A Gentle Introduction to Effective Computing in Quantitative Research: What Every Research Assistant Should Know (MIT Press)

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9780262034111: A Gentle Introduction to Effective Computing in Quantitative Research: What Every Research Assistant Should Know (MIT Press)

A practical guide to using modern software effectively in quantitative research in the social and natural sciences.

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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About the Author:

After initial appointments at the University of British Columbia and the University of Western Ontario, Harry J. Paarsch held the position of Professor of Economics and Robert Jensen Research Fellow in the Henry B. Tippie College of Business at the University of Iowa and subsequently Chair in Economics at the University of Melbourne. From 2011 to 2014, he worked as an applied economist and data scientist for Amazon.com.

Konstantin Golyaev is an applied economist and data scientist who lives and works in Seattle.

Review:

This book covers exactly the material I ask my research assistants and students to learn and it covers it very well. Pattern recognition and data organization have become key tools of good working economists. The authors are proven experts and very creative quantitative researchers and it is good for us that they have written this 'gentle introduction.'

(Thomas J. Sargent, Nobel Laureate in Economics, 2011)

This book is a good place for the novice programmer to begin.

(James J. Heckman, Nobel Laureate in Economics, 2000)

This book will be invaluable to almost everyone except the most advanced computer geeks. It is an easy-to-read guide to the essential practical computer tools that are almost never formally taught in class but which every PhD student needs to know in order to be productive. Senior economists and faculty can also profit from this book by helping them reduce their dependence on computer-literate research assistants to do many tasks that Paarsch and Golyaev show are easy to do themselves with just a small amount of investment.

(John Rust, Professor of Economics, Georgetown University)

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Book Description MIT Press Ltd, United States, 2016. Hardback. Book Condition: New. Language: English . Brand New Book. A practical guide to using modern software effectively in quantitative research in the social and natural sciences.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. Bookseller Inventory # AAC9780262034111

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