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Analyzing linguistic data : a practical introduction to statistics using R / R. H. Baayen.

By: Material type: TextTextPublisher: Cambridge : Cambridge University Press, 2014Edition: Seventh printingDescription: xiii, 353 pages : illustrations ; 26 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 0521709180 (pbk.)
  • 9780521709187 (pbk.)
Subject(s): Genre/Form: DDC classification:
  • 410.151 BAA 22
Online resources:
Contents:
1. An introduction to R: 1.1. R as a calculator -- 1.2. Getting data into and out of R -- 1.3. Accessing information in data frames -- 1.4. Operations on data frames -- 1.5. Session management -- 2. Graphical data exploration: 2.1. Random variables -- 2.2. Visualizing single random variables -- 2.3. Visualizing two or more variables -- 2.4. Trellis graphics -- 3. Probability distributions: 3.1. Distributions -- 3.2. Discrete distributions -- 3.3. Continuous distributions -- 4. Basic statistical methods: 4.1. Tests for single vectors -- 4.2. Tests for two independent vectors -- 4.3. Paired vectors -- 4.4. A numerical vector and a factor: analysis of variance -- 4.5. Two vectors with counts -- 4.6. A note on statistical significance -- 5. Clustering and classification: 5.1. Clustering -- 5.2. Classification -- 6. Regression modeling: 6.1. Introduction -- 6.2. Ordinary least squares regression -- 6.3. Generalized linear models -- 6.4. Regression with breakpoints -- 6.5. Models for lexical richness -- 6.6. General considerations -- 7. Mixed models: 7.1. Modeling data with fixed and random effects -- 7.2. comparison with traditional analyses -- 7.3. Shrinkage in mixed-effects models -- 7.4. Generalized linear mixed models -- 7.5. Case studies.
Summary: "This textbook provides a straightforward introduction to the statistical analysis of language data. It clearly introduces the basic principles and methods of statistical analysis, using R, the leading computational statistics programming environment. The reader is guided step-by-step through a range of real data sets, allowing them to analyze phonetic data, construct phylogenetic trees, quantify register variation in corpus linguistics, and analyze experimental data using state-of-the-art models. The visualization of data plays a key role, both in the early stages of data exploration and later on when the reader is encouraged to criticize initial models fitted to the data. Containing over forty 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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Holdings
Item type Current library Collection Call number Vol info Status Date due Barcode Item holds
Book - Borrowing Book - Borrowing Central Library Second Floor Baccah 410.151 BAA (Browse shelf(Opens below)) Available 000043715
NB - Book (Non borrowing) NB - Book (Non borrowing) Central Library Second Floor Baccah 410.151 BAA (Browse shelf(Opens below)) 26103 Not for loan 000033433
Total holds: 0

Includes bibliographical references and index.

1. An introduction to R: 1.1. R as a calculator -- 1.2. Getting data into and out of R -- 1.3. Accessing information in data frames -- 1.4. Operations on data frames -- 1.5. Session management -- 2. Graphical data exploration: 2.1. Random variables -- 2.2. Visualizing single random variables -- 2.3. Visualizing two or more variables -- 2.4. Trellis graphics --
3. Probability distributions: 3.1. Distributions -- 3.2. Discrete distributions -- 3.3. Continuous distributions -- 4. Basic statistical methods: 4.1. Tests for single vectors -- 4.2. Tests for two independent vectors -- 4.3. Paired vectors -- 4.4. A numerical vector and a factor: analysis of variance -- 4.5. Two vectors with counts -- 4.6. A note on statistical significance --
5. Clustering and classification: 5.1. Clustering -- 5.2. Classification -- 6. Regression modeling: 6.1. Introduction --
6.2. Ordinary least squares regression -- 6.3. Generalized linear models -- 6.4. Regression with breakpoints -- 6.5. Models for lexical richness -- 6.6. General considerations -- 7. Mixed models: 7.1. Modeling data with fixed and random effects --
7.2. comparison with traditional analyses -- 7.3. Shrinkage in mixed-effects models -- 7.4. Generalized linear mixed models --
7.5. Case studies.

"This textbook provides a straightforward introduction to the statistical analysis of language data. It clearly introduces the basic principles and methods of statistical analysis, using R, the leading computational statistics programming environment. The reader is guided step-by-step through a range of real data sets, allowing them to analyze phonetic data, construct phylogenetic trees, quantify register variation in corpus linguistics, and analyze experimental data using state-of-the-art models. The visualization of data plays a key role, both in the early stages of data exploration and later on when the reader is encouraged to criticize initial models fitted to the data. Containing over forty 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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