Courses catalog
Data science and statistical analysis

Introduction to statistical analysis in Social Sciences with R

DESCRIPTION

Nowadays there is a growing need to work with diverse datasets in all areas of science, from economics, communication, social sciences, or experimental. This course provides the basics of working with, describing, analysing and visualising scientific data using the R and RStudio tools. R was initially designed by Robert Gentleman and Ross Ihaka, members of the Department of Statistics at the University of Auckland, New Zealand. One of the great advantages of R is that today it is actually the fruit of the efforts of thousands of people around the world who collaborate in its development. The aim of this course is to present these tools, thus facilitating the tasks of analysis and graphical representation of data sets.

STRUCTURE

Module 1 – Current overview of data analysis in Social Sciences

  • Relevance of statistical analysis in social sciences.
  • Applications and needs of analysis in areas such as economics, communication, among others.
  • Challenges and opportunities in the analysis of large datasets.

Module 2 – Introduction to R and RStudio

  • Introduction to RStudio and its interface.
  • Benefits and features of R as an open source tool.

Module 3 – Data management and data processing with R

  • Importing and cleaning data in R.
  • Processing datasets: operations, filtering and grouping.
  • Transforming and preparing data for analysis.

Module 4 – Descriptive analysis and graphic visualisation with R

  • Basic descriptive statistics in R.
  • Creating graphs and visualisations: from histograms to complex graphs.
  • Interpreting and communicating graphical results.

Module 5 – Global community and additional resources in R

  • Popular R repositories and packages for Social Sciences.
  • Continuous learning paths and resources to deepen your knowledge of R.