| 书目名称 | Quantitative Economics with R | | 副标题 | A Data Science Appro | | 编辑 | Vikram Dayal | | 视频video | | | 概述 | Employs a popular data science approach while discussing concepts and applications related to economics.Explains causal inferences with the aid of simulations, data graphs, and sample applications.Int | | 图书封面 |  | | 描述 | .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 bootstrap is introduced. Causal inferenceis 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 t | | 出版日期 | Textbook 2020 | | 关键词 | R; Time Series Data; Causality; Graph; Data Wrangling; Solow Model | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-15-2035-8 | | isbn_softcover | 978-981-15-2037-2 | | isbn_ebook | 978-981-15-2035-8 | | copyright | Springer Nature Singapore Pte Ltd. 2020 |
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发表于 2025-3-21 18:33:50
