Statistics for linguistics with R : a practical introduction / Stefan Th. Gries

By:

GRIES, Stefan Th. Stefan Th. Gries

Contributor(s):

Stefan Th. Gries Stefan Th. Gries [Author]

Material type: Text

TextPublication details: Berlin: De Gruyter Mouton, 2021.Edition: 2nd ed.-Description: xvi, 495 p. : ill. ; 23 cm. BookISBN:

978-3-11-030728-3

Subject(s):

R (Computer program language)

LOC classification:

DUCE P138.5 .G75

Online resources:

http://172.20.27.22:4000/handle/123456789/102

Summary: This is the second, newly revised and extended edition of this successful book (that has already been translated into three languages). Like the previous editions, it is entirely based on the programming language and environment R and is still thoroughly hands-on (with thousands of lines of heavily annotated code for all computations and plots). However, this edition has been updated based on many workshops/bootcamps taught by the author all over the world for the past few years: This edition has been didactically streamlined with regard to its exposition, it adds two new chapters -- one on mixed-effects modeling, one on classification and regression trees as well as random forests -- plus it features new discussion of curvature, orthogonal and other contrasts, interactions, collinearity, the effects and emmeans packages, autocorrelation/runs, some more bits on programming, writing statistical functions, and simulations, and many practical tips based on 10 years of teaching with these materials http://172.20.27.22:4000/handle/123456789/102

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Item type	Current library	Collection	Call number	URL	Status
Books	DUCE LIBRARY	Humanities and Social Sciences	DUCE P138.5 .G75 (Browse shelf(Opens below))	Link to resource	Available

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Includes bibliographical references (pages 486-495).

This is the second, newly revised and extended edition of this successful book (that has already been translated into three languages). Like the previous editions, it is entirely based on the programming language and environment R and is still thoroughly hands-on (with thousands of lines of heavily annotated code for all computations and plots). However, this edition has been updated based on many workshops/bootcamps taught by the author all over the world for the past few years: This edition has been didactically streamlined with regard to its exposition, it adds two new chapters -- one on mixed-effects modeling, one on classification and regression trees as well as random forests -- plus it features new discussion of curvature, orthogonal and other contrasts, interactions, collinearity, the effects and emmeans packages, autocorrelation/runs, some more bits on programming, writing statistical functions, and simulations, and many practical tips based on 10 years of teaching with these materials

http://172.20.27.22:4000/handle/123456789/102

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