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Chapman and Hall/CRC Statistics in the Social and Behavioral Sciences Ser.: Big Data and Social Science : A Practical Guide to Methods and Tools by Rayid Ghani (2016, Hardcover)

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By Foster, Ian; Ghani, Rayid; Jarmin, Ron S.; Kreuter, Frauke; Lane, Julia.

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Product Information

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.

Product Identifiers

Publisher
CRC Press LLC
ISBN-10
1498751407
ISBN-13
9781498751407
eBay Product ID (ePID)
221459249

Product Key Features

Author
Rayid Ghani
Publication Name
Big Data and Social Science : a Practical Guide to Methods and Tools
Format
Hardcover
Language
English
Publication Year
2016
Series
Chapman and Hall/Crc Statistics in the Social and Behavioral Sciences Ser.
Type
Textbook
Number of Pages
356 Pages

Dimensions

Item Length
9.5in
Item Height
0.9in
Item Width
7.8in
Item Weight
33.7 Oz

Additional Product Features

Series Volume Number
25
Lc Classification Number
H61.3.B55 2017
Reviews
"In Big Data and Social Science, the authors have deftly crafted one of the very best "how-to" books on big data that researchers, enterprise analysts, and government practitioners will find equally valuable. From Nodes, to Edges, to Arcs, the book takes the reader along a near-perfect path to understanding the fundamental elements of constructing a practical and realistic model for Big Data Analysis that any organization can execute by simply following the path outlined in this book. Elegant in its simplicity, Big Data and Social Scienceis one of those books that every research group and data-analysis team will want to have on their reference shelf." --Tom Herzog, Former Deputy Commissioner, NY State Department of Corrections and Community Supervision
Table of Content
Introduction Why this book? Defining big data and its value Social science, inference, and big data Social science, data quality, and big data New tools for new data The book's "use case" The structure of the book Resources Capture and Curation Working with Web Data and APIs Introduction Scraping information from the web New data in the research enterprise A functional view Programming against an API Using the ORCID API via a wrapper Quality, scope, and management Integrating data from multiple sources Working with the graph of relationships Bringing it together: Tracking pathways to impact Summary Resources Acknowledgements and copyright Record Linkage Motivation Introduction to record linkage Preprocessing data Classification Record linkage and data protection Summary Resources Databases Introduction DBMS: When and why Relational DBMSs Linking DBMSs and other tools NoSQL databases Spatial databases Which database to use? Summary Resources Programming with Big Data Introduction The MapReduce programming model Apache Hadoop MapReduce Apache Spark Summary Resources Modeling and Analysis Machine Learning Introduction What is machine learning? The machine learning process Problem formulation: Mapping a problem to machine learning methods Methods Evaluation Practical tips How can social scientists benefit from machine learning? Advanced topics Summary Resources Text Analysis Understanding what people write How to analyze text Approaches and applications Evaluation Text analysis tools Summary Resources Networks: The Basics Introduction Network data Network measures Comparing collaboration networks Summary Resources Inference and Ethics Information Visualization Introduction Developing effective visualizations A data-by-tasks taxonomy Challenges Summary Resources Errors and Inference Introduction The total error paradigm Illustrations of errors in big data Errors in big data analytics Some methods for mitigating, detecting, and compensating for errors Summary Resources Privacy and Confidentiality Introduction Why is access at all important? Providing access The new challenges Legal and ethical framework Summary Resources Workbooks Introduction Environment Workbook details Resources Bibliography
Copyright Date
2017
Topic
Machine Theory, Probability & Statistics / General, General, Databases / Data Mining, Statistics
Lccn
2016-010317
Intended Audience
College Audience
Illustrated
Yes
Genre
Computers, Business & Economics, Mathematics, Social Science

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Picture 1 of 1

Chapman and Hall/CRC Statistics in the Social and Behavioral Sciences Ser.: Big Data and Social Science : A Practical Guide to Methods and Tools by Rayid Ghani (2016, Hardcover)

About this product

Product Information

Product Identifiers

Product Key Features

Dimensions

Additional Product Features

All listings for this product

item 1 Big Data and Social Science: A - Hardcover, by Foster Ian; Ghani - Very Good

item 2 Big Data and Social Science: A Practical Guide to Methods and Tools [Chapman & H

item 3 Big Data and Social Science: A Practical Guide to Methods and Tools (Chapman &

item 4 Big Data and Social Science: A Practical Guide to Methods and Tools (Chap - GOOD

item 5 Big Data and Social Science: A Practical Guide to Me...

item 6 BIG DATA AND SOCIAL SCIENCE: A PRACTICAL GUIDE TO METHODS By Ian Foster & Rayid

Best Selling in Textbooks

Designing Data-Intensive Applications : The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann (2017, Trade Paperback)

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Diagnostic and Statistical Manual of Mental Disorders DSM-5-TR by American Psychiatric Association (2022, Trade Paperback)

Research Design : Qualitative, Quantitative, and Mixed Methods Approaches by J. David Creswell and John W. Creswell (2022, Trade Paperback)

Self Heal by Design : The Role of Micro-organisms for Health by Barbara O'Neill (2018, Trade Paperback)

Leadership : Theory and Practice by Peter G. Northouse (2021, Trade Paperback, Revised edition)

Diagnostic and Statistical Manual of Mental Disorders : DSM-5-TR by American Psychiatric Association (2022, Hardcover)

Save on Textbooks

An Index to Precept Upon Precept Volumes 1 & 2

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International Building Code IBC 2021, Paperback International Code Council

International Code Council Ser.: 2021 International Residential

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