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Big Data and Social Science

A Practical Guide to Methods and Tools

Hodnotenie knihy

Parametre

  • 376 stránok
  • 14 hodin čítania

Viac o knihe

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.

Nákup knihy

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

Jazyk
Rok vydania
2016
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Titul
Big Data and Social Science
Podtitul
A Practical Guide to Methods and Tools
Jazyk
anglicky
Rok vydania
2016
Väzba
pevná
Počet strán
376
ISBN10
1498751407
ISBN13
9781498751407
Hodnotenie
2,65 z 5
Anotácia
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.