- Docente: Stefania Mignani
- Credits: 3
- Language: Italian
- Teaching Mode: Traditional lectures
Learning outcomes
The main goals of this course are: • to understand what data are and what their role in society is; • to discriminate data based on specific use; • to synthesize, create visualizations and representations of data; • to understand the issues involved in the use of data; • to promote critical thinking based on information from data analysis • to recognize when data are tampered with, misrepresented and used in a misleading manner • to communicate information about the data to people who are not expert on the subject (data storytelling). After completing this course, students will be able to: • Provide examples of how people use data every day • Apply critical thinking skills when working with data • Identify data analysis tools and techniques appropriate for the analysis
Course contents
NOTICE
THE COURSE WILL BE HELD IN THE PERIOD: MID MARCH-MID MAY
THE HOURS OF LESSON ARE 4 WEEKLY, TWO FOR EACH LESSON THE COURSE TIMETABLE WILL BE AVAILABLE BY DECEMBER
part 1: Transforming data into knowledge
1. How to obtain the data: institutional sources, open data and ad hoc surveys2. How to process data: the basic tools of statistical analysis.
3. How to represent the data: the main types of graphs
Part 2 Reasoning on the information obtained with the analyses
1. Infographics and errors in graphical representations
2. Data story telling
Part 3 (Practical activity): Critical evaluation of case studies from society and research contexts
1. Analysis of a data set using excel
Readings/Bibliography
David Spiegelhalter, L’arte della statistica. Cosa ci insegnano i dati, Piccola Biblioteca, Einaudi, 2020
Alberto Cairo, Come i grafici mentono. Capire meglio le informazioni visive, Raffaello Cortina Editore, 2020
Teaching methods
Lessons, laboratory activities and case study.
The blended modality is planned for 35% of the hours, therefore 8 hours will also be held online. Attendance of at least 12 hours is required in order to take the exam.
Assessment methods
The exam aims to evaluate the skills achieved in the ability to critically analyze the quantitative information of a real problem.
The student must written a report describing the results of the analysis on a real data set.
The report must be sent two days before the exam round and will be discussed on the day of the exam.
The exam grade is expressed out of thirty
Teaching tools
slides; paper; open data
Some lessons will be recorded
Office hours
See the website of Stefania Mignani