Physics and Statistics
A.Y. 2019/2020
Learning objectives
The aim of this course is:
-To provide the basic notions and the methods of biomedical physics;
-To provide the principles of mechanics and their applications to human locomotion;
-To provide the principles of fluid dynamics and thermodynamics and their applications to human physiology.
-To provide the basic notions and the methods of biomedical physics;
-To provide the principles of mechanics and their applications to human locomotion;
-To provide the principles of fluid dynamics and thermodynamics and their applications to human physiology.
Expected learning outcomes
At the end of the course, the students:
- will be able to use, in a rigorous manner, the language and the units of Physics;
- will be able to describe quantitatively the mechanics of locomotion and some key physiological processes.
- will be able to use, in a rigorous manner, the language and the units of Physics;
- will be able to describe quantitatively the mechanics of locomotion and some key physiological processes.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
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
Prerequisites for admission
None required
Assessment methods and Criteria
Written and oral examination.
Fisica applicata
Course syllabus
Observational Studies.
Measures in Epidemiology.
Basic statistical methods.
Statistical inference and significance.
Measures of association and risk.
Variability of estimates and measure errors.
Error, bias and inference.
Measures in Epidemiology.
Basic statistical methods.
Statistical inference and significance.
Measures of association and risk.
Variability of estimates and measure errors.
Error, bias and inference.
Teaching methods
Lectures
Teaching Resources
handouts provided by the teacher in the classroom
Informatica
Course syllabus
· Foundations of Computer Science
o Introduction to Computer Science
o Information coding
o Computer structure
o Programs and software
o The "Infosphera" risks
· Spreadsheets
o Introduction to spreadsheets
o General functions in Excel
o Statistical functions in Excel
o Chart creation in Excel
· Information management
o Introduction to information management
o Data storing and databases
o Relational databases
o Database creation
o Query composition
o Web databases
· Internet and web
o Computer networks
o The Internet network
o Web architecture
o Web standards
o Web contents
o Search engines
o Web evolutions
o Introduction to Computer Science
o Information coding
o Computer structure
o Programs and software
o The "Infosphera" risks
· Spreadsheets
o Introduction to spreadsheets
o General functions in Excel
o Statistical functions in Excel
o Chart creation in Excel
· Information management
o Introduction to information management
o Data storing and databases
o Relational databases
o Database creation
o Query composition
o Web databases
· Internet and web
o Computer networks
o The Internet network
o Web architecture
o Web standards
o Web contents
o Search engines
o Web evolutions
Teaching methods
The Course is provided as a blended-learning course.
For acquisition of expected knowledge, a student has to browse the program contents on the online course according to an e-learning modality. Contents are organized into the following training courses: G) Foundations of Computer Science, F) Spreadsheets, B) Information management, and I) Internet and web. A training course is then articulated into thematic modules. Students have to pass a self-evaluation test at the end of each thematic module. Initially, a student can access just an introductory module. The access to subsequent modules is progressively enabled when the test of available modules is successfully passed. For acquisition of expected skills, a student can attend two exercise sessions in a computer-science room. Each exercise session is three hours long. The attendance to exercise sessions is not a mandatory requirement for successfully pass the Course and obtain the credits, however students are strongly encouraged to attend the exercise sessions.
For acquisition of expected knowledge, a student has to browse the program contents on the online course according to an e-learning modality. Contents are organized into the following training courses: G) Foundations of Computer Science, F) Spreadsheets, B) Information management, and I) Internet and web. A training course is then articulated into thematic modules. Students have to pass a self-evaluation test at the end of each thematic module. Initially, a student can access just an introductory module. The access to subsequent modules is progressively enabled when the test of available modules is successfully passed. For acquisition of expected skills, a student can attend two exercise sessions in a computer-science room. Each exercise session is three hours long. The attendance to exercise sessions is not a mandatory requirement for successfully pass the Course and obtain the credits, however students are strongly encouraged to attend the exercise sessions.
Teaching Resources
The teaching stuff is online at https://3cfuinformatica.unimi.it
Statistica medica
Course syllabus
- Basics of rototranslational kinematics of the rigid body
- Basics of rototranslational dynamics of the rigid body
- Measurement and representation of biomechanical parameters
- Kinematic analysis of the movement
- Dynamic analysis of the movement
- Basics of rototranslational dynamics of the rigid body
- Measurement and representation of biomechanical parameters
- Kinematic analysis of the movement
- Dynamic analysis of the movement
Teaching methods
Lectures and seminars
Teaching Resources
I.A. Kapandji, Anatomia funzionale. Maloine-Monduzzi Editoriale
Fisica applicata
FIS/07 - APPLIED PHYSICS - University credits: 3
Lessons: 30 hours
Professor:
Giavazzi Fabio
Shifts:
-
Professor:
Giavazzi Fabio
Informatica
INF/01 - INFORMATICS - University credits: 3
Basic computer skills: 18 hours
Statistica medica
MED/01 - MEDICAL STATISTICS - University credits: 2
Lessons: 20 hours
Professor:
La Vecchia Carlo Vitantonio Battista
Shifts:
-
Professor:
La Vecchia Carlo Vitantonio BattistaProfessor(s)