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Library,Documentation and Information Science Division

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Gentle introduction to effective computing in quantitative research : what every research assistant should know / Harry J. Paarsch and Konstantin Golyaev.

By: Contributor(s): Material type: TextTextPublication details: Cambridge : The MIT Press, ©2015.Description: xxxvii, 738 pages : illustrations ; 24 cmISBN:
  • 9780262034111 (hardcover : alk. paper)
Subject(s): DDC classification:
  • 001.420285 23 P113
Contents:
1. Introduction -- 2. Productivity tools -- 3. Organizing data -- 4. Simple programming -- 5. Analyzing data -- 6. Geek stuff -- 7. Numerical methods -- 8. Solved examples -- 9. Extensions to Phython -- 10. Papers and presentations -- 11. Final thoughts.
Summary: This book offers a practical guide to the computational methods at the heart of most modern quantitative research. It will be essential reading for research assistants needing hands-on experience; students entering PhD programs in business, economics, and other social or natural sciences; and those seeking quantitative jobs in industry. No background in computer science is assumed; a learner need only have a computer with access to the Internet. Using the example as its principal pedagogical device, the book offers tried-and-true prototypes that illustrate many important computational tasks required in quantitative research. The best way to use the book is to read it at the computer keyboard and learn by doing. The book begins by introducing basic skills: how to use the operating system, how to organize data, and how to complete simple programming tasks. For its demonstrations, the book uses a UNIX-based operating system and a set of free software tools: the scripting language Python for programming tasks; the database management system SQLite; and the freely available R for statistical computing and graphics. The book goes on to describe particular tasks: analyzing data, implementing commonly used numerical and simulation methods, and creating extensions to Python to reduce cycle time. Finally, the book describes the use of LaTeX, a document markup language and preparation system.
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Includes bibliographical references and index.

1. Introduction --
2. Productivity tools --
3. Organizing data --
4. Simple programming --
5. Analyzing data --
6. Geek stuff --
7. Numerical methods --
8. Solved examples --
9. Extensions to Phython --
10. Papers and presentations --
11. Final thoughts.

This book offers a practical guide to the computational methods at the heart of most modern quantitative research. It will be essential reading for research assistants needing hands-on experience; students entering PhD programs in business, economics, and other social or natural sciences; and those seeking quantitative jobs in industry. No background in computer science is assumed; a learner need only have a computer with access to the Internet. Using the example as its principal pedagogical device, the book offers tried-and-true prototypes that illustrate many important computational tasks required in quantitative research. The best way to use the book is to read it at the computer keyboard and learn by doing. The book begins by introducing basic skills: how to use the operating system, how to organize data, and how to complete simple programming tasks. For its demonstrations, the book uses a UNIX-based operating system and a set of free software tools: the scripting language Python for programming tasks; the database management system SQLite; and the freely available R for statistical computing and graphics. The book goes on to describe particular tasks: analyzing data, implementing commonly used numerical and simulation methods, and creating extensions to Python to reduce cycle time. Finally, the book describes the use of LaTeX, a document markup language and preparation system.

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