Analyzing linguistic data: a practical introduction to statistics using R
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Cambridge [u.a.]
Cambridge Univ. Press
2009
|
| Edition: | 1. publ. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XIII, 353 S. graph. Darst. |
| ISBN: | 9780521709187 9780521882590 |
Staff View
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| 245 | 1 | 0 | |a Analyzing linguistic data |b a practical introduction to statistics using R |c R. H. Baayen |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a Cambridge [u.a.] |b Cambridge Univ. Press |c 2009 | |
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Record in the Search Index
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|---|---|
| adam_text | Contents
Preface x
1
An introduction
to R
1
1.1
R
as a calculator
2
1.2
Getting data into and out of
R
4
1.3
Accessing information in data frames
6
1.4
Operations on data frames
10
1.4.1
Sorting a data frame by one or more columns
i o
1.4.2
Changing information in a data frame
12
1.4.3
Extracting contingency tables from data frames
і З
1.4.4
Calculations on data frames
15
1.5
Session management
18
2
Graphical data exploration
20
2.1
Random variables
20
2.2
Visualizing single random variables
21
2.3
Visualizing two or more variables
32
2.4
Trellis graphics
37
3
Probability distributions
44
3.1
Distributions
44
3.2
Discrete distributions
44
3.3
Continuous distributions
57
3.3.1
The normal distribution
58
3.3.2
The
t, F,
and
χ2
distributions
63
4
Basic statistical methods
68
4.1
Tests for single vectors
7
1
4.1.1
Distribution tests
71
4.1.2
Tests for the mean
75
4.2
Tests for two independent vectors
77
4.2.1
Are the distributions the same?
78
4.2.2
Are the means the same?
79
4.2.3
Are the variances the same?
81
4.3
Paired vectors
82
4.3.1
Are the means or medians the same?
82
4.3.2
Functional relations: linear regression
84
CONTENTS
4.3.3
What does the joint density look like?
97
4.4
A numerical vector and a factor: analysis of variance
Ю1
4.4.1
Two numerical vectors and a factor: analysis
ofcovariance
108
4.5
Two vectors with counts
111
4.6
A note on statistical significance
114
Clustering and classification
118
5.1
Clustering
118
5.1.1
Tables with measurements: principal components analysis
Ц8
5.1.2
Tables with measurements: factor analysis
126
5.1.3
Tables with counts: correspondence analysis
128
5.1.4
Tables with distances: multidimensional scaling
136
5.1.5
Tables with distances: hierarchical cluster analysis
1
38
5.2
Classification
148
5.2.1
Classification trees
148
5.2.2
Discriminant analysis
154
5.2.3
Support vector machines
160
Regression modeling
165
6.1
Introduction
165
6.2
Ordinary least squares regression
169
6.2.1
Nonlinearities I74
6.2.2
Collinearity
181
6.2.3
Model criticism
188
6.2.4
Validation I93
6.3
Generalized linear models
195
6.3.1
Logistic regression I95
6.3.2
Ordinal logistic regression
208
6.4
Regression with breakpoints
214
6.5
Models for lexical richness
222
6.6
General considerations
236
Mixed models
241
7.1
Modeling data with fixed and random effects
242
7.2
A comparison with traditional analyses
259
7.2.1
Mixed-effects models and quasi-F
260
7.2.2
Mixed-effects models and Latin Square designs
266
7.2.3
Regression with subjects and items
269
7.3
Shrinkage in mixed-effects models
275
7.4
Generalized linear mixed models
278
7.5
Case studies
284
7.5.1
Primed lexical decision latencies for Dutch neologisms
284
7.5.2
Self-paced reading latencies for Dutch neologisms
287
7.5.3
Visual lexical decision latencies of Dutch
eight-year-olds
289
7.5.4
Mixed-effects models in corpus linguistics
295
Contents
Appendix
A
Solutions
to the exercises
303
Appendix
В
Overview of
R
functions
335
References
342
Index
347
Index of data sets
347
Index of
R
347
Index of topics
349
Index of authors
352
|
| adam_txt |
Contents
Preface x
1
An introduction
to R
1
1.1
R
as a calculator
2
1.2
Getting data into and out of
R
4
1.3
Accessing information in data frames
6
1.4
Operations on data frames
10
1.4.1
Sorting a data frame by one or more columns
i o
1.4.2
Changing information in a data frame
12
1.4.3
Extracting contingency tables from data frames
і З
1.4.4
Calculations on data frames
15
1.5
Session management
18
2
Graphical data exploration
20
2.1
Random variables
20
2.2
Visualizing single random variables
21
2.3
Visualizing two or more variables
32
2.4
Trellis graphics
37
3
Probability distributions
44
3.1
Distributions
44
3.2
Discrete distributions
44
3.3
Continuous distributions
57
3.3.1
The normal distribution
58
3.3.2
The
t, F,
and
χ2
distributions
63
4
Basic statistical methods
68
4.1
Tests for single vectors
7
1
4.1.1
Distribution tests
71
4.1.2
Tests for the mean
75
4.2
Tests for two independent vectors
77
4.2.1
Are the distributions the same?
78
4.2.2
Are the means the same?
79
4.2.3
Are the variances the same?
81
4.3
Paired vectors
82
4.3.1
Are the means or medians the same?
82
4.3.2
Functional relations: linear regression
84
CONTENTS
4.3.3
What does the joint density look like?
97
4.4
A numerical vector and a factor: analysis of variance
Ю1
4.4.1
Two numerical vectors and a factor: analysis
ofcovariance
108
4.5
Two vectors with counts
111
4.6
A note on statistical significance
114
Clustering and classification
118
5.1
Clustering
118
5.1.1
Tables with measurements: principal components analysis
Ц8
5.1.2
Tables with measurements: factor analysis
126
5.1.3
Tables with counts: correspondence analysis
128
5.1.4
Tables with distances: multidimensional scaling
136
5.1.5
Tables with distances: hierarchical cluster analysis
1
38
5.2
Classification
148
5.2.1
Classification trees
148
5.2.2
Discriminant analysis
154
5.2.3
Support vector machines
160
Regression modeling
165
6.1
Introduction
165
6.2
Ordinary least squares regression
169
6.2.1
Nonlinearities I74
6.2.2
Collinearity
181
6.2.3
Model criticism
188
6.2.4
Validation I93
6.3
Generalized linear models
195
6.3.1
Logistic regression I95
6.3.2
Ordinal logistic regression
208
6.4
Regression with breakpoints
214
6.5
Models for lexical richness
222
6.6
General considerations
236
Mixed models
241
7.1
Modeling data with fixed and random effects
242
7.2
A comparison with traditional analyses
259
7.2.1
Mixed-effects models and quasi-F
260
7.2.2
Mixed-effects models and Latin Square designs
266
7.2.3
Regression with subjects and items
269
7.3
Shrinkage in mixed-effects models
275
7.4
Generalized linear mixed models
278
7.5
Case studies
284
7.5.1
Primed lexical decision latencies for Dutch neologisms
284
7.5.2
Self-paced reading latencies for Dutch neologisms
287
7.5.3
Visual lexical decision latencies of Dutch
eight-year-olds
289
7.5.4
Mixed-effects models in corpus linguistics
295
Contents
Appendix
A
Solutions
to the exercises
303
Appendix
В
Overview of
R
functions
335
References
342
Index
347
Index of data sets
347
Index of
R
347
Index of topics
349
Index of authors
352 |
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| isbn | 9780521709187 9780521882590 |
| language | English |
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| spelling | Baayen, R. Harald 1958- Verfasser (DE-588)132384914 aut Analyzing linguistic data a practical introduction to statistics using R R. H. Baayen 1. publ. Cambridge [u.a.] Cambridge Univ. Press 2009 XIII, 353 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier R Programm (DE-588)4705956-4 gnd rswk-swf Sprachstatistik (DE-588)4182534-2 gnd rswk-swf Sprachstatistik (DE-588)4182534-2 s R Programm (DE-588)4705956-4 s DE-604 Digitalisierung UB Bamberg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016381549&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Baayen, R. Harald 1958- Analyzing linguistic data a practical introduction to statistics using R R Programm (DE-588)4705956-4 gnd Sprachstatistik (DE-588)4182534-2 gnd |
| subject_GND | (DE-588)4705956-4 (DE-588)4182534-2 |
| title | Analyzing linguistic data a practical introduction to statistics using R |
| title_auth | Analyzing linguistic data a practical introduction to statistics using R |
| title_exact_search | Analyzing linguistic data a practical introduction to statistics using R |
| title_exact_search_txtP | Analyzing linguistic data a practical introduction to statistics using R |
| title_full | Analyzing linguistic data a practical introduction to statistics using R R. H. Baayen |
| title_fullStr | Analyzing linguistic data a practical introduction to statistics using R R. H. Baayen |
| title_full_unstemmed | Analyzing linguistic data a practical introduction to statistics using R R. H. Baayen |
| title_short | Analyzing linguistic data |
| title_sort | analyzing linguistic data a practical introduction to statistics using r |
| title_sub | a practical introduction to statistics using R |
| topic | R Programm (DE-588)4705956-4 gnd Sprachstatistik (DE-588)4182534-2 gnd |
| topic_facet | R Programm Sprachstatistik |
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