OVERVIEW

We will explore together the fundamentals of the R language, a powerful tool for data analysis. The course will cover the basic concepts of programming in R, data manipulation, and creating graphics. Additionally, we will learn to conduct simple statistical analyses. Through practical and theoretical lessons, you will acquire useful skills to transform data into meaningful information.

AIMS AND CONTENT

LEARNING OUTCOMES

The course aims to provide skills in the quantitative analysis of economic and social phenomena and in the use of R software for statistical data analysis.

AIMS AND LEARNING OUTCOMES

At the end of the course, students will:

• Know the syntax of R, variable types, and the main libraries for data management and analysis.
• Be able to import data into R, perform the main data management operations, and conduct descriptive analyses using R functions.

PREREQUISITES

Basic knowledge of descriptive statistics (contents of the first part of the course of Statistics)

TEACHING METHODS

Lectures and practicals with computer. Attendance is mandatory.

Students who have valid certification of physical or learning disabilities  and who wish to discuss possible accommodations or other circumstances regarding lectures, coursework and exams, should speak both with the instructor and with Prof.ssa Elena Lagomarsino (elena.lagomarsino@unige.it),  the Department’s disability liaison

SYLLABUS/CONTENT

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

RECOMMENDED READING/BIBLIOGRAPHY

Course notes provided by the teacher

TEACHERS AND EXAM BOARD

Exam Board

CORRADO LAGAZIO (President)

MARTA NAI RUSCONE

FABIO RAPALLO

LESSONS

LESSONS START

February

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

The exam consists of a practical laboratory test in which students are required to analyze and process a dataset provided by the instructor.

For students in the Master's Degree program in Management, this course is classified as "Other training activity". Students who pass the exam will receive a grade of "Idoneo", while students who fail the exam will receive a grade of "Non Idoneo".

ASSESSMENT METHODS

The assessment aims to evaluate the student’s ability to correctly and independently apply the data analysis techniques covered during the course. The evaluation will take into account the methodological correctness of the analyses performed, as well as their completeness and appropriateness.

Exam schedule