Statistics for linguistics with R: a practical introduction
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| Main Author: | |
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| Format: | Book |
| Language: | English |
| Published: |
Berlin ; Boston
de Gruyter Mouton
[2021]
|
| Edition: | 3rd revised edition |
| Series: | Mouton Textbook
|
| Subjects: | |
| Online Access: | https://www.degruyter.com/books/9783110718164 Inhaltsverzeichnis |
| Physical Description: | XVI, 495 Seiten Diagramme 23 cm x 15.5 cm, 553 g |
| ISBN: | 9783110718164 3110718162 |
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| 020 | |a 9783110718164 |c Paperback : EUR 35.95 (DE) (freier Preis), EUR 35.95 (AT) (freier Preis) |9 978-3-11-071816-4 | ||
| 020 | |a 3110718162 |9 3-11-071816-2 | ||
| 024 | 3 | |a 9783110718164 | |
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| 084 | |8 1\p |a 400 |2 sdnb | ||
| 100 | 1 | |a Gries, Stefan Thomas |d 1970- |e Verfasser |0 (DE-588)131571222 |4 aut | |
| 245 | 1 | 0 | |a Statistics for linguistics with R |b a practical introduction |c Stefan Th. Gries |
| 250 | |a 3rd revised edition | ||
| 264 | 1 | |a Berlin ; Boston |b de Gruyter Mouton |c [2021] | |
| 264 | 4 | |c © 2021 | |
| 300 | |a XVI, 495 Seiten |b Diagramme |c 23 cm x 15.5 cm, 553 g | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Mouton Textbook | |
| 650 | 0 | 7 | |a R |g Programm |0 (DE-588)4705956-4 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Sprachstatistik |0 (DE-588)4182534-2 |2 gnd |9 rswk-swf |
| 653 | |a Regression Modeling | ||
| 653 | |a R | ||
| 653 | |a Linguistics | ||
| 653 | |a Statistics | ||
| 653 | |a Linguistik | ||
| 653 | |a Statistik | ||
| 653 | |a R | ||
| 653 | |a Regressionsanalyse | ||
| 653 | |a TB: Textbook | ||
| 655 | 7 | |0 (DE-588)4123623-3 |a Lehrbuch |2 gnd-content | |
| 689 | 0 | 0 | |a Sprachstatistik |0 (DE-588)4182534-2 |D s |
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| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe, PDF |z 978-3-11-071825-6 |
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe, EPUB |z 978-3-11-071829-4 |
| 856 | 4 | 2 | |m X:MVB |u https://www.degruyter.com/books/9783110718164 |
| 856 | 4 | 2 | |m DNB Datenaustausch |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032700274&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
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| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-032700274 | |
Record in the Search Index
| _version_ | 1816692020217905152 |
|---|---|
| adam_text |
TABLE
OF
CONTENTS
INTRODUCTION
-----
IX
1
1.1
1.2
1.3
1.3.1
1.3.2
1.3.2.1
1.3.2.2
1.3.2.3
1.4
1.5
1.5.1
1.5.2
1.5.3
1.6
SOME
FUNDAMENTALS
OF
EMPIRICAL
RESEARCH
-----
1
INTRODUCTION
-----
1
ON
THE
RELEVANCE
OF
QUANTITATIVE
METHODS
IN
LINGUISTICS
-----
4
THE
DESIGN
AND
THE
LOGIC
OF
QUANTITATIVE
STUDIES
-----
9
SCOUTING
-----
10
HYPOTHESES
AND
OPERATIONALIZATION
-----
12
SCIENTIFIC
HYPOTHESES
IN
TEXT
FORM
-----
12
OPERATIONALIZING
YOUR
VARIABLES
-----
16
SCIENTIFIC
HYPOTHESES
IN
STATISTICAL/MATHEMATICAL
FORM
-----
20
DATA
COLLECTION
AND
STORAGE
-----
24
THE
DECISION
-----
28
ONE-TAILED
P-VALUES
FROM
DISCRETE
PROBABILITY
DISTRIBUTIONS
-----
31
TWO-TAILED
P-VALUES
FROM
DISCRETE
PROBABILITY
DISTRIBUTIONS
-----
36
SIGNIFICANCE
AND
EFFECT
SIZE
-----
42
DATA
COLLECTION
AND
STORAGE
------44
2
2.1
2.2
2.3
2.3.1
2.3.2
2.3.3
2.4
2.4.1
2.4.2
2.4.3
2.5
2.5.1
2.5.2
2.5.3
2.6
FUNDAMENTALS
OF
R
-----
51
INTRODUCTION
AND
INSTALLATION
-----
51
FUNCTIONS
AND
ARGUMENTS
-----
54
VECTORS
-----
57
GENERATING
VECTORS
-----
57
LOADING
AND
SAVING
VECTORS
-----
63
WORKING
WITH
VECTORS
-----
65
FACTORS
-----
74
GENERATING
FACTORS
-----
74
LOADING
AND
SAVING
FACTORS
-----
75
WORKING
WITH
FACTORS
-----
76
DATA
FRAMES
-----
77
GENERATING
DATA
FRAMES
-----
78
LOADING
AND
SAVING
DATA
FRAMES
-----
80
WORKING
WITH
DATA
FRAMES
-----
82
LISTS
-----
87
3
DESCRIPTIVE
STATISTICS
-----
91
XII
-
TABLE
OF
CONTENTS
3.1
3.1.1
3.1.1.1
3.1.1.2
3.1.1.3
3.1.2
3.1.2.1
3.1.2.2
3.1.2.3
3.1.3
3.1.3.1
3.1.3.2
3.1.3.3
3.1.3.4
3.1.4
3.1.4.1
3.1.4.2
3.1.4.3
3.2
3.2.1
UNIVARIATE
DESCRIPTIVE
STATISTICS
-----
91
CATEGORICAL
VARIABLES
-----
93
CENTRAL
TENDENCY:
THE
MODE
-----
94
DISPERSION:
NORMALIZED
ENTROPY
-----
95
VISUALIZATION
------96
ORDINAL
VARIABLES
-----
99
CENTRAL
TENDENCY:
THE
MEDIAN
-----
100
DISPERSION:
QUANTILES
ETC.
-----
101
VISUALIZATION
-----
102
NUMERIC
VARIABLES
-----
103
CENTRAL
TENDENCY:
ARITHMETIC
MEAN
-----
104
DISPERSION:
STANDARD
DEVIATION
ETC.
-----
104
VISUALIZATION
-----
105
TWO
FREQUENT
TRANSFORMATIONS
-----
113
STANDARD
ERRORS
AND
CONFIDENCE
INTERVALS
-----
115
STANDARD
ERRORS
FOR
PERCENTAGES
-----
116
STANDARD
ERRORS
FOR
MEANS
-----
117
CONFIDENCE
INTERVALS
-----
118
BIVARIATE
DESCRIPTIVE
STATISTICS
-----
121
CATEGORICAL/ORDINAL
AS
A
FUNCTION
OF
CATEGORICAL/ORDINAL
VARIABLES
-----
121
3.2.2
CATEGORICAL/ORDINAL
VARIABLES
AS
A
FUNCTION
OF
NUMERIC
VARIABLES
-----
126
3.2.3
NUMERIC
VARIABLES
AS
A
FUNCTION
OF
CATEGORICAL/ORDINAL
VARIABLES
-----
128
3.2.4
3.3
3.4
3.5
3.5.1
3.5.2
3.5.3
3.5.4
3.5.4.1
3.5.4.2
NUMERIC
VARIABLES
AS
A
FUNCTION
OF
NUMERIC
VARIABLES
-----
129
POLEMIC
EXCURSUS
1:
ON
'
CORRELATION
'
-----
141
POLEMIC
EXCURSUS
2:
ON
VISUALIZATION
-----
145
(NON-POLEMIC)
EXCURSUS
ON
PROGRAMMING
-----
148
CONDITIONAL
EXPRESSIONS
-----
148
ON
LOOPING
-----
152
ON
NOT
LOOPING:
THE
APPLY
FAMILY
-----
156
FUNCTION
WRITING
-----
158
ANONYMOUS
FUNCTIONS
-----
159
NAMED
FUNCTIONS
-----
160
4
4.1
4.1.1
4.1.1.1
MONOFACTORIAL
TESTS
-----
164
DISTRIBUTIONS
AND
FREQUENCIES
-----
169
GOODNESS-OF-FIT
-----
169
ONE
CATEGORICAL/ORDINAL
RESPONSE
-----
169
TABLE
OF
CONTENTS
-
XIII
4X1.2
ONE
NUMERIC
RESPONSE
------
175
4.1.2
TESTS
FOR
DIFFERENCES/INDEPENDENCE
------
178
4.1.2.1
ONE
CATEGORICAL
RESPONSE
AND
ONE
CATEGORICAL
PREDICTOR
(INDEP.SAM
PLES)
------
178
4.1.2.2
ONE
ORDINAL/NUMERIC
RESPONSE
AND
ONE
CATEGORICAL
PREDICTOR
(INDEP.
SAMPLES)
-----
185
4.2
DISPERSION
-----
189
4.2.1
GOODNESS-OF-FIT
TEST
FOR
ONE
NUMERIC
RESPONSE
-----
190
4.2.2
TEST
FOR
INDEPENDENCE
FOR
ONE
NUMERIC
RESPONSE
AND
ONE
CATEGORI
CAL
PREDICTOR
------
192
4.2.2.1
A
SMALL
EXCURSUS:
SIMULATION
------
199
4.3
CENTRAL
TENDENCIES
------
200
4.3.1
GOODNESS-OF-FIT
TESTS
---------200
4.3.1.1
ONE
ORDINAL
RESPONSE
---------
200
4.3.1.2
ONE
NUMERIC
RESPONSE
-------
205
4.3.2
TESTS
FOR
DIFFERENCES/INDEPENDENCE
-----
209
4.3.2.1
ONE
ORDINAL
RESPONSE
AND
ONE
CATEGORICAL
PREDICTOR
(INDEP.
SAM
PLES)
-------209
4.3.2.2
ONE
ORDINAL
RESPONSE
AND
ONE
CATEGORICAL
PREDICTOR
(DEP.
SAMPLES)
------
213
4.3.2.3
ONE
NUMERIC
RESPONSE
AND
ONE
CATEGORICAL
PREDICTOR
(INDEP.
SAM
PLES)
------
217
4.3.2.4
ONE
NUMERIC
RESPONSE
AND
ONE
CATEGORICAL
PREDICTOR
(DEP.
SAMPLES)
------
222
4.4
CORRELATION
AND
SIMPLE
LINEAR
REGRESSION
-----
227
4.4.1
ORDINAL
VARIABLES
-----
227
4.4.2
NUMERIC
VARIABLES
-----
230
4.4.3
CORRELATION
AND
CAUSALITY
-----
233
5
FIXED-EFFECTS
REGRESSION
MODELING
-------
235
5.1
A
BIT
ON
'
MULTIFACTORIALITY
'
-----
235
5.2
LINEAR
REGRESSION
------240
5.2.1
A
LINEAR
MODEL
WITH
A
NUMERIC
PREDICTOR
-----
241
5.2.1.1
NUMERICAL
EXPLORATION
------
244
5.2.1.2
GRAPHICAL
MODEL
EXPLORATION
------
250
5.2.1.3
EXCURSUS:
CURVATURE
AND
ANOVA
------
251
5.2.1.4
EXCURSUS:
MODEL
FRAMES
AND
MODEL
MATRICES
------
255
5.2.1.5
EXCURSUS:
THE
95%-CI
OF
THE
SLOPE
------
256
5.2.2
A
LINEAR
MODEL
WITH
A
BINARY
PREDICTOR
-----
257
5.2.2.1
NUMERICAL
EXPLORATION
------
258
XIV
TABLE
OF
CONTENTS
5.2.2.2
GRAPHICAL
MODEL
EXPLORATION
------
261
5.2.2.3
EXCURSUS:
COEFFICIENTS
AS
INSTRUCTIONS
------
262
5.2.3
A
LINEAR
MODEL
WITH
A
CATEGORICAL
PREDICTOR
-----
263
5.2.3.1
NUMERICAL
EXPLORATION
------
264
5.2.3.2
GRAPHICAL
MODEL
EXPLORATION
------
269
5.2.3.3
EXCURSUS:
CONFLATION,
MODEL
COMPARISON,
AND
CONTRASTS
------
270
5.2.4
TOWARDS
MULTIFACTORIAL
MODELING
-----
279
5.2.4.1
SIMPSON'S
PARADOX
-----
279
5.2.4.2
INTERACTIONS
------
280
5.2.5
A
LINEAR
MODEL
WITH
TWO
CATEGORICAL
PREDICTORS
-----
289
5.2.5.1
NUMERICAL
EXPLORATION
-----
290
5.2.5.2
GRAPHICAL
MODEL
EXPLORATION
------
294
5.2.5.3
EXCURSUS:
COLLINEARITY
AND
VIFS
------
296
5.2.6
A
LINEAR
MODEL
WITH
A
CATEGORICAL
AND
A
NUMERIC
PREDICTOR
-----
299
5.2.6.1
NUMERICAL
EXPLORATION
------
299
5.2.6.2
GRAPHICAL
MODEL
EXPLORATION
------
302
5.2.6.3
EXCURSUS:
POST-HOC
COMPARISONS
AND
PREDICTIONS
FROM
EFFECTS
-----
302
5.2.7
A
LINEAR
MODEL
WITH
TWO
NUMERIC
PREDICTORS
-----
308
5.2.7.1
NUMERICAL
EXPLORATION
-----
309
5.2.7.2
GRAPHICAL
MODEL
EXPLORATION
-----
311
5.2.7.3
EXCURSUS:
WHERE
ARE
MOST
OF
THE
VALUES?
-----
313
5.2.8
INTERACTIONS
(YES,
AGAIN)
-----
314
5.3
BINARY
LOGISTIC
REGRESSION
-----
319
5.3.1
A
BINARY
LOGISTIC
REGRESSION
WITH
A
BINARY
PREDICTOR
-----
319
5.3.1.1
NUMERICAL
EXPLORATION
-----
319
5.3.1.2
GRAPHICAL
MODEL
EXPLORATION
----
327
5.3.2
A
BINARY
LOGISTIC
REGRESSION
WITH
A
CATEGORICAL
PREDICTOR
-----
328
5.3.2.1
NUMERICAL
EXPLORATION
-----
330
5.3.2.2
GRAPHICAL
MODEL
EXPLORATION
----
331
5.3.3
A
BINARY
LOGISTIC
REGRESSION
WITH
A
NUMERIC
PREDICTOR
------
332
5.3.3.1
NUMERICAL
EXPLORATION
-----
333
5.3.3.2
GRAPHICAL
MODEL
EXPLORATION
-----
335
5.3.3.3
EXCURSUS:
ON
CUT-OFF
POINTS
-----
336
5.3.4
A
BINARY
LOGISTIC
REGRESSION
WITH
TWO
CATEGORICAL
PREDICTORS
-----
338
5.3.4.1
NUMERICAL
EXPLORATION
-----
339
5.3.4.2
GRAPHICAL
MODEL
EXPLORATION
------
341
5.3.5
TWO
MORE
EFFECTS
PLOTS
FOR
YOU
TO
RECREATE
-----
341
5.4
OTHER
REGRESSION
MODELS
------
343
5.4.1
MULTINOMIAL
REGRESSION
-----
344
TABLE
OF
CONTENTS
-
XV
5.4.1.1
A
MULTINOMIAL
REGRESSION
WITH
A
NUMERIC
PREDICTOR
-----
345
5.4.1.2
A
MULTINOMIAL
REGRESSION
WITH
A
CATEGORICAL
PREDICTOR
-----
350
5.4.1.3
MULTINOMIAL
AND
BINARY
LOGISTIC
REGRESSION
-----
352
5.4.2
ORDINAL
LOGISTIC
REGRESSION
-----
353
5.4.2.1
AN
ORDINAL
REGRESSION
WITH
A
NUMERIC
PREDICTOR
-----
354
5.4.2.2
AN
ORDINAL
REGRESSION
WITH
A
CATEGORICAL
PREDICTOR
-----
358
5.5
MODEL
FORMULATION
(AND
MODEL
SELECTION)
-----
361
5.6
MODEL
ASSUMPTIONS/DIAGNOSTICS
-----
370
5.6.1
AMOUNT
OF
DATA
-----
371
5.6.2
RESIDUALS
-----
372
5.6.3
INFLUENTIAL
DATA
POINTS
-----
375
5.6.4
EXCURSUS:
AUTOCORRELATION/TIME
8I
OVERDISPERSION
------
379
5.7
MODEL
VALIDATION
(AND
CLASSIFICATION
VS.
PREDICTION)
-----
384
5.8
A
THOUGHT
EXPERIMENT
-----
387
6
MIXED-EFFECTS
REGRESSION
MODELING
-----
393
6.1
A
VERY
BASIC
INTRODUCTION
-----
393
6.1.1
VARYING
INTERCEPTS
ONLY
-----
397
6.1.2
VARYING SLOPES
ONLY
-----
401
6.1.3
VARYING
INTERCEPTS
AND
SLOPES
-----
403
6.1.3.1
VARYING
INTERCEPTS
AND
SLOPES
(CORRELATED)
-----
404
6.1.3.2
VARYING
INTERCEPTS
AND
SLOPES
(UNCORRELATED)
-----
406
6.2
SOME
GENERAL
MEM
CONSIDERATIONS
-----
408
6.3
LINEAR
MEM
CASE
STUDY
-----
414
6.3.1
PREPARATION
AND
EXPLORATION
-----
414
6.3.2
MODEL
FITTING/SELECTION
-----
418
6.3.3
QUICK
EXCURSUS
ON
UPDATE
-----
423
6.3.4
MODEL
DIAGNOSTICS
-----
424
6.3.5
MODEL
FITTING/SELECTION,
PART
2
------
425
6.3.6
A
BRIEF
INTERLUDE
-----
428
6.3.7
MODEL
DIAGNOSTICS,
PART
2
------
430
6.3.8
MODEL
INTERPRETATION
-----
432
6.3.9
A
BITON
MEM
PREDICTIONS
-----
437
6.4
GENERALIZED
LINEAR
MEM
CASE
STUDY
-----
439
6.4.1
PREPARATION
AND
EXPLORATION
-----
440
6.4.2
MODEL
FITTING/SELECTION
-----
442
6.4.3
MODEL
DIAGNOSTICS
-----
445
6.4.4
MODEL
INTERPRETATION
-----
445
6.5
ON
CONVERGENCE
AND
FINAL
RECOMMENDATIONS
-----
450
XVI
-
-
TABLE
OF
CONTENTS
7
TREE-BASED
APPROACHES-----
453
7.1
TREES
-----
454
7.1.1
CLASSIFICATION
AND
REGRESSION
TREES
-----
454
7.1.2
CONDITIONAL
INFERENCE
TREES
-----
460
7.2
ENSEMBLES
OF
TREES:
FORESTS
-----
463
7.2.1
FORESTS
OF
CLASSIFICATION
AND
REGRESSION
TREES
-----
465
7.2.2
FORESTS
OF
CONDITIONAL
INFERENCE
TREES
-----
469
7.3
DISCUSSION
-----
471
REFERENCES
-----
486
ABOUT
THE
AUTHOR
-----
496 |
| adam_txt |
TABLE
OF
CONTENTS
INTRODUCTION
-----
IX
1
1.1
1.2
1.3
1.3.1
1.3.2
1.3.2.1
1.3.2.2
1.3.2.3
1.4
1.5
1.5.1
1.5.2
1.5.3
1.6
SOME
FUNDAMENTALS
OF
EMPIRICAL
RESEARCH
-----
1
INTRODUCTION
-----
1
ON
THE
RELEVANCE
OF
QUANTITATIVE
METHODS
IN
LINGUISTICS
-----
4
THE
DESIGN
AND
THE
LOGIC
OF
QUANTITATIVE
STUDIES
-----
9
SCOUTING
-----
10
HYPOTHESES
AND
OPERATIONALIZATION
-----
12
SCIENTIFIC
HYPOTHESES
IN
TEXT
FORM
-----
12
OPERATIONALIZING
YOUR
VARIABLES
-----
16
SCIENTIFIC
HYPOTHESES
IN
STATISTICAL/MATHEMATICAL
FORM
-----
20
DATA
COLLECTION
AND
STORAGE
-----
24
THE
DECISION
-----
28
ONE-TAILED
P-VALUES
FROM
DISCRETE
PROBABILITY
DISTRIBUTIONS
-----
31
TWO-TAILED
P-VALUES
FROM
DISCRETE
PROBABILITY
DISTRIBUTIONS
-----
36
SIGNIFICANCE
AND
EFFECT
SIZE
-----
42
DATA
COLLECTION
AND
STORAGE
------44
2
2.1
2.2
2.3
2.3.1
2.3.2
2.3.3
2.4
2.4.1
2.4.2
2.4.3
2.5
2.5.1
2.5.2
2.5.3
2.6
FUNDAMENTALS
OF
R
-----
51
INTRODUCTION
AND
INSTALLATION
-----
51
FUNCTIONS
AND
ARGUMENTS
-----
54
VECTORS
-----
57
GENERATING
VECTORS
-----
57
LOADING
AND
SAVING
VECTORS
-----
63
WORKING
WITH
VECTORS
-----
65
FACTORS
-----
74
GENERATING
FACTORS
-----
74
LOADING
AND
SAVING
FACTORS
-----
75
WORKING
WITH
FACTORS
-----
76
DATA
FRAMES
-----
77
GENERATING
DATA
FRAMES
-----
78
LOADING
AND
SAVING
DATA
FRAMES
-----
80
WORKING
WITH
DATA
FRAMES
-----
82
LISTS
-----
87
3
DESCRIPTIVE
STATISTICS
-----
91
XII
-
TABLE
OF
CONTENTS
3.1
3.1.1
3.1.1.1
3.1.1.2
3.1.1.3
3.1.2
3.1.2.1
3.1.2.2
3.1.2.3
3.1.3
3.1.3.1
3.1.3.2
3.1.3.3
3.1.3.4
3.1.4
3.1.4.1
3.1.4.2
3.1.4.3
3.2
3.2.1
UNIVARIATE
DESCRIPTIVE
STATISTICS
-----
91
CATEGORICAL
VARIABLES
-----
93
CENTRAL
TENDENCY:
THE
MODE
-----
94
DISPERSION:
NORMALIZED
ENTROPY
-----
95
VISUALIZATION
------96
ORDINAL
VARIABLES
-----
99
CENTRAL
TENDENCY:
THE
MEDIAN
-----
100
DISPERSION:
QUANTILES
ETC.
-----
101
VISUALIZATION
-----
102
NUMERIC
VARIABLES
-----
103
CENTRAL
TENDENCY:
ARITHMETIC
MEAN
-----
104
DISPERSION:
STANDARD
DEVIATION
ETC.
-----
104
VISUALIZATION
-----
105
TWO
FREQUENT
TRANSFORMATIONS
-----
113
STANDARD
ERRORS
AND
CONFIDENCE
INTERVALS
-----
115
STANDARD
ERRORS
FOR
PERCENTAGES
-----
116
STANDARD
ERRORS
FOR
MEANS
-----
117
CONFIDENCE
INTERVALS
-----
118
BIVARIATE
DESCRIPTIVE
STATISTICS
-----
121
CATEGORICAL/ORDINAL
AS
A
FUNCTION
OF
CATEGORICAL/ORDINAL
VARIABLES
-----
121
3.2.2
CATEGORICAL/ORDINAL
VARIABLES
AS
A
FUNCTION
OF
NUMERIC
VARIABLES
-----
126
3.2.3
NUMERIC
VARIABLES
AS
A
FUNCTION
OF
CATEGORICAL/ORDINAL
VARIABLES
-----
128
3.2.4
3.3
3.4
3.5
3.5.1
3.5.2
3.5.3
3.5.4
3.5.4.1
3.5.4.2
NUMERIC
VARIABLES
AS
A
FUNCTION
OF
NUMERIC
VARIABLES
-----
129
POLEMIC
EXCURSUS
1:
ON
'
CORRELATION
'
-----
141
POLEMIC
EXCURSUS
2:
ON
VISUALIZATION
-----
145
(NON-POLEMIC)
EXCURSUS
ON
PROGRAMMING
-----
148
CONDITIONAL
EXPRESSIONS
-----
148
ON
LOOPING
-----
152
ON
NOT
LOOPING:
THE
APPLY
FAMILY
-----
156
FUNCTION
WRITING
-----
158
ANONYMOUS
FUNCTIONS
-----
159
NAMED
FUNCTIONS
-----
160
4
4.1
4.1.1
4.1.1.1
MONOFACTORIAL
TESTS
-----
164
DISTRIBUTIONS
AND
FREQUENCIES
-----
169
GOODNESS-OF-FIT
-----
169
ONE
CATEGORICAL/ORDINAL
RESPONSE
-----
169
TABLE
OF
CONTENTS
-
XIII
4X1.2
ONE
NUMERIC
RESPONSE
------
175
4.1.2
TESTS
FOR
DIFFERENCES/INDEPENDENCE
------
178
4.1.2.1
ONE
CATEGORICAL
RESPONSE
AND
ONE
CATEGORICAL
PREDICTOR
(INDEP.SAM
PLES)
------
178
4.1.2.2
ONE
ORDINAL/NUMERIC
RESPONSE
AND
ONE
CATEGORICAL
PREDICTOR
(INDEP.
SAMPLES)
-----
185
4.2
DISPERSION
-----
189
4.2.1
GOODNESS-OF-FIT
TEST
FOR
ONE
NUMERIC
RESPONSE
-----
190
4.2.2
TEST
FOR
INDEPENDENCE
FOR
ONE
NUMERIC
RESPONSE
AND
ONE
CATEGORI
CAL
PREDICTOR
------
192
4.2.2.1
A
SMALL
EXCURSUS:
SIMULATION
------
199
4.3
CENTRAL
TENDENCIES
------
200
4.3.1
GOODNESS-OF-FIT
TESTS
---------200
4.3.1.1
ONE
ORDINAL
RESPONSE
---------
200
4.3.1.2
ONE
NUMERIC
RESPONSE
-------
205
4.3.2
TESTS
FOR
DIFFERENCES/INDEPENDENCE
-----
209
4.3.2.1
ONE
ORDINAL
RESPONSE
AND
ONE
CATEGORICAL
PREDICTOR
(INDEP.
SAM
PLES)
-------209
4.3.2.2
ONE
ORDINAL
RESPONSE
AND
ONE
CATEGORICAL
PREDICTOR
(DEP.
SAMPLES)
------
213
4.3.2.3
ONE
NUMERIC
RESPONSE
AND
ONE
CATEGORICAL
PREDICTOR
(INDEP.
SAM
PLES)
------
217
4.3.2.4
ONE
NUMERIC
RESPONSE
AND
ONE
CATEGORICAL
PREDICTOR
(DEP.
SAMPLES)
------
222
4.4
CORRELATION
AND
SIMPLE
LINEAR
REGRESSION
-----
227
4.4.1
ORDINAL
VARIABLES
-----
227
4.4.2
NUMERIC
VARIABLES
-----
230
4.4.3
CORRELATION
AND
CAUSALITY
-----
233
5
FIXED-EFFECTS
REGRESSION
MODELING
-------
235
5.1
A
BIT
ON
'
MULTIFACTORIALITY
'
-----
235
5.2
LINEAR
REGRESSION
------240
5.2.1
A
LINEAR
MODEL
WITH
A
NUMERIC
PREDICTOR
-----
241
5.2.1.1
NUMERICAL
EXPLORATION
------
244
5.2.1.2
GRAPHICAL
MODEL
EXPLORATION
------
250
5.2.1.3
EXCURSUS:
CURVATURE
AND
ANOVA
------
251
5.2.1.4
EXCURSUS:
MODEL
FRAMES
AND
MODEL
MATRICES
------
255
5.2.1.5
EXCURSUS:
THE
95%-CI
OF
THE
SLOPE
------
256
5.2.2
A
LINEAR
MODEL
WITH
A
BINARY
PREDICTOR
-----
257
5.2.2.1
NUMERICAL
EXPLORATION
------
258
XIV
TABLE
OF
CONTENTS
5.2.2.2
GRAPHICAL
MODEL
EXPLORATION
------
261
5.2.2.3
EXCURSUS:
COEFFICIENTS
AS
INSTRUCTIONS
------
262
5.2.3
A
LINEAR
MODEL
WITH
A
CATEGORICAL
PREDICTOR
-----
263
5.2.3.1
NUMERICAL
EXPLORATION
------
264
5.2.3.2
GRAPHICAL
MODEL
EXPLORATION
------
269
5.2.3.3
EXCURSUS:
CONFLATION,
MODEL
COMPARISON,
AND
CONTRASTS
------
270
5.2.4
TOWARDS
MULTIFACTORIAL
MODELING
-----
279
5.2.4.1
SIMPSON'S
PARADOX
-----
279
5.2.4.2
INTERACTIONS
------
280
5.2.5
A
LINEAR
MODEL
WITH
TWO
CATEGORICAL
PREDICTORS
-----
289
5.2.5.1
NUMERICAL
EXPLORATION
-----
290
5.2.5.2
GRAPHICAL
MODEL
EXPLORATION
------
294
5.2.5.3
EXCURSUS:
COLLINEARITY
AND
VIFS
------
296
5.2.6
A
LINEAR
MODEL
WITH
A
CATEGORICAL
AND
A
NUMERIC
PREDICTOR
-----
299
5.2.6.1
NUMERICAL
EXPLORATION
------
299
5.2.6.2
GRAPHICAL
MODEL
EXPLORATION
------
302
5.2.6.3
EXCURSUS:
POST-HOC
COMPARISONS
AND
PREDICTIONS
FROM
EFFECTS
-----
302
5.2.7
A
LINEAR
MODEL
WITH
TWO
NUMERIC
PREDICTORS
-----
308
5.2.7.1
NUMERICAL
EXPLORATION
-----
309
5.2.7.2
GRAPHICAL
MODEL
EXPLORATION
-----
311
5.2.7.3
EXCURSUS:
WHERE
ARE
MOST
OF
THE
VALUES?
-----
313
5.2.8
INTERACTIONS
(YES,
AGAIN)
-----
314
5.3
BINARY
LOGISTIC
REGRESSION
-----
319
5.3.1
A
BINARY
LOGISTIC
REGRESSION
WITH
A
BINARY
PREDICTOR
-----
319
5.3.1.1
NUMERICAL
EXPLORATION
-----
319
5.3.1.2
GRAPHICAL
MODEL
EXPLORATION
----
327
5.3.2
A
BINARY
LOGISTIC
REGRESSION
WITH
A
CATEGORICAL
PREDICTOR
-----
328
5.3.2.1
NUMERICAL
EXPLORATION
-----
330
5.3.2.2
GRAPHICAL
MODEL
EXPLORATION
----
331
5.3.3
A
BINARY
LOGISTIC
REGRESSION
WITH
A
NUMERIC
PREDICTOR
------
332
5.3.3.1
NUMERICAL
EXPLORATION
-----
333
5.3.3.2
GRAPHICAL
MODEL
EXPLORATION
-----
335
5.3.3.3
EXCURSUS:
ON
CUT-OFF
POINTS
-----
336
5.3.4
A
BINARY
LOGISTIC
REGRESSION
WITH
TWO
CATEGORICAL
PREDICTORS
-----
338
5.3.4.1
NUMERICAL
EXPLORATION
-----
339
5.3.4.2
GRAPHICAL
MODEL
EXPLORATION
------
341
5.3.5
TWO
MORE
EFFECTS
PLOTS
FOR
YOU
TO
RECREATE
-----
341
5.4
OTHER
REGRESSION
MODELS
------
343
5.4.1
MULTINOMIAL
REGRESSION
-----
344
TABLE
OF
CONTENTS
-
XV
5.4.1.1
A
MULTINOMIAL
REGRESSION
WITH
A
NUMERIC
PREDICTOR
-----
345
5.4.1.2
A
MULTINOMIAL
REGRESSION
WITH
A
CATEGORICAL
PREDICTOR
-----
350
5.4.1.3
MULTINOMIAL
AND
BINARY
LOGISTIC
REGRESSION
-----
352
5.4.2
ORDINAL
LOGISTIC
REGRESSION
-----
353
5.4.2.1
AN
ORDINAL
REGRESSION
WITH
A
NUMERIC
PREDICTOR
-----
354
5.4.2.2
AN
ORDINAL
REGRESSION
WITH
A
CATEGORICAL
PREDICTOR
-----
358
5.5
MODEL
FORMULATION
(AND
MODEL
SELECTION)
-----
361
5.6
MODEL
ASSUMPTIONS/DIAGNOSTICS
-----
370
5.6.1
AMOUNT
OF
DATA
-----
371
5.6.2
RESIDUALS
-----
372
5.6.3
INFLUENTIAL
DATA
POINTS
-----
375
5.6.4
EXCURSUS:
AUTOCORRELATION/TIME
8I
OVERDISPERSION
------
379
5.7
MODEL
VALIDATION
(AND
CLASSIFICATION
VS.
PREDICTION)
-----
384
5.8
A
THOUGHT
EXPERIMENT
-----
387
6
MIXED-EFFECTS
REGRESSION
MODELING
-----
393
6.1
A
VERY
BASIC
INTRODUCTION
-----
393
6.1.1
VARYING
INTERCEPTS
ONLY
-----
397
6.1.2
VARYING SLOPES
ONLY
-----
401
6.1.3
VARYING
INTERCEPTS
AND
SLOPES
-----
403
6.1.3.1
VARYING
INTERCEPTS
AND
SLOPES
(CORRELATED)
-----
404
6.1.3.2
VARYING
INTERCEPTS
AND
SLOPES
(UNCORRELATED)
-----
406
6.2
SOME
GENERAL
MEM
CONSIDERATIONS
-----
408
6.3
LINEAR
MEM
CASE
STUDY
-----
414
6.3.1
PREPARATION
AND
EXPLORATION
-----
414
6.3.2
MODEL
FITTING/SELECTION
-----
418
6.3.3
QUICK
EXCURSUS
ON
UPDATE
-----
423
6.3.4
MODEL
DIAGNOSTICS
-----
424
6.3.5
MODEL
FITTING/SELECTION,
PART
2
------
425
6.3.6
A
BRIEF
INTERLUDE
-----
428
6.3.7
MODEL
DIAGNOSTICS,
PART
2
------
430
6.3.8
MODEL
INTERPRETATION
-----
432
6.3.9
A
BITON
MEM
PREDICTIONS
-----
437
6.4
GENERALIZED
LINEAR
MEM
CASE
STUDY
-----
439
6.4.1
PREPARATION
AND
EXPLORATION
-----
440
6.4.2
MODEL
FITTING/SELECTION
-----
442
6.4.3
MODEL
DIAGNOSTICS
-----
445
6.4.4
MODEL
INTERPRETATION
-----
445
6.5
ON
CONVERGENCE
AND
FINAL
RECOMMENDATIONS
-----
450
XVI
-
-
TABLE
OF
CONTENTS
7
TREE-BASED
APPROACHES-----
453
7.1
TREES
-----
454
7.1.1
CLASSIFICATION
AND
REGRESSION
TREES
-----
454
7.1.2
CONDITIONAL
INFERENCE
TREES
-----
460
7.2
ENSEMBLES
OF
TREES:
FORESTS
-----
463
7.2.1
FORESTS
OF
CLASSIFICATION
AND
REGRESSION
TREES
-----
465
7.2.2
FORESTS
OF
CONDITIONAL
INFERENCE
TREES
-----
469
7.3
DISCUSSION
-----
471
REFERENCES
-----
486
ABOUT
THE
AUTHOR
-----
496 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Gries, Stefan Thomas 1970- |
| author_GND | (DE-588)131571222 |
| author_facet | Gries, Stefan Thomas 1970- |
| author_role | aut |
| author_sort | Gries, Stefan Thomas 1970- |
| author_variant | s t g st stg |
| building | Verbundindex |
| bvnumber | BV047297035 |
| classification_rvk | ES 275 |
| ctrlnum | (OCoLC)1256438147 (DE-599)DNB1220643114 |
| discipline | Sprachwissenschaft Literaturwissenschaft |
| discipline_str_mv | Sprachwissenschaft Literaturwissenschaft |
| edition | 3rd revised edition |
| format | Book |
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| genre | (DE-588)4123623-3 Lehrbuch gnd-content |
| genre_facet | Lehrbuch |
| id | DE-604.BV047297035 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T17:22:13Z |
| indexdate | 2024-11-25T11:02:00Z |
| institution | BVB |
| institution_GND | (DE-588)1065653190 |
| isbn | 9783110718164 3110718162 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032700274 |
| oclc_num | 1256438147 |
| open_access_boolean | |
| owner | DE-188 DE-11 DE-739 DE-473 DE-BY-UBG |
| owner_facet | DE-188 DE-11 DE-739 DE-473 DE-BY-UBG |
| physical | XVI, 495 Seiten Diagramme 23 cm x 15.5 cm, 553 g |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | de Gruyter Mouton |
| record_format | marc |
| series2 | Mouton Textbook |
| spelling | Gries, Stefan Thomas 1970- Verfasser (DE-588)131571222 aut Statistics for linguistics with R a practical introduction Stefan Th. Gries 3rd revised edition Berlin ; Boston de Gruyter Mouton [2021] © 2021 XVI, 495 Seiten Diagramme 23 cm x 15.5 cm, 553 g txt rdacontent n rdamedia nc rdacarrier Mouton Textbook R Programm (DE-588)4705956-4 gnd rswk-swf Sprachstatistik (DE-588)4182534-2 gnd rswk-swf Regression Modeling R Linguistics Statistics Linguistik Statistik Regressionsanalyse TB: Textbook (DE-588)4123623-3 Lehrbuch gnd-content Sprachstatistik (DE-588)4182534-2 s R Programm (DE-588)4705956-4 s DE-604 De Gruyter Mouton (DE-588)1065653190 pbl Erscheint auch als Online-Ausgabe, PDF 978-3-11-071825-6 Erscheint auch als Online-Ausgabe, EPUB 978-3-11-071829-4 X:MVB https://www.degruyter.com/books/9783110718164 DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032700274&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p vlb 20201102 DE-101 https://d-nb.info/provenance/plan#vlb |
| spellingShingle | Gries, Stefan Thomas 1970- Statistics for linguistics with R a practical introduction R Programm (DE-588)4705956-4 gnd Sprachstatistik (DE-588)4182534-2 gnd |
| subject_GND | (DE-588)4705956-4 (DE-588)4182534-2 (DE-588)4123623-3 |
| title | Statistics for linguistics with R a practical introduction |
| title_auth | Statistics for linguistics with R a practical introduction |
| title_exact_search | Statistics for linguistics with R a practical introduction |
| title_exact_search_txtP | Statistics for linguistics with R a practical introduction |
| title_full | Statistics for linguistics with R a practical introduction Stefan Th. Gries |
| title_fullStr | Statistics for linguistics with R a practical introduction Stefan Th. Gries |
| title_full_unstemmed | Statistics for linguistics with R a practical introduction Stefan Th. Gries |
| title_short | Statistics for linguistics with R |
| title_sort | statistics for linguistics with r a practical introduction |
| title_sub | a practical introduction |
| topic | R Programm (DE-588)4705956-4 gnd Sprachstatistik (DE-588)4182534-2 gnd |
| topic_facet | R Programm Sprachstatistik Lehrbuch |
| url | https://www.degruyter.com/books/9783110718164 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032700274&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT griesstefanthomas statisticsforlinguisticswithrapracticalintroduction AT degruytermouton statisticsforlinguisticswithrapracticalintroduction |