Quantitative Social Science: An Introduction. Kosuke Imai
Quantitative-Social-Science.pdf
ISBN: 9780691175461 | 432 pages | 11 Mb
- Quantitative Social Science: An Introduction
- Kosuke Imai
- Page: 432
- Format: pdf, ePub, fb2, mobi
- ISBN: 9780691175461
- Publisher: Princeton University Press
New releases audio books download Quantitative Social Science: An Introduction English version MOBI RTF 9780691175461
Quantitative Social Science: An Introduction 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
Quantitative Social Science: An Introduction - Kosuke Imai - kirja
Hinta: 40,10 €. nidottu, 2017. Lähetetään 2‑5 arkipäivässä.. Osta kirjaQuantitative Social Science: An Introduction Kosuke Imai (ISBN 9780691175461) osoitteesta Adlibris.fi. Ilmainen toimitus.
Quantitative Social Science: An Introduction - Google Books
This textbook is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the socialsciences and allied fields, such as economics, sociology, public policy, and datascience. Quantitative Social Science engages directly with empirical
Quantitative social science : an introduction (Book, 2017) [WorldCat
Get this from a library! Quantitative social science : an introduction. [Kosuke Imai] -- 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,
Archive: University of Houston: Minor in Quantitative Social Science
No more than six semester hours of special problems courses may be used to satisfy any major or minor requirements in CLASS. Following is a partial listing of courses that would count as satisfactory electives for the Minor in QuantitativeSocial Science: ECON 4349: Introduction to Game Theory. ECON 4360:Introduction
Quantitative Social Science: An Introduction | Didier Ruedin
Kosuke Imai has recently published a great introduction: Quantitative SocialScience: An Introduction. Finally a stats data analysis book that has arrived in the present! Yes, we can get away with very little mathematics and still do quantitative analysis. Yes, examples from published work are much more
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