Data Analysis with R for Agricultural Economists


Level: Master and PhD
Taught at: University of Göttingen
When: Every Summer term (2018-2022)
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Learning Objectives

Students learn

  • the basic functionality of the statistical software package R
  • how to retrieve, manage and analyze datasets
  • an independent and autonomous usage of online resources (e.g. packages, support, R-literature)
  • implementation of standard econometric tools

in context of topics in agricultural economics. The course aims at providing a tool- set for the successful completion of final thesis with quantitative focus.

Course Outline

The course is blocked in two weeks and split into two main components: The first one is mainly concerned with R programming while the second part deals with applied analysis of datasets connected to agricultural economics:

  1. Programming in R: Introduction and basic functionalities, data management, data visualization, coding styles, functions and programming, dynamic report generation
  2. Applied Data Analysis: data sources in agricultural economics and related API packages, application of selected econometric techniques

Course Requirements

Term project (100%) Examination requirements:

Students proof that they are capable of

  • finding relevant data, manage and manipulate datasets
  • applying an appropriate econometric or statistical method and write corresponding code which is comprehensive and clean
  • interpreting data and results through the use of graphical tools.