9781498751407-1498751407-Big Data and Social Science: A Practical Guide to Methods and Tools (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)

Big Data and Social Science: A Practical Guide to Methods and Tools (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)

ISBN-13: 9781498751407
ISBN-10: 1498751407
Edition: 1
Author: Frauke Kreuter, Julia Lane, Ian Foster, Rayid Ghani, Ron S. Jarmin
Publication date: 2016
Publisher: Chapman and Hall/CRC
Format: Hardcover 376 pages
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Book details

ISBN-13: 9781498751407
ISBN-10: 1498751407
Edition: 1
Author: Frauke Kreuter, Julia Lane, Ian Foster, Rayid Ghani, Ron S. Jarmin
Publication date: 2016
Publisher: Chapman and Hall/CRC
Format: Hardcover 376 pages

Summary

Big Data and Social Science: A Practical Guide to Methods and Tools (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences) (ISBN-13: 9781498751407 and ISBN-10: 1498751407), written by authors Frauke Kreuter, Julia Lane, Ian Foster, Rayid Ghani, Ron S. Jarmin, was published by Chapman and Hall/CRC in 2016. With an overall rating of 4.4 stars, it's a notable title among other Statistics (Education & Reference, Social Sciences) books. You can easily purchase or rent Big Data and Social Science: A Practical Guide to Methods and Tools (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences) (Hardcover, Used) from BooksRun, along with many other new and used Statistics books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.97.

Description

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.

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