Statistics
Course objectives
Main goal of this course is to develop the students’ ability to think statistically. In particular, after following this course students should be able to recognize questions for which statistics would be useful and to answer them using the appropriate procedures; be able to recognize and explain the central role of variability in the field of statistics; understand and exploit the potential of distribution models, being aware of their limitations; understand and use statistical inference techniques in a variety of settings.
Channel 1
                      
                ROBERTA VARRIALE
                Lecturers' profile
              
            Program - Frequency - Exams
Course program
Introduction
Probability Theory, basics
Random Variables
Probability Models
Sample Statitsics Distributions
Theory of Point Estimation
Theory of Interval Estimation
Testing Statistical Hypotheses, basics
Testing Statistical Hypotheses, power function
Prerequisites
Basic mathematics knowledge
Books
Sheldon M. Ross "Probabilità e statistica per l'ingegneria e le scienze", Edizione Apogeo, Milano, 2003, Capitoli 1-8.
Pagano M., Gauvreau K. "Biostatistica", IDELSON-GNOCCHI
Teaching mode
Attendance of teaching classes is not compulsory.
The course is structured in frontal theoretical lessons, for a global amount of 48 hours of teaching (6 CFU)
At the end of the course, a self-assessment test will take place, to verify students' level of understanding, and review some key aspects of the program.
Frequency
Attending the course is not mandatory, but is strongly recommended
Exam mode
The exam test aims at verifying the students' level of understanding with regards to basic topic of parametrical statistical inference, with a view towards comprehension of its basic concepts, and skills acquired in applied perspective. The final mark ranges from 18/30 to 30/30 cum laude. The assessment consists in a written test (lasting approximately two hours) and a viva examination. The aim is at veryfing whether the student has achieved the objectives in terms of understanding and correctly applying  main parametric inference methods.
Lesson mode
Attendance of teaching classes is not compulsory.
The course is structured in frontal theoretical lessons, for a global amount of 48 hours of teaching (6 CFU)
At the end of the course, a self-assessment test will take place, to verify students' level of understanding, and review some key aspects of the program.
              - Lesson code1017413
- Academic year2025/2026
- CourseManagement Engineering
- CurriculumSingle curriculum
- Year3rd year
- Semester2nd semester
- SSDSECS-S/01
- CFU6
 
        