UID:
almafu_9961294710302883
Format:
1 online resource (xiii, 353 pages) :
,
digital, PDF file(s).
ISBN:
1-316-09966-0
,
0-511-80168-8
,
0-511-64962-2
,
0-511-38447-5
,
0-511-57425-8
,
0-511-38630-3
Content:
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.
Note:
Title from publisher's bibliographic system (viewed on 18 Jul 2016).
,
introduction to R --
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R as a calculator --
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Getting data into and out of R --
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Accessing information in data frames --
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Operations on data frames --
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Session management --
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Graphical data exploration --
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Random variables --
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Visualizing single random variables --
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Visualizing two or more variables --
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Trellis graphics --
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Probability distributions --
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Distributions --
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Discrete distributions --
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Continuous distributions --
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Basic statistical methods --
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Tests for single vectors --
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Tests for two independent vectors --
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Paired vectors --
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numerical vector and a factor: analysis of variance --
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Two vectors with counts --
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note on statistical significance --
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Clustering and classification --
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Clustering --
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Classification --
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Regression modeling --
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Introduction --
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Ordinary least squares regression --
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Generalized linear models --
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Regression with breakpoints --
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Models for lexical richness --
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General considerations --
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Mixed models --
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Modeling data with fixed and random effects --
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comparison with traditional analyses --
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Shrinkage in mixed-effects models --
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Generalized linear mixed models --
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Case studies --
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Solutions to the exercises --
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Overview of R functions.
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English
Additional Edition:
ISBN 0-521-70918-0
Additional Edition:
ISBN 0-521-88259-1
Language:
English
