Knowledge and understanding: Students will learn about R syntax, variable types, and the main libraries for handling and analysing data.
Ability to apply knowledge and understanding: Students will be able to import data into R, carry out the main data management operations, and perform descriptive analyses using R functions.
Making judgements: Students must be able to use the acquired knowledge both on a theoretical and operational level with autonomous assessment skills, in various applicative contexts.
Communication skills: Students will acquire the technical language typical of the discipline to communicate clearly and without ambiguity with both statisticians and non-statisticians.
Learning skills: Students will develop adequate learning skills that allow them to continue to study the subject independently.
Connections of the course with other courses in the programme: The topics introduced in this course will allow the students to properly understand numerical data within other disciplines.
Basic knowledge of descriptive statistics (contents of the first part of the course of Statistics)
Lectures and practicals with computer.
1. Introduction to R and Rstudio
2. Data types in R: vectors, matrices, data.frame
3. Use of libraries and main libraries in R
4. Data import in R
5. Data handling in R
6. Graphics in R
7. Contingency tables in R
8. Linear regression in R
Course notes provided by the teacher
Ricevimento: Tuesday 16.30-18.00
CORRADO LAGAZIO (President)
MARTA NAI RUSCONE
FABIO RAPALLO (Substitute)
February 2024
The exam will consist in the preparation and discussion of a small data analysis project in R
The project serves to evaluate student's ability and autonomy in using R for data analysis.
