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Machine learning for experiments in the social sciences

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning for experiments in the social sciencesJon Green, Mark H. White.
Author:	Green, Jonathan.
other author:	White, Mark Harmon.
Published:	Cambridge :Cambridge University Press,2023.
Description:	72 p. :ill., digital ;23 cm.
Notes:	Also issued in print: 2023.
Subject:	Social sciencesStatistical methods
Online resource:	https://doi.org/10.1017/9781009168236
ISBN:	9781009168236$q(electronic bk.)

Machine learning for experiments in the social sciences
Green, Jonathan.

Machine learning for experiments in the social sciences[electronic resource] /Jon Green, Mark H. White. - Cambridge :Cambridge University Press,2023. - 72 p. :ill., digital ;23 cm. - Cambridge elements. Elements in experimental political science,2633-3368. - Cambridge elements.Elements in experimental political science..

Also issued in print: 2023.

Includes bibliographical references.

Causal inference and machine learning are typically introduced in the social sciences separately as theoretically distinct methodological traditions. This volume provides theoretical and practical introductions to machine learning for social scientists interested in applying such methods to experimental data.

Specialized.

ISBN: 9781009168236$q(electronic bk.)Subjects--Topical Terms:

224754
Social sciences
--Statistical methods

LC Class. No.: H61.3 / .G7 2023

Dewey Class. No.: 300.2855631

Machine learning for experiments in the social sciences
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245 1 0 $a Machine learning for experiments in the social sciences $h [electronic resource] / $c Jon Green, Mark H. White.
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300 $a 72 p. : $b ill., digital ; $c 23 cm.
490 1 $a Cambridge elements. Elements in experimental political science, $x 2633-3368
500 $a Also issued in print: 2023.
504 $a Includes bibliographical references.
520 8 $a Causal inference and machine learning are typically introduced in the social sciences separately as theoretically distinct methodological traditions. This volume provides theoretical and practical introductions to machine learning for social scientists interested in applying such methods to experimental data.
521 $a Specialized.
588 $a Description based on online resource; title from PDF title page (viewed on April 13, 2023).
650 0 $a Social sciences $x Statistical methods $x Data processing. $3 224754
650 0 $a Machine learning. $3 188639
700 1 $a White, Mark Harmon. $3 981472
830 0 $a Cambridge elements. $p Elements in experimental political science. $3 981473
856 4 0 $u https://doi.org/10.1017/9781009168236