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An Introduction to R for Quantitative Economics Graphing Simulating and Computing at Meripustak

An Introduction to R for Quantitative Economics Graphing Simulating and Computing by Vikram Dayal , Springer

Books from same Author: Vikram Dayal

Books from same Publisher: Springer

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  • General Information  
    Author(s)Vikram Dayal
    PublisherSpringer
    ISBN9788132223399
    Pages109
    BindingPaperback
    LanguageEnglish
    Publish YearMarch 2015

    Description

    Springer An Introduction to R for Quantitative Economics Graphing Simulating and Computing by Vikram Dayal

    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._x000D_ Table of contents :- _x000D_ 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._x000D_



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