國立虎尾科技大學 |

An Introduction to R for Quantitative Economics = Graphing, Simulating and Computing /

紀錄類型:	書目-語言資料,印刷品 : 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.
面頁冊數:	XV, 109 p. 79 illus., 9 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Econometrics. -
電子資源:	https://doi.org/10.1007/978-81-322-2340-5
ISBN:	9788132223405

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. - 1st ed. 2015. - XV, 109 p. 79 illus., 9 illus. in color.online resource. - 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

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

556981
Econometrics.

LC Class. No.: HB139-141

Dewey Class. No.: 330.015195

An Introduction to R for Quantitative Economics = Graphing, Simulating and Computing /
LDR:02874nam a22004095i 4500 001 963580
003 DE-He213
005 20200920171354.0
007 cr nn 008mamaa
008 201211s2015 ii | s |||| 0|eng d
020 $a 9788132223405 $9 978-81-322-2340-5
024 7 $a 10.1007/978-81-322-2340-5 $2 doi
035 $a 978-81-322-2340-5
050 4 $a HB139-141
072 7 $a KCH $2 bicssc
072 7 $a BUS021000 $2 bisacsh
072 7 $a KCH $2 thema
082 0 4 $a 330.015195 $2 23
100 1 $a Dayal, Vikram. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1021921
245 1 3 $a An Introduction to R for Quantitative Economics $h [electronic resource] : $b Graphing, Simulating and Computing / $c by Vikram Dayal.
250 $a 1st ed. 2015.
264 1 $a New Delhi : $b Springer India : $b Imprint: Springer, $c 2015.
300 $a XV, 109 p. 79 illus., 9 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a SpringerBriefs in Economics, $x 2191-5504
505 0 $a 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.
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.
650 0 $a Econometrics. $3 556981
650 0 $a Statistics . $3 1253516
650 0 $a Computer simulation. $3 560190
650 0 $a Artificial intelligence. $3 559380
650 2 4 $a Statistics for Business, Management, Economics, Finance, Insurance. $3 1211158
650 2 4 $a Simulation and Modeling. $3 669249
650 2 4 $a Statistics and Computing/Statistics Programs. $3 669775
650 2 4 $a Artificial Intelligence. $3 646849
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9788132223412
776 0 8 $i Printed edition: $z 9788132223399
776 0 8 $i Printed edition: $z 9788132239802
830 0 $a SpringerBriefs in Economics, $x 2191-5504 $3 1256355
856 4 0 $u https://doi.org/10.1007/978-81-322-2340-5
912 $a ZDB-2-SBE
912 $a ZDB-2-SXEF
950 $a Business and Economics (SpringerNature-11643)
950 $a Economics and Finance (R0) (SpringerNature-43720)