Description
A Gentle Introduction to Effective Computing in - What Every Research Assistant Should Know
Authors: Paarsch Harry J., Golyaev Konstantin
Language: EnglishSubject for A Gentle Introduction to Effective Computing in - What...:
Approximative price 53.46 €
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Add to cart the book of Paarsch Harry J., Golyaev Konstantin
Publication date: 06-2016
840 p. · 18.5x22.8 cm · Hardback
840 p. · 18.5x22.8 cm · Hardback
Description
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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.
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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