Computer Technology and Statistics Knowledge
A.Y. 2021/2022
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
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.
Lesson period: Second semester
Assessment methods: Giudizio di approvazione
Assessment result: superato/non superato
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second semester
Lessons will be held in-presence. If the Covid situation becomes worse, the lessons will be held remotely in synchronous on the Teams platform. Class recordings will be available asynchronously on the Teams platform.
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
- 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 teachers 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
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
The final test will consist in the development of a database using the statistical and computer techniques acquired during the course and a series of questions to assess the knowledge acquired.
- University credits: 6
Lessons: 48 hours
Professors:
Baldi Lucia, Tamburini Alberto Giuseppe Carlo Maria
Professor(s)
Reception:
on appointment
Via Celoria 2, Milan, Italy, 3rd floor (or by Skype/Teams/Zoom)
Reception:
by appointment (send an email)
Dipartimento di Scienze Agrarie e Ambientali (sezione Zootecnica) via Celoria 2 Milano