Analyzing Linguistic Data

A Practical Introduction to Statistics using R

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Paperback | 15 April 2008

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Statistical analysis is a useful skill for linguists and psycholinguists, allowing them to understand the quantitative structure of their data. This textbook provides a straightforward introduction to the statistical analysis of language. Designed for linguists with a non-mathematical background, it clearly introduces the basic principles and methods of statistical analysis, using 'R', the leading computational statistics programme. The reader is guided step-by-step through a range of real data sets, allowing them to analyse acoustic data, construct grammatical trees for a variety of languages, quantify register variation in corpus linguistics, and measure experimental data using state-of-the-art models. The visualization of data plays a key role, both in the initial stages of data exploration and later on when the reader is encouraged to criticize various models. Containing over 40 exercises with model answers, this book will be welcomed by all linguists wishing to learn more about working with and presenting quantitative data.

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Non-Fiction Language & Linguistics Linguistics Mathematics Probability & Statistics Reference, Dictionaries & Guides Computing & I.T.Business Applications Mathematical & Statistical Software

Preface	p. x
An introduction to R	p. 1
R as a calculator	p. 2
Getting data into and out of R	p. 4
Accessing information in data frames	p. 6
Operations on data frames	p. 10
Sorting a data frame by one or more columns	p. 10
Changing information in a data frame	p. 12
Extracting contingency tables from data frames	p. 13
Calculations on data frames	p. 15
Session management	p. 18
Graphical data exploration	p. 20
Random variables	p. 20
Visualizing single random variables	p. 21
Visualizing two or more variables	p. 32
Trellis graphics	p. 37
Probability distributions	p. 44
Distributions	p. 44
Discrete distributions	p. 44
Continuous distributions	p. 57
The normal distribution	p. 58
The t, F, and X[superscript 2] distributions	p. 63
Basic statistical methods	p. 68
Tests for single vectors	p. 71
Distribution tests	p. 71
Tests for the mean	p. 75
Tests for two independent vectors	p. 77
Are the distributions the same?	p. 78
Are the means the same?	p. 79
Are the variances the same?	p. 81
Paired vectors	p. 82
Are the means or medians the same?	p. 82
Functional relations: linear regression	p. 84
What does the joint density look like?	p. 97
A numerical vector and a factor: analysis of variance	p. 101
Two numerical vectors and a factor: analysis of covariance	p. 108
Two vectors with counts	p. 111
A note on statistical significance	p. 114
Clustering and classification	p. 118
Clustering	p. 118
Tables with measurements: principal components analysis	p. 118
Tables with measurements: factor analysis	p. 126
Tables with counts: correspondence analysis	p. 128
Tables with distances: multidimensional scaling	p. 136
Tables with distances: hierarchical cluster analysis	p. 138
Classification	p. 148
Classification trees	p. 148
Discriminant analysis	p. 154
Support vector machines	p. 160
Regression modeling	p. 165
Introduction	p. 165
Ordinary least squares regression	p. 169
Nonlinearities	p. 174
Collinearity	p. 181
Model criticism	p. 188
Validation	p. 193
Generalized linear models	p. 195
Logistic regression	p. 195
Ordinal logistic regression	p. 208
Regression with breakpoints	p. 214
Models for lexical richness	p. 222
General considerations	p. 236
Mixed models	p. 241
Modeling data with fixed and random effects	p. 242
A comparison with traditional analyses	p. 259
Mixed-effects models and quasi-F	p. 260
Mixed-effects models and Latin Square designs	p. 266
Regression with subjects and items	p. 269
Shrinkage in mixed-effects models	p. 275
Generalized linear mixed models	p. 278
Case studies	p. 284
Primed lexical decision latencies for Dutch neologisms	p. 284
Self-paced reading latencies for Dutch neologisms	p. 287
Visual lexical decision latencies of Dutch eight-year-olds	p. 289
Mixed-effects models in corpus linguistics	p. 295
Solutions to the exercises	p. 303
Overview of R functions	p. 335
References	p. 342
Index	p. 347
Index of data sets	p. 347
Index of R	p. 347
Index of topics	p. 349
Index of authors	p. 352
Table of Contents provided by Ingram. All Rights Reserved.

Analyzing Linguistic Data

A Practical Introduction to Statistics using R

At a Glance

Paperback

Shipping

How to return your order

Defective items

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