SummeR School: Introduction to R for Statistical Analysis

Professor involved: Davide Gentilini and Francesco Ranucci

Course learning outcomes/abstract: In today’s professional landscape, effective data management and analysis are critical components across various domains. However, proprietary software tools often come with high costs and limited applications. This course is designed to equip participants with the necessary knowledge and skills to harness the potential of R, a versatile and powerful open-source language and software environment for statistical analysis and data manipulation.
R stands out as a comprehensive solution, offering simplicity in data handling, a robust suite of tools for vector and matrix operations, an extensive repository of integrated statistical functions, versatile graphical capabilities, and the ability to create custom applications using real object-oriented programming.
The course provides an in-depth introduction to R programming, with a specific focus on essential aspects including data manipulation, data management, statistical test selection, and data visualization through R’s extensive graphic capabilities. Throughout the course, participants will work with diverse datasets and practical examples relevant to their fields of interest, enabling them to grasp and apply the knowledge acquired effectively.

Goals: Foster Proficiency in R Usage: By the end of the course, participants should have a strong command of R’s capabilities and be able to utilize it as a powerful tool for data management and analysis. Data Management Skills: Participants will gain expertise in data cleaning, transformation, and organization, enabling them to work with real-world datasets efficiently.
Statistical Analysis: The course will empower participants to identify appropriate statistical tests for various research questions, interpret their results, and make informed decisions based on the data. Data Visualization: Participants will learn to harness R’s extensive graphic potential to effectively convey insights from data through visually appealing and informative plots and charts. Custom Programming: The course will enable participants to create their own functions, apply conditional and cyclic structures, and build custom applications tailored to their specific data analysis needs. Practical Application: By working with relevant datasets and examples from various fields, participants will develop the ability to apply R’s capabilities to real-world scenarios and challenges.
Upon completing this course, participants will be well-prepared to integrate R into their work, enhancing their data management and analysis capabilities while reducing reliance on costly proprietary software solutions.

Number of hours and planning: The course will last at least 20 hours (5 CFU), and will be divided into 5 meetings. Individual meetings can also be attended.

Period: The course will be held throughout May 2024, with afternoon sessions from 16:00 to 18:00 on May 2-3, 9-10, 16-17, 23-24, and 30-31, making it convenient for working professionals and learners

Delivery mode and location ( in presence, on line, ecc): Online; On line


Language: english

Evaluation criterial:The degree of learning will be tested at the end of the course by subjecting the participants to a test. The verification test will consist of a dataset to analyze and a series of questions related to the dataset to answer

Credits (CFU): 5