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Quantitative Methods for the Social Sciences: A Practical Introduction with Examples in R

AUTHOR Bordeleau, Jean-Nicolas; Stockemer, Daniel
PUBLISHER Springer (09/13/2023)
PRODUCT TYPE Hardcover (Hardcover)

Description

This textbook offers an essential introduction to survey research and quantitative methods with clear instructions on how to conduct statistical tests with R. Building on the premise that we need to teach statistical methods in a holistic and practical format, the book guides students through the four main elements of survey research and quantitative analysis: (1) the importance of survey research, (2) preparing a survey, (3) conducting a survey and (4) analyzing a survey. In detail, students will learn how to create their own questionnaire on the basis of formulating hypotheses; sampling participants; disseminating their questionnaire; creating datasets; and analyzing their data. The data analytical sections of this revised and extended edition explain the theory, rationale and mathematical foundations of relevant bivariate and multi-variate statistical tests. These include the T-test, F-test, Chi-square test and correlation analyses, as well as bivariate and multivariate regression analyses. In addition, the book offers a brief introduction to statistical computing with R, which includes clear instructions on how to conduct these statistical tests in R. Given the breadth of its coverage, the textbook is suitable for introductory statistics, survey research and quantitative methods classes in the social sciences.

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Product Format
Product Details
ISBN-13: 9783031345821
ISBN-10: 3031345827
Binding: Hardback or Cased Book (Sewn)
Content Language: English
Edition Number: 0002
More Product Details
Page Count: 141
Carton Quantity: 26
Product Dimensions: 6.14 x 0.44 x 9.21 inches
Weight: 0.89 pound(s)
Feature Codes: Illustrated
Country of Origin: NL
Subject Information
BISAC Categories
Political Science | General
Political Science | Statistics
Political Science | Mathematical & Statistical Software
Descriptions, Reviews, Etc.
jacket back
This textbook offers an essential introduction to survey research and quantitative methods with clear instructions on how to conduct statistical tests with R. Building on the premise that we need to teach statistical methods in a holistic and practical format, the book guides students through the four main elements of survey research and quantitative analysis: (1) the importance of survey research, (2) preparing a survey, (3) conducting a survey and (4) analyzing a survey. In detail, students will learn how to create their own questionnaire on the basis of formulating hypotheses; sampling participants; disseminating their questionnaire; creating datasets; and analyzing their data. The data analytical sections of this revised and extended edition explain the theory, rationale and mathematical foundations of relevant bivariate and multi-variate statistical tests. These include the T-test, F-test, Chi-square test and correlation analyses, as well as bivariateand multivariate regression analyses. In addition, the book offers a brief introduction to statistical computing with R, which includes clear instructions on how to conduct these statistical tests in R. Given the breadth of its coverage, the textbook is suitable for introductory statistics, survey research and quantitative methods classes in the social sciences.
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publisher marketing

This textbook offers an essential introduction to survey research and quantitative methods with clear instructions on how to conduct statistical tests with R. Building on the premise that we need to teach statistical methods in a holistic and practical format, the book guides students through the four main elements of survey research and quantitative analysis: (1) the importance of survey research, (2) preparing a survey, (3) conducting a survey and (4) analyzing a survey. In detail, students will learn how to create their own questionnaire on the basis of formulating hypotheses; sampling participants; disseminating their questionnaire; creating datasets; and analyzing their data. The data analytical sections of this revised and extended edition explain the theory, rationale and mathematical foundations of relevant bivariate and multi-variate statistical tests. These include the T-test, F-test, Chi-square test and correlation analyses, as well as bivariate and multivariate regression analyses. In addition, the book offers a brief introduction to statistical computing with R, which includes clear instructions on how to conduct these statistical tests in R. Given the breadth of its coverage, the textbook is suitable for introductory statistics, survey research and quantitative methods classes in the social sciences.

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Hardcover