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Analyzing Linguistic Data A Practical Introduction to Statistics Using R

ISBN-10: 0521709180
ISBN-13: 9780521709187
Edition: 2007
Authors: R. H. Baayen
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Description: 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  More...

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Book details

List price: $54.99
Copyright year: 2007
Publisher: Cambridge University Press
Publication date: 3/6/2008
Binding: Paperback
Pages: 368
Size: 7.00" wide x 9.75" long x 1.00" tall
Weight: 1.672
Language: English

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.

R. H. Baayen is Professor of Quantitative Linguistics at Radboud University of Nijmegen and the Max Planck Institute for Psycholinguistics, Nijmegen.

Preface
An introduction to R
R as a calculator
Getting data into and out of R
Accessing information in data frames
Operations on data frames
Sorting a data frame by one or more columns
Changing information in a data frame
Extracting contingency tables from data frames
Calculations on data frames
Session management
Graphical data exploration
Random variables
Visualizing single random variables
Visualizing two or more variables
Trellis graphics
Probability distributions
Distributions
Discrete distributions
Continuous distributions
The normal distribution
The t, F, and X[superscript 2] distributions
Basic statistical methods
Tests for single vectors
Distribution tests
Tests for the mean
Tests for two independent vectors
Are the distributions the same?
Are the means the same?
Are the variances the same?
Paired vectors
Are the means or medians the same?
Functional relations: linear regression
What does the joint density look like?
A numerical vector and a factor: analysis of variance
Two numerical vectors and a factor: analysis of covariance
Two vectors with counts
A note on statistical significance
Clustering and classification
Clustering
Tables with measurements: principal components analysis
Tables with measurements: factor analysis
Tables with counts: correspondence analysis
Tables with distances: multidimensional scaling
Tables with distances: hierarchical cluster analysis
Classification
Classification trees
Discriminant analysis
Support vector machines
Regression modeling
Introduction
Ordinary least squares regression
Nonlinearities
Collinearity
Model criticism
Validation
Generalized linear models
Logistic regression
Ordinal logistic regression
Regression with breakpoints
Models for lexical richness
General considerations
Mixed models
Modeling data with fixed and random effects
A comparison with traditional analyses
Mixed-effects models and quasi-F
Mixed-effects models and Latin Square designs
Regression with subjects and items
Shrinkage in mixed-effects models
Generalized linear mixed models
Case studies
Primed lexical decision latencies for Dutch neologisms
Self-paced reading latencies for Dutch neologisms
Visual lexical decision latencies of Dutch eight-year-olds
Mixed-effects models in corpus linguistics
Solutions to the exercises
Overview of R functions
References
Index
Index of data sets
Index of R
Index of topics
Index of authors

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