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The Resource Quantitative economics with R : A Data Science Approach, by Vikram Dayal, (electronic book)

Quantitative economics with R : A Data Science Approach, by Vikram Dayal, (electronic book)

Creator
Summary
This book provides a contemporary treatment of quantitative economics, with a focus on data science. The book introduces the reader to R and RStudio, and uses expert Hadley Wickham's tidyverse package for different parts of the data analysis workflow. After a gentle introduction to R code, the reader's R skills are gradually honed, with the help of "your turn" exercises. At the heart of data science is data, and the book equips the reader to import and wrangle data, (including network data). Very early on, the reader will begin using the popular ggplot2 package for visualizing data, even making basic maps. The use of R in understanding functions, simulating difference equations, and carrying out matrix operations is also covered. The book uses Monte Carlo simulation to understand probability and statistical inference, and the bootstrapis introduced. Causal inference is illuminated using simulation, data graphs, and R code for applications with real economic examples, covering experiments, matching, regression discontinuity, difference-in-difference, and instrumental variables. The interplay of growth related data and models is presented, before the book introduces the reader to time series data analysis with graphs, simulation, and examples. Lastly, two computationally intensive methods--generalized additive models and random forests (an important and versatile machine learning method)--are introduced intuitively with applications. The book will be of great interest to economists--students, teachers, and researchers alike--who want to learn R. It will help economics students gain an intuitive appreciation of appliedeconomics and enjoy engaging with the material actively, while also equipping them with key data science skills.--
Language
eng
Work
Publication
Extent
1 online resource (xv, 326 pages)
Contents
  • Ch 1 Introduction
  • Ch 2 R and RStudio
  • Ch 3 Getting data into R
  • Ch 4 Wrangling and graphing data
  • Ch 5 Functions
  • Ch 6 Matrices
  • Ch 7 Probability and statistical inference
  • Ch 8 Causal inference
  • Ch 9 Solow model and basic facts of growth
  • Ch 10 Causal inference for growth
  • Ch 11 Graphing and simulating basic time series
  • Ch 12 Simple examples: forecasting and causal inference
  • Ch 13 Generalized additive models
  • Ch 14 Tree models
Isbn
9789811520358
Instance
Label
Quantitative economics with R : A Data Science Approach
Title
Quantitative economics with R
Title remainder
A Data Science Approach
Statement of responsibility
by Vikram Dayal
Creator
Subject
Language
eng
Summary
This book provides a contemporary treatment of quantitative economics, with a focus on data science. The book introduces the reader to R and RStudio, and uses expert Hadley Wickham's tidyverse package for different parts of the data analysis workflow. After a gentle introduction to R code, the reader's R skills are gradually honed, with the help of "your turn" exercises. At the heart of data science is data, and the book equips the reader to import and wrangle data, (including network data). Very early on, the reader will begin using the popular ggplot2 package for visualizing data, even making basic maps. The use of R in understanding functions, simulating difference equations, and carrying out matrix operations is also covered. The book uses Monte Carlo simulation to understand probability and statistical inference, and the bootstrapis introduced. Causal inference is illuminated using simulation, data graphs, and R code for applications with real economic examples, covering experiments, matching, regression discontinuity, difference-in-difference, and instrumental variables. The interplay of growth related data and models is presented, before the book introduces the reader to time series data analysis with graphs, simulation, and examples. Lastly, two computationally intensive methods--generalized additive models and random forests (an important and versatile machine learning method)--are introduced intuitively with applications. The book will be of great interest to economists--students, teachers, and researchers alike--who want to learn R. It will help economics students gain an intuitive appreciation of appliedeconomics and enjoy engaging with the material actively, while also equipping them with key data science skills.--
Assigning source
Provided by publisher
Cataloging source
FIE
http://library.link/vocab/creatorName
Dayal, Vikram
Dewey number
  • 330.01/51
  • 519
Illustrations
illustrations
Index
no index present
LC call number
HB143.5
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/subjectName
  • Economics
  • R (Computer program language)
  • Game theory
  • Economics
  • Statistics
  • Computer simulation
  • Sociology
Label
Quantitative economics with R : A Data Science Approach, by Vikram Dayal, (electronic book)
Instantiates
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Ch 1 Introduction -- Ch 2 R and RStudio -- Ch 3 Getting data into R -- Ch 4 Wrangling and graphing data -- Ch 5 Functions -- Ch 6 Matrices -- Ch 7 Probability and statistical inference -- Ch 8 Causal inference -- Ch 9 Solow model and basic facts of growth -- Ch 10 Causal inference for growth -- Ch 11 Graphing and simulating basic time series -- Ch 12 Simple examples: forecasting and causal inference -- Ch 13 Generalized additive models -- Ch 14 Tree models
Dimensions
unknown
Extent
1 online resource (xv, 326 pages)
File format
multiple file formats
Form of item
online
Isbn
9789811520358
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-981-15-2035-8
Other physical details
illustrations (some color)
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
  • on1140959580
  • (OCoLC)1140959580
Label
Quantitative economics with R : A Data Science Approach, by Vikram Dayal, (electronic book)
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Ch 1 Introduction -- Ch 2 R and RStudio -- Ch 3 Getting data into R -- Ch 4 Wrangling and graphing data -- Ch 5 Functions -- Ch 6 Matrices -- Ch 7 Probability and statistical inference -- Ch 8 Causal inference -- Ch 9 Solow model and basic facts of growth -- Ch 10 Causal inference for growth -- Ch 11 Graphing and simulating basic time series -- Ch 12 Simple examples: forecasting and causal inference -- Ch 13 Generalized additive models -- Ch 14 Tree models
Dimensions
unknown
Extent
1 online resource (xv, 326 pages)
File format
multiple file formats
Form of item
online
Isbn
9789811520358
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-981-15-2035-8
Other physical details
illustrations (some color)
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
  • on1140959580
  • (OCoLC)1140959580

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