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Regular version of the site

R for Social Science: Introduction to Programming Language

Monday 1 July - Friday 12 July, 2019

2 weeks = 2 ECTS

Course description

Data analysis skills are in high demand in business and academia alike. However, coding skills alone often are not enough to solve common for the research process problems, especially in the context of social sciences. This course will introduce students to R and the tidy verse approach in the social science context. Participants will learn elegant ways to waggle and visualize data, the fundamental skills translatable to an analysis of any kind. Additionally, we will address the best practices in data analysis, research organization and communication as well as typical limitations of the ‘one-language-paradigm’, showing how to go beyond R ecosystem when needed.  

Brief course content

Statistical computing and organization of research

  • How to organize your research: fundamental problems and best practices
  • Statistical computing for social sciences: introduction to R
  • Reproducible research with R and R Studio
  • Problem solving in data analysis: the usual way and the tidy way

Data wrangling

  • Storing and reading data
  • Data manipulation with pipelines
  • Data cleaning
  • Case study: cleaning textual data

Exploratory data analysis and research communication

  • Elements of exploratory data analysis
  • The grammar of graphics
  • Communicating your research: building applications and packages    

Learning outcome

  • Basic understanding of R
  • Practical research organization
  • Data manipulation
  • Data cleaning
  • Data visualization
  • Basic exploratory analysis
  • Building R packages and shiny apps

Prerequisites

The course is aimed at social science students in marketing, sociology, political science, and assumes no prior programming knowledge.

Teaching 

Lectures, workshops, case study and group project

Assessment

Group project

Course lecturer

Sergey Pashakhin

Research Assistant

Proceed to application