Analyzing Linguistic Data 1st Edition by R H Baayen ISBN 0521709180 9780521709187
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Product details:
ISBN 10: 0521709180
ISBN 13: 9780521709187
Author: R. H. Baayen
Table of 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
1.4.1 Sorting a data frame by one or more columns
1.4.2 Changing information in a data frame
1.4.3 Extracting contingency tables from data frames
1.4.4 Calculations 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
3.3.1 The normal distribution
3.3.2 The t, F, and X2 distributions
4 Basic statistical methods
4.1 Tests for single vectors
4.1.1 Distribution tests
4.1.2 Tests for the mean
4.2 Tests for two independent vectors
4.2.1 Are the distributions the same?
4.2.2 Are the means the same?
4.2.3 Are the variances the same?
4.3 Paired vectors
4.3.1 Are the means or medians the same?
4.3.2 Functional relations: linear regression
4.3.2.1 Slope and intercept
4.3.2.2 Estimating slope and intercept
4.3.2.3 Correlation
4.3.2.4 Summarizing a linear model object
4.3.2.5 Problems and pitfalls of linear regression
4.3.3 What does the joint density look like?
4.4 A numerical vector and a factor: analysis of variance
4.4.1 Two numerical vectors and a factor: analysis of covariance
4.5 Two vectors with counts
4.6 A note on statistical significance
5 Clustering and classification
5.1 Clustering
5.1.1 Tables with measurements: principal components analysis
5.1.2 Tables with measurements: factor analysis
5.1.3 Tables with counts: correspondence analysis
5.1.4 Tables with distances: multidimensional scaling
5.1.5 Tables with distances: hierarchical cluster analysis
5.2 Classification
5.2.1 Classification trees
5.2.2 Discriminant analysis
5.2.3 Support vector machines
6 Regression modeling
6.1 Introduction
6.2 Ordinary least squares regression
6.2.1 Nonlinearities
6.2.2 Collinearity
6.2.3 Model criticism
6.2.4 Validation
6.3 Generalized linear models
6.3.1 Logistic regression
6.3.2 Ordinal logistic regression
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 A comparison with traditional analyses
7.2.1 Mixed-effects models and quasi-F
7.2.2 Mixed-effects models and Latin Square designs
7.2.3 Regression with subjects and items
7.3 Shrinkage in mixed-effects models
7.4 Generalized linear mixed models
7.5 Case studies
7.5.1 Primed lexical decision latencies for Dutch neologisms
7.5.2 Self-paced reading latencies for Dutch neologisms
7.5.3 Visual lexical decision latencies of Dutch eight-year-olds
7.5.4 Mixed-effects models in corpus linguistics
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R H Baayen,Analyzing,Data