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An introduction to R for quantitative economics [electronic resource] : graphing, simulating and computing / Vikram Dayal.

Dayal, Vikram, author.
2015
QA276.45.R3
Available Online
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Title
An introduction to R for quantitative economics [electronic resource] : graphing, simulating and computing / Vikram Dayal.
Author
Dayal, Vikram, author.
ISBN
9788132223405 electronic book
8132223403 electronic book
9788132223399
DOI
https://doi.org/10.1007/978-81-322-2340-5
Published
New Delhi : Springer, 2015.
Language
English
Description
1 online resource (xv, 109 pages) : illustrations.
Item Number
10.1007/978-81-322-2340-5 doi
Call Number
QA276.45.R3
Dewey Decimal Classification
005.13/3
Summary
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.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed March 25, 2015).
Series
SpringerBriefs in economics.
Available in Other Form
Print version: 9788132223399
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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.

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