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Big Data and Social Science

A Practical Guide to Methods and Tools

Ocena książki

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  • 376 stron
  • 14 godzin czytania

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Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.

Zakup książki

Big Data and Social Science, Ian Foster, Rayid Ghani, Ron S. Jarmin, Frauke Kreuter, Julia Lane

Język
Rok wydania
2016
Oprawa
(twarda),
Stan książki
Dobry
Cena
26,56 zł

Metody płatności

2,7
Dobra
6 Ocena

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Tytuł
Big Data and Social Science
Podtytuł
A Practical Guide to Methods and Tools
Język
angielski
Rok wydania
2016
Oprawa
twarda
Liczba stron
376
ISBN10
1498751407
ISBN13
9781498751407
Ocena
2,65 z 5
Opis
Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.