STATISTICS

The course is one of the quantitative training activities of the Bachelor's Degree Programme in Physical Engineering. The aim is to get the student familiar with the main statistical and probabilistic methods for engineering and the sciences.
The course provides knowledge of statistics and probability, as well as skills in the use of specific programs for probabilistic calculus, simulation and data analysis.
At the end of the course, the student will be able to identify suitable statistical and probabilistic models and methodologies in the context of interest.

1. Knowledge and understanding:
- to know the main descriptive tools for summary and graphical representation of statistical variables
- to know the basic concepts of elementary probability, probability distributions and limit theorems
- to know and understand the main methods of statistical inference

2. Ability to apply knowledge and understanding:
- to use specific theoretical knowledge for calculations with probability distributions
- to use appropriate formulas and terminology in all the processes of application and communication of the acquired knowledge

3. Ability to judge:
- to apply the acquired knowledge in a specific context, identifying the most appropriate probabilistic models and methods

4. Communication skills:
- to present in a clear and exhaustive way the results obtained from solving a statistical or probabilistic problem, using rigorous formulas and appropriate terminology

5. Learning skills:
- to use and merge information from notes, books, slides and practical lab sessions
- to assess the achieved knowledge through quizzes, exercises and assignments during the course

Good mathematical knowledge at the level of High School and Higher Secondary School programs: algebra and elementary geometry, analytical geometry,
algebraic equations and inequalities, basic knowledge of trigonometry and of the trigonometry equations, knowledge of the basic mathematical
functions and their properties (powers, exponential and logarithms).
It is strongly suggested to follow PRECORSO-MATEMATICA GENERALE [CT0110].

Descriptive statistics: Population, samples and variables; indexes of position, spread and correlation; graphical representations of statistical variables.
Probability: combinatorial analysis; sample space, events and probability; conditional probability and independence; discrete and continuous random variables; expectation and moments; joint distributions of random variables, covariance and correlation; central limit theorem and law of large numbers; simulation and Monte Carlo methods; application to reliability of systems.
Inference: parameters, estimators and sample distributions; confidence intervals and tests of significance; application to errors in measurements and quality control; linear regression model.

Main textbook:
S.M. Ross (2015). Probabilità e statistica per l'ingegneria e le scienze. Terza edizione. Apogeo.
S.M. Ross (2014). Introduction to Probability and Statistics for Engineers and Scientists. 5th ed. Academic Press.

Suggested books:
W. Navidi (2019). Statistics for Engineers and Scientists. 5th ed. McGraw-Hill.
R.E. Walpole, R.H. Myers, S.L. Myers, K.E. Ye (2016). Analisi statistica dei dati per l’ingegneria. Pearson.

The achievement of the course objectives is assessed through participation in activities during the course (20%) and a written final exam (80%).
Among the activities proposed during the classes there will be quizzes to assess understanding of basic concepts, exercises to be solved alone or in groups, peer learning and peer assessment activities. Active participation in these activities is evaluated 7 points maximum.
The final exam (26 points) is composed by exercises similar to those solved or assigned in Moodle during the course. During the written exam the use of notes, books and other teaching material is not allowed. A simple calculator can be used. A textbook will be available for consultation. An example of exam will be made available in Moodle.
Students not attending the classes, with a grade in the written exam equal or higher than 22, may ask to improve their final grade with an oral exam. The oral exam is about the whole program of the course and may increase or decrease the grade in the written exam.

The main methodology used in this course is active learning, in which students are asked to participate in different activities by answering questions and solving exercises individually or in groups. Classical lessons only take a small part of the class, leaving to individual home study the knowledge of simple concepts.

Italian

STRUCTURE AND CONTENT OF THE COURSE COULD CHANGE AS A RESULT OF THE COVID-19 EPIDEMIC.

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