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Quantitative Social Science

- An Introduction
Af: Kosuke Imai Engelsk Hardback

Quantitative Social Science

- An Introduction
Af: Kosuke Imai Engelsk Hardback
Tjek vores konkurrenters priser

An introductory textbook on data analysis and statistics written especially for students in the social sciences and allied fields

Quantitative analysis is an increasingly essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it—or if they do, they usually end up in statistics classes that offer few insights into their field. This textbook is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, such as economics, sociology, public policy, and data science.

Quantitative Social Science engages directly with empirical analysis, showing students how to analyze data using the R programming language and to interpret the results—it encourages hands-on learning, not paper-and-pencil statistics. More than forty data sets taken directly from leading quantitative social science research illustrate how data analysis can be used to answer important questions about society and human behavior.

Proven in the classroom, this one-of-a-kind textbook features numerous additional data analysis exercises and interactive R programming exercises, and also comes with supplementary teaching materials for instructors.

  • Written especially for students in the social sciences and allied fields, including economics, sociology, public policy, and data science
  • Provides hands-on instruction using R programming, not paper-and-pencil statistics
  • Includes more than forty data sets from actual research for students to test their skills on
  • Covers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical tools
  • Features a wealth of supplementary exercises, including additional data analysis exercises and interactive programming exercises
  • Offers a solid foundation for further study
  • Comes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides


Looking for a more accessible introduction? Consider Data Analysis for Social Science by Elena Llaudet and Kosuke Imai, which teaches from scratch and step-by-step the fundamentals of survey research, predictive models, and causal inference. It covers descriptive statistics, the difference-in-means estimator, simple linear regression, and multiple linear regression.

Tjek vores konkurrenters priser
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kr 1.002
Fragt: 39 kr
6 - 8 hverdage
20 kr
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God 4 anmeldelser på
Tjek vores konkurrenters priser

An introductory textbook on data analysis and statistics written especially for students in the social sciences and allied fields

Quantitative analysis is an increasingly essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it—or if they do, they usually end up in statistics classes that offer few insights into their field. This textbook is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, such as economics, sociology, public policy, and data science.

Quantitative Social Science engages directly with empirical analysis, showing students how to analyze data using the R programming language and to interpret the results—it encourages hands-on learning, not paper-and-pencil statistics. More than forty data sets taken directly from leading quantitative social science research illustrate how data analysis can be used to answer important questions about society and human behavior.

Proven in the classroom, this one-of-a-kind textbook features numerous additional data analysis exercises and interactive R programming exercises, and also comes with supplementary teaching materials for instructors.

  • Written especially for students in the social sciences and allied fields, including economics, sociology, public policy, and data science
  • Provides hands-on instruction using R programming, not paper-and-pencil statistics
  • Includes more than forty data sets from actual research for students to test their skills on
  • Covers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical tools
  • Features a wealth of supplementary exercises, including additional data analysis exercises and interactive programming exercises
  • Offers a solid foundation for further study
  • Comes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides


Looking for a more accessible introduction? Consider Data Analysis for Social Science by Elena Llaudet and Kosuke Imai, which teaches from scratch and step-by-step the fundamentals of survey research, predictive models, and causal inference. It covers descriptive statistics, the difference-in-means estimator, simple linear regression, and multiple linear regression.

Produktdetaljer
Sprog: Engelsk
Sider: 432
ISBN-13: 9780691167039
Indbinding: Hardback
Udgave:
ISBN-10: 0691167036
Udg. Dato: 9 feb 2018
Længde: 31mm
Bredde: 189mm
Højde: 260mm
Forlag: Princeton University Press
Oplagsdato: 9 feb 2018
Forfatter(e): Kosuke Imai
Forfatter(e) Kosuke Imai


Kategori Social forskning og statistik


ISBN-13 9780691167039


Sprog Engelsk


Indbinding Hardback


Sider 432


Udgave


Længde 31mm


Bredde 189mm


Højde 260mm


Udg. Dato 9 feb 2018


Oplagsdato 9 feb 2018


Forlag Princeton University Press

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