This course assumes basic knowledge of descriptive and inferential statistics, along with minimal computer literacy (Windows, Mac, or Linux). Participants should bring their own device.
Knowledge: - Understand the R programming environment. - Familiarize yourself with the main objects used in R. - Learn how to import and export data. - Identify and utilize suitable statistical tools in R.
Skills: - Navigate and use the R programming environment. - Create and manipulate data objects in R. - Prepare structured tables and informative graphs. - Import/export datasets and define user functions. - Recognize appropriate statistical techniques for data analysis.
Communication Skills: - Present results effectively using graphs and tables. - Perform critical analysis of outcomes and their implications.
Learning Skills: - Develop self-sufficiency and confidence in using R as a programming environment.
By the end of this course, you will be able to:
W. N. Venables, D. M. Smith, and the R Core Team: An Introduction to R. Notes on R: A Programming Environment for Data Analysis and Graphics. Available on CRAN.
Additional tutorials and resources available online.
| Hours | Topics |
|---|---|
| 5 | What is R Programming? Introduction and basics. How to download and install R and RStudio on Mac/Windows. Understanding R data types, operators, and basic tutorials on R matrices. |
| 5 | Decision-making statements: if-else, for/while loops (with examples using lists and matrices). Importing data (CSV, Excel, SPSS, etc.) and the utilization of apply functions. |
A work by Gianluca Sottile
gianluca.sottile@unipa.it