Computer Technology and Statistics Knowledge
A.Y. 2022/2023
Learning objectives
The course aims to provide:
- knowledge of descriptive statistics.
- notions for the use of position and variability indicators.
- acquisition of the principles and techniques of regression and correlation between variables.
- knowledge of the fundamental notions of computer science.
- skills on spreadsheet management, to create formulas, to carry out statistical tests, and to create graphs.
- ability to use search engines for information retrieval.
- knowledge of descriptive statistics.
- notions for the use of position and variability indicators.
- acquisition of the principles and techniques of regression and correlation between variables.
- knowledge of the fundamental notions of computer science.
- skills on spreadsheet management, to create formulas, to carry out statistical tests, and to create graphs.
- ability to use search engines for information retrieval.
Expected learning outcomes
At the end of the course the student should be able to:
- describe phenomena using the main statistical indicators.
- prepare sample survey plans.
- apply the analysis of the variance with one and two factors.
- objectively evaluate the results of statistical analyses.
- use software packages for data management, statistical processing, data storage and their graphic representation.
- be able to use bibliographic databases.
- describe phenomena using the main statistical indicators.
- prepare sample survey plans.
- apply the analysis of the variance with one and two factors.
- objectively evaluate the results of statistical analyses.
- use software packages for data management, statistical processing, data storage and their graphic representation.
- be able to use bibliographic databases.
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
Course syllabus
Statistics
Types of variables; the representation of statistical data; descriptive and dispersion measures; probability distributions; parametric and non-parametric statistical tests; linear regression; multiple linear and logistic regression.
Informatics
Basic principles of Excel (or other spreadsheets)
Data processing for the main statistical analyses and use of advanced graphs.
Using Pivot Tables and the Excel "Data Analysis" package.
Types of variables; the representation of statistical data; descriptive and dispersion measures; probability distributions; parametric and non-parametric statistical tests; linear regression; multiple linear and logistic regression.
Informatics
Basic principles of Excel (or other spreadsheets)
Data processing for the main statistical analyses and use of advanced graphs.
Using Pivot Tables and the Excel "Data Analysis" package.
Prerequisites for admission
Statistics
Passing the mathematics exam, or at least attending the course, is an important element for understanding the topics covered in the course.
Informatics
Not essential, but a minimum knowledge of the PC and the Windows operating system is welcome.
Passing the mathematics exam, or at least attending the course, is an important element for understanding the topics covered in the course.
Informatics
Not essential, but a minimum knowledge of the PC and the Windows operating system is welcome.
Teaching methods
Statistics
The topics included in the course program will be presented during lectures. Self-assessment tests will be proposed during the course. During the lessons, the use of a simple calculator will be required (a scientific calculator is not required).
Informatics
The topics included in the course program will be presented during lectures. Self-assessment Excel excercises will be proposed during the course.
In all the scheduled lessons, the PC will be used (for G26 and G28 in the IT classroom, for G31 using the personal computer to bring to the classroom). For G31, some exercises in the IT classroom are foreseen.
The topics included in the course program will be presented during lectures. Self-assessment tests will be proposed during the course. During the lessons, the use of a simple calculator will be required (a scientific calculator is not required).
Informatics
The topics included in the course program will be presented during lectures. Self-assessment Excel excercises will be proposed during the course.
In all the scheduled lessons, the PC will be used (for G26 and G28 in the IT classroom, for G31 using the personal computer to bring to the classroom). For G31, some exercises in the IT classroom are foreseen.
Teaching Resources
Statistics
A. Petrie & P. Watson, "Statistic for veterinary and animal science" third edition (available free in pdf version)
Informatics
"Analisi Statistica con Excel", di D. Giuliani, M. M. Dickson, ed. Apogeo, 2015.
Any video course on the web that helps you perform Excel exercises.
The didactic material, relating to both the statistics and informatics sections, will be available on the course team (code s9n1y3k).
A. Petrie & P. Watson, "Statistic for veterinary and animal science" third edition (available free in pdf version)
Informatics
"Analisi Statistica con Excel", di D. Giuliani, M. M. Dickson, ed. Apogeo, 2015.
Any video course on the web that helps you perform Excel exercises.
The didactic material, relating to both the statistics and informatics sections, will be available on the course team (code s9n1y3k).
Assessment methods and Criteria
The exam, which includes both questions and excel exercises relating to the statistics and informatics parts, will involve the resolution of a closed-question test and exercise (using PC). The evaluation obtained by the student will be proportional to the number of questions answered exactly, and will be registered as "APPROVED" or "NOT APPROVED".
- University credits: 6
Lessons: 48 hours
Professors:
Parma Pietro, Tamburini Alberto Giuseppe Carlo Maria
Professor(s)
Reception:
by appointment
Agricultural and Environmental Sciences - Production, Landscape, Agroenergy, Building 6
Reception:
by appointment (send an email)
Dipartimento di Scienze Agrarie e Ambientali (sezione Zootecnica) via Celoria 2 Milano