Computer technology and statistics knowledge

A.Y. 2020/2021
Overall hours
Learning objectives
This course is designed to integrate and strengthen the knowledge of statistical analysis of data with the aim of providing students with the necessary tools to deal with those situations in which elaborations of empirical data are required.
To this end, using the appropriate IT tools, descriptive, bivariate and inferential statistics will be developed. The use of Excel will be proposed, both in the basic version and in the advanced version "Data Analysis". The course will take place in an IT laboratory
Expected learning outcomes
Ability to manage databases and find the best solutions for creating new databases. Ability to create charts and tables. Ability to process data with Excel and identify the best statistical tools. Ability to find suitable solutions for the communication of the results obtained from data processing.
Course syllabus and organization

Single session

Lesson period
Second semester
Lectures will mostly be held in remote on MS-Teams. The lecture recordings will be available to students (links in Ariel).
Course syllabus
- Basic principles of using Excel
- Main public and private databases for the analysis of the agricultural and food sector
- Main methodologies of descriptive statistics, regression, one-way analysis of variance
- Use of the Excel "Data Analysis" package
Prerequisites for admission
The student should know the mathematical language
Teaching methods
The lessons will be both theoretical and in the form of a computer lab.
Teaching Resources
1) Material provided by the teacher on Ariel
2) suggested:
"Introduzione alla Statistica", di M. K. Pelosi e T. M. Sandifer, ed. McGraw-Hill, 2009.
"Analisi Statistica con Excel", di D. Giuliani, M. M. Dickson, ed. Apogeo, 2015
Assessment methods and Criteria
To verify the learning of the course, there are exercises to be carried out during the course and to be delivered to the teacher. The final test will consist of the development of a database using the statistical and computer techniques acquired during the course.
- University credits: 6
Lessons: 48 hours
Professor: Baldi Lucia
Educational website(s)
on appointment
Via Celoria 2, Milan, Italy, 3rd floor (or by Skype/Teams/Zoom)