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Course Description: A Brief Introduction to Programming with R
| Prof. Dr. Ulrich Matter | (University of St.Gallen)
10/09/2021
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Prerequisites

  • Install the latest R version. R is open source and freely available from here: https://stat.ethz.ch/CRAN/. Click on the respective link for your operating system (Windows, Mac, Linux), and follow the instructions.
  • Once R is installed, install RStudio from here: https://www.rstudio.com/products/rstudio/download/#download. Under "Installers for Supported Platforms", click on the respective installer for your operating system (Windows, Mac, etc.) and follow the instructions.
  • In case you have problems with the installations, you can create a free account for RStudio Cloud: https://rstudio.cloud/, and use RStudio Cloud for the exercises in this course (the functionality is essentially the same). Note, however, that it is strongly recommended to also have R/RStudio running on your own machine.

Course Content

Short summary

This course introduces students to the fundamental practices of programming with R in the context of economic research. The course briefly covers basic theoretical concepts and teaches basic skills in how to make use of the high-level programming language and statistical computing environment R. Examples and exercises are focused on data handling and data analysis tasks. The overall aim is to give students a solid overview of basic programming in R, and how they can potentially make use of R during their studies and research in economics.

Course Structure

This is a block course and part of the introductory week for MEcon students at HSG. The course is structured in three parts:

Part I: Background/Tools

  • Why R? Why programming?
  • The tools: R, RStudio.

Part II: First steps in R, core concepts.

  • First steps in R: R as a calculator, variables.
  • Basic programming concepts in R.
  • R objects and data structures.
  • R functions for basic statistics.

Part III: Working with Data in R.

  • Loading/importing data.
  • Visualizing data with R/ggplot.
  • Basic data analysis with R.

Detailed Schedule

  • 09:15-10:00 Introduction, Background, Tools (UM [TA, JS])
  • 10:00-10:15 Break, support with installations (TA, JS)
  • 10:15-11:00 Exercises, First Steps with R (TA, JS)
  • 11:00-11:15 Break, Q&A (TA, JS)
  • 11:15-12:00 First Steps with R, Concepts (TA, JS)
  • 12:00-13:15 Lunch (individually)
  • 13:15-14:00 Exercises (TA, JS)
  • 14:00-14:15 Break, Q&A (TA, JS)
  • 14:15-15:00 Working with Data (TA, JS)

(UM: Ulrich Matter, TA: Thomas Aeschbacher, JS: Jan Serwart)