An Introduction to R for Quantitative Economics

Graphing, Simulating and Computing

Business & Finance, Economics, Econometrics, Statistics
Cover of the book An Introduction to R for Quantitative Economics by Vikram Dayal, Springer India
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Author: Vikram Dayal ISBN: 9788132223405
Publisher: Springer India Publication: March 17, 2015
Imprint: Springer Language: English
Author: Vikram Dayal
ISBN: 9788132223405
Publisher: Springer India
Publication: March 17, 2015
Imprint: Springer
Language: English

This book gives an introduction to R to build up graphing, simulating and computing skills to enable one to see theoretical and statistical models in economics in a unified way. The great advantage of R is that it is free, extremely flexible and extensible. The book addresses the specific needs of economists, and helps them move up the R learning curve. It covers some mathematical topics such as, graphing the Cobb-Douglas function, using R to study the Solow growth model, in addition to statistical topics, from drawing statistical graphs to doing linear and logistic regression. It uses data that can be downloaded from the internet, and which is also available in different R packages. With some treatment of basic econometrics, the book discusses quantitative economics broadly and simply, looking at models in the light of data. Students of economics or economists keen to learn how to use R would find this book very useful.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book gives an introduction to R to build up graphing, simulating and computing skills to enable one to see theoretical and statistical models in economics in a unified way. The great advantage of R is that it is free, extremely flexible and extensible. The book addresses the specific needs of economists, and helps them move up the R learning curve. It covers some mathematical topics such as, graphing the Cobb-Douglas function, using R to study the Solow growth model, in addition to statistical topics, from drawing statistical graphs to doing linear and logistic regression. It uses data that can be downloaded from the internet, and which is also available in different R packages. With some treatment of basic econometrics, the book discusses quantitative economics broadly and simply, looking at models in the light of data. Students of economics or economists keen to learn how to use R would find this book very useful.

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