. 187
11.3
Model search
. 190
11.4
Exercises
. 193
Contents xv
12 Linear
models
195
12.1
Polynomial regression
. 196
12.2
Regression through the origin
. 198
12.3
Design matrices and dummy variables
. 200
12.4
Linearity over groups
. 202
12.5
Interactions
. 206
12.6
Two-way ANOVA with replication
. 207
12.7
Analysis of covariance
. 208
12.7.1
Graphical description
. 209
12.7.2
Comparison of regression lines
. 212
12.8
Diagnostics
. 218
12.9
Exercises
. 224
13
Logistic regression
227
13.1
Generalized linear models
. 228
13.2
Logistic regression on tabular data
. 229
13.2.1
The analysis of deviance table
. 234
13.2.2
Connection to test for trend
. 235
13.3
Likelihood profiling
. 237
13.4
Presentation as odds-ratio estimates
. 239
13.5
Logistic regression using raw data
. 239
13.6
Prediction
. 241
13.7
Model checking
. 242
13.8
Exercises
. 247
14
Survival analysis
249
14.1
Essential concepts
. 249
14.2
Survival objects
. 250
14.3
Kaplan-Meier estimates
. 251
14.4
The log-rank test
. 254
14.5
The Cox proportional hazards model
. 256
14.6
Exercises
. 258
15
Rates and
Poisson
regression
259
15.1
Basic ideas
. 259
15.1.1
The
Poisson
distribution
. 260
15.1.2
Survival analysis with constant hazard
. 260
15.2
Fitting
Poisson
models
. 262
15.3
Computing rates
. 266
15.4
Models with piecewise constant intensities
. 270
15.5
Exercises
. 274
16
Nonlinear curve fitting
275
16.1
Basic usage
. 276
16.2
Finding starting values
. 278
xvi Contents
16.3
Self-starting models
. 284
16.4
Profiling
. 285
16.5
Finer control of the fitting algorithm
. 287
16.6
Exercises
. 288
A Obtaining and installing
R
and the ISwR package
289
В
Data sets in the ISwR package
293
С
Compendium
325
D
Answers to exercises
337
Bibliography
355
Index
357 |
| adam_txt |
Contents
Preface
vii
1 Basics 1
1.1
First
steps
. 1
1.1.1
An overgrown calculator
. 3
1.1.2
Assignments
. 3
1.1.3
Vectorized arithmetic
. 4
1.1.4
Standard procedures
. 6
1.1.5
Graphics
. 7
1.2
R
language essentials
. 9
1.2.1
Expressions and objects
. 9
1.2.2
Functions and arguments
. 11
1.2.3
Vectors
. 12
1.2.4
Quoting and escape sequences
. 13
1.2.5
Missing values
. 14
1.2.6
Functions that create vectors
. 14
1.2.7
Matrices and arrays
. 16
1.2.8
Factors
. 18
1.2.9
Lists
. 19
1.2.10
Data frames
. 20
1.2.11
Indexing
. 21
1.2.12
Conditional selection
. 22
1.2.13
Indexing of data frames
. 23
1.2.14
Grouped data and data frames
. 25
xii Contents
1.2.15
Implicit
loops
. 26
1.2.16
Sorting
. 27
1.3
Exercises
. 28
2
The
R
environment
31
2.1
Session management
. 31
2.1.1
The workspace
. 31
2.1.2
Textual output
. 32
2.1.3
Scripting
. 33
2.1.4
Getting help
. 34
2.1.5
Packages
. 35
2.1.6
Built-in data
. 35
2.1.7
attach and detach
. 36
2.1.8
subset, transform, and within
. 37
2.2
The graphics subsystem
. 39
2.2.1
Plotlayout
. 39
2.2.2
Building a plot from pieces
. 40
2.2.3
Using par
. 42
2.2.4
Combining plots
. 42
2.3
R
programming
. 44
2.3.1
Flow control
. 44
2.3.2
Classes and generic functions
. 46
2.4
Data entry
. 46
2.4.1
Reading from a text file
. 47
2.4.2
Further details on read, table
. 50
2.4.3
The data editor
. 51
2.4.4
Interfacing to other programs
. 52
2.5
Exercises
. 53
3
Probability and distributions
55
3.1
Random sampling
. 55
3.2
Probability calculations and combinatorics
. 56
3.3
Discrete distributions
. 57
3.4
Continuous distributions
. 58
3.5
The built-in distributions in
R
. 59
3.5.1
Densities
. 59
3.5.2
Cumulative distribution functions
. 62
3.5.3
Quantiles
. 63
3.5.4
Random numbers
. 64
3.6
Exercises
. 65
4
Descriptive statistics and graphics
67
4.1
Summary statistics for a single group
. 67
4.2
Graphical display of distributions
. 71
4.2.1
Histograms
. 71
Contents xiii
4.2.2
Empirical cumulative distribution
. 73
4.2.3
Q-Q plots
. 74
4.2.4
Boxplots
. 75
4.3
Summary statistics by groups
. 75
4.4
Graphics for grouped data
. 79
4.4.1
Histograms
. 79
4.4.2
Parallel boxplots
. 80
4.4.3 Stripcharts. 81
4.5
Tables
. 83
4.5.1
Generating tables
. 83
4.5.2
Marginal tables and relative frequency
. 87
4.6
Graphical display of tables
. 89
4.6.1
Barplots
. 89
4.6.2
Dotcharts
. 91
4.6.3
Piecharts
. 92
4.7
Exercises
. 93
5
One- and two-sample tests
95
5.1
One-sample
t
test
. 95
5.2
Wilcoxon signed-rank test
. 99
5.3
Two-sample
ŕ
test
. 100
5.4
Comparison of variances
. 103
5.5
Two-sample Wilcoxon test
. 103
5.6
The paired
t
test
. 104
5.7
The matched-pairs Wilcoxon test
. 106
5.8
Exercises
. 107
6
Regression and correlation
109
6.1
Simple linear regression
. 109
6.2
Residuals and fitted values
. 113
6.3
Prediction and confidence bands
. 117
6.4
Correlation
. 120
6.4.1
Pearson correlation
. 121
6.4.2
Spearman's
p
. 123
6.4.3
Kendall's
τ
. 124
6.5
Exercises
. 124
7
Analysis of variance and the Kruskal-Wallis test
127
7.1
One-way analysis of variance
. 127
7.1.1
Pairwise comparisons and multiple testing
. . . 131
7.1.2
Relaxing the variance assumption
. 133
7.1.3
Graphical presentation
. 134
7.1.4
Bartlett's test
. 136
7.2
Kruskal-Wallis test
. 136
7.3
Two-way analysis of variance
. 137
xiv Contents
7.3.1 Graphics
for repeated measurements
. 140
7.4
The Friedman test
. 141
7.5
The ANOVA table in regression analysis
. 141
7.6
Exercises
. 143
8
Tabular data
145
8.1
Single proportions
. 145
8.2
Two independent proportions
. 147
8.3
к
proportions, test for trend
. 149
8.4
r
xc
tables
. 151
8.5
Exercises
. 153
9
Power and the computation of sample size
155
9.1
The principles of power calculations
. 155
9.1.1
Power of one-sample and paired
t
tests
. 156
9.1.2
Power of two-sample
ŕ
test
. 158
9.1.3
Approximate methods
. 158
9.1.4
Power of comparisons of proportions
. 159
9.2
Two-sample problems
. 159
9.3
One-sample problems and paired tests
. 161
9.4
Comparison of proportions
. 161
9.5
Exercises
. 162
10
Advanced data handling
163
10.1
Recoding variables
. 163
10.1.1
The cut function
. 163
10.1.2
Manipulating factor levels
. 165
10.1.3
Working with dates
. 166
10.1.4
Recoding multiple variables
. 169
10.2
Conditional calculations
. 170
10.3
Combining and restructuring data frames
. 171
10.3.1
Appending frames
. 172
10.3.2
Merging data frames
. 173
10.3.3
Reshaping data frames
. 175
10.4
Per-group and per-case procedures
. 178
10.5
Time splitting
. 179
10.6
Exercises
. 183
11
Multiple regression
185
11.1
Plotting multivariate data
. 185
11.2
Model specification and output
. 187
11.3
Model search
. 190
11.4
Exercises
. 193
Contents xv
12 Linear
models
195
12.1
Polynomial regression
. 196
12.2
Regression through the origin
. 198
12.3
Design matrices and dummy variables
. 200
12.4
Linearity over groups
. 202
12.5
Interactions
. 206
12.6
Two-way ANOVA with replication
. 207
12.7
Analysis of covariance
. 208
12.7.1
Graphical description
. 209
12.7.2
Comparison of regression lines
. 212
12.8
Diagnostics
. 218
12.9
Exercises
. 224
13
Logistic regression
227
13.1
Generalized linear models
. 228
13.2
Logistic regression on tabular data
. 229
13.2.1
The analysis of deviance table
. 234
13.2.2
Connection to test for trend
. 235
13.3
Likelihood profiling
. 237
13.4
Presentation as odds-ratio estimates
. 239
13.5
Logistic regression using raw data
. 239
13.6
Prediction
. 241
13.7
Model checking
. 242
13.8
Exercises
. 247
14
Survival analysis
249
14.1
Essential concepts
. 249
14.2
Survival objects
. 250
14.3
Kaplan-Meier estimates
. 251
14.4
The log-rank test
. 254
14.5
The Cox proportional hazards model
. 256
14.6
Exercises
. 258
15
Rates and
Poisson
regression
259
15.1
Basic ideas
. 259
15.1.1
The
Poisson
distribution
. 260
15.1.2
Survival analysis with constant hazard
. 260
15.2
Fitting
Poisson
models
. 262
15.3
Computing rates
. 266
15.4
Models with piecewise constant intensities
. 270
15.5
Exercises
. 274
16
Nonlinear curve fitting
275
16.1
Basic usage
. 276
16.2
Finding starting values
. 278
xvi Contents
16.3
Self-starting models
. 284
16.4
Profiling
. 285
16.5
Finer control of the fitting algorithm
. 287
16.6
Exercises
. 288
A Obtaining and installing
R
and the ISwR package
289
В
Data sets in the ISwR package
293
С
Compendium
325
D
Answers to exercises
337
Bibliography
355
Index
357 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Dalgaard, Peter 1959- |
| author_GND | (DE-588)1229995811 |
| author_facet | Dalgaard, Peter 1959- |
| author_role | aut |
| author_sort | Dalgaard, Peter 1959- |
| author_variant | p d pd |
| building | Verbundindex |
| bvnumber | BV023329601 |
| callnumber-first | Q - Science |
| callnumber-label | QA276 |
| callnumber-raw | QA276.45.R3 |
| callnumber-search | QA276.45.R3 |
| callnumber-sort | QA 3276.45 R3 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | CM 4400 MR 2200 QH 231 ST 250 ST 600 ST 601 SK 850 |
| classification_tum | SOZ 710f DAT 368f MAT 620f |
| ctrlnum | (OCoLC)253729714 (DE-599)DNB988178001 |
| dewey-full | 519.50285/5133 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.50285/5133 |
| dewey-search | 519.50285/5133 |
| dewey-sort | 3519.50285 45133 |
| dewey-tens | 510 - Mathematics |
| discipline | Informatik Soziologie Psychologie Mathematik Wirtschaftswissenschaften |
| discipline_str_mv | Informatik Soziologie Psychologie Mathematik Wirtschaftswissenschaften |
| edition | Second edition |
| format | Book |
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| id | DE-604.BV023329601 |
| illustrated | Illustrated |
| index_date | 2024-07-02T20:57:06Z |
| indexdate | 2024-08-05T08:39:23Z |
| institution | BVB |
| isbn | 9780387790534 0387790535 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016513553 |
| oclc_num | 253729714 |
| open_access_boolean | |
| owner | DE-703 DE-384 DE-M347 DE-473 DE-BY-UBG DE-19 DE-BY-UBM DE-898 DE-BY-UBR DE-945 DE-83 DE-20 DE-91 DE-BY-TUM DE-739 DE-11 DE-824 DE-91G DE-BY-TUM DE-188 DE-355 DE-BY-UBR DE-1028 DE-863 DE-BY-FWS DE-521 |
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| physical | xvi, 363 Seiten Illustrationen, Diagramme |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | Springer |
| record_format | marc |
| series2 | Statistics and computing |
| spellingShingle | Dalgaard, Peter 1959- Introductory statistics with R Estatística computacional larpcal R (Langage de programmation) R (computerprogramma) gtt Software estatístico para microcomputadores larpcal Statistiek gtt Statistique - Informatique Datenverarbeitung Statistik R (Computer program language) Statistics Data processing R Programm (DE-588)4705956-4 gnd Statistik (DE-588)4056995-0 gnd |
| subject_GND | (DE-588)4705956-4 (DE-588)4056995-0 |
| title | Introductory statistics with R |
| title_auth | Introductory statistics with R |
| title_exact_search | Introductory statistics with R |
| title_exact_search_txtP | Introductory statistics with R |
| title_full | Introductory statistics with R Peter Dalgaard |
| title_fullStr | Introductory statistics with R Peter Dalgaard |
| title_full_unstemmed | Introductory statistics with R Peter Dalgaard |
| title_short | Introductory statistics with R |
| title_sort | introductory statistics with r |
| topic | Estatística computacional larpcal R (Langage de programmation) R (computerprogramma) gtt Software estatístico para microcomputadores larpcal Statistiek gtt Statistique - Informatique Datenverarbeitung Statistik R (Computer program language) Statistics Data processing R Programm (DE-588)4705956-4 gnd Statistik (DE-588)4056995-0 gnd |
| topic_facet | Estatística computacional R (Langage de programmation) R (computerprogramma) Software estatístico para microcomputadores Statistiek Statistique - Informatique Datenverarbeitung Statistik R (Computer program language) Statistics Data processing R Programm |
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