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An introduction to R for quantitativ...

Dayal, Vikram.

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An introduction to R for quantitative economics = graphing, simulating and computing /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	An introduction to R for quantitative economics/ by Vikram Dayal.
其他題名:	graphing, simulating and computing /
作者:	Dayal, Vikram.
出版者:	New Delhi :Springer India : : 2015.,
面頁冊數:	xv, 109 p. :ill. (some col.), digital ;24 cm.
內容註:	Chapter 1. Introduction -- Chapter 2. R and RStudio -- Chapter 3. Getting data into R -- Chapter 4. Supply and demand -- Chapter 5. Functions -- Chapter 6. The Cobb-Douglas Function -- Chapter 7. Matrices -- Chapter 8. Statistical simulation -- Chapter 9. Anscombe's quartet: graphs can reveal -- Chapter 10. Carbon and forests: graphs and regression -- Chapter 11. Evaluating training -- Chapter 12. The Solow growth model -- Chapter 13. Simulating random walks and shing cycles -- Chapter 14. Basic time series.
Contained By:	Springer eBooks
標題:	R (Computer program language) -
電子資源:	http://dx.doi.org/10.1007/978-81-322-2340-5
ISBN:	9788132223405 (electronic bk.)

An introduction to R for quantitative economics = graphing, simulating and computing /
Dayal, Vikram.

An introduction to R for quantitative economicsgraphing, simulating and computing /[electronic resource] :by Vikram Dayal. - New Delhi :Springer India :2015. - xv, 109 p. :ill. (some col.), digital ;24 cm. - SpringerBriefs in economics,2191-5504. - SpringerBriefs in economics..

Chapter 1. Introduction -- Chapter 2. R and RStudio -- Chapter 3. Getting data into R -- Chapter 4. Supply and demand -- Chapter 5. Functions -- Chapter 6. The Cobb-Douglas Function -- Chapter 7. Matrices -- Chapter 8. Statistical simulation -- Chapter 9. Anscombe's quartet: graphs can reveal -- Chapter 10. Carbon and forests: graphs and regression -- Chapter 11. Evaluating training -- Chapter 12. The Solow growth model -- Chapter 13. Simulating random walks and shing cycles -- Chapter 14. Basic time series.

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.

ISBN: 9788132223405 (electronic bk.)

Standard No.: 10.1007/978-81-322-2340-5doiSubjects--Topical Terms:

784593
R (Computer program language)

LC Class. No.: QA276.45.R3

Dewey Class. No.: 005.133

An introduction to R for quantitative economics = graphing, simulating and computing /
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520 $a 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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