# Università degli Studi di Napoli "Parthenope"  ## Teaching schedule

2017/2018
Belonging course:
Course of Bachelor's Degree Programme on CIVIL AND ENVIRONMENTAL ENGINEERING
Disciplinary sector:
TOPOGRAPHY AND CARTOGRAPHY (ICAR/06)
Credits:
6
Year of study:
2
Teachers:
Cycle:
First Semester
Hours of front activity:
48

Italian

### Course description

Educational Goals
The course aims to provide students with the indispensable knowledge and the means to understand, at a basic level, the notions of probability and statistics and how these can be applied to the study of various random phenomena in the engineering field. The course illustrates the fundamental concepts of statistics and probability calculations, as a basic tool for data analysis and the study of random phenomena. In particular, descriptive statistics techniques and the basic elements of probability calculus will be presented, focusing on methods useful for solving some engineering problems. The basic concepts of inferential statistics and an introduction to statistical modeling will also be given. The laboratory activity will concern the parts of the program for which the computer aid (matlab statistical tool box) is indispensable.
Learning outcomes (compared to the Dublin descriptors)

Knowledge and understanding
At the end of the course the student will have learned the fundamental concepts of statistics and probability calculations, as a basic tool for data analysis and the study of random phenomena that fall within the civil engineering field. In particular, he will possess the knowledge of basic statistical techniques, basic probabilistic techniques and the basic elements necessary for statistical modeling. The presentation of knowledge in an organic form allows not only memorization, but also understanding.

Applied knowledge and understanding
At the end of the study path the student will have developed the ability to describe and model in statistical form some of the phenomena typical of civil engineering.

Autonomy of judgment
Upon passing the exam, the student will have the necessary tools to critically evaluate, set and correctly solve a probabilistic and statistical problem.
Communication skills
Upon passing the exam, the student must have acquired sufficient language properties with regard to the specific scientific terminology of the statistics. In particular, he will be able to present probabilistic-statistical arguments in a clear, simple and punctual manner.
Ability to learn
The student will be able to deepen independently the knowledge of the random phenomena, and to learn the use of dedicated statistical software beyond those presented during the course. This will allow us to face the non-deterministic phenomena that are presented in the subsequent characteristic courses.

### Prerequisites

You need to have acquired and assimilated the following knowledge from the course "Analysis I":
Polynomial, goniometric, exponential and inverse functions, differential and integral calculus. Some conceptions of multiple variables differential and integral calculus are required. These notions are given during the course.

### Syllabus

Descriptive statistics: introduction to the course; summary measures; graphic representations; association and correlation measures (4 lesson hours, 2 hours practice)
Introduction to probability: basic concepts; conditional probability and independence; application to system reliability (4 hours lesson, 1 hour tutorial)
Random variables: random variables; functions of random variables; multivariate random variables (4 hours lesson, 2 hours tutorial)
Typical probability distributions: Bernoulli; binomial and related distributions; Poisson; normal and lognormale; exponential; gamma and Weibull (8 hours lesson, 2 hours tutorial)
Sequences of random variables and limit theorems: law of large numbers; central limit theorem (4 hours lesson, 1 hour tutorial)
Point estimate: estimators; estimate of the parameters of the most common distributions (4 lesson hours)
Interval estimation: interval estimation; confidence intervals for the mean and the difference between averages (4 lesson hours, 2 hours exercises)
Hypothesis testing: statistical tests; level of significance; test for the average and the difference between averages; other remarkable tests (6 lesson hours)

Descriptive statistics: introduction to the course; summary measures; graphic representations; association and correlation measures (4 lesson hours, 2 hours practice)
Introduction to probability: basic concepts; conditional probability and independence; application to system reliability (4 hours lesson, 1 hour tutorial)
Random variables: random variables; functions of random variables; multivariate random variables (4 hours lesson, 2 hours tutorial)
Typical probability distributions: Bernoulli; binomial and related distributions; Poisson; normal and lognormale; exponential; gamma and Weibull (8 hours lesson, 2 hours tutorial)
Sequences of random variables and limit theorems: law of large numbers; central limit theorem (4 hours lesson, 1 hour tutorial)
Point estimate: estimators; estimate of the parameters of the most common distributions (4 lesson hours)
Interval estimation: interval estimation; confidence intervals for the mean and the difference between averages (4 lesson hours, 2 hours exercises)
Hypothesis testing: statistical tests; level of significance; test for the average and the difference between averages; other remarkable tests (6 lesson hours)

### Teaching Methods

Lectures in the classroom, exercises on the subjects carried out using the Matlab statistical tool box.

### Textbooks

- W. Navidi: Probabilità e statistica per l'ingegneria e le scienze; McGraw-Hill (Milano) 2006
(Reference text)
Notes provided by the teacher available on the department site

### Learning assessment

The objective of the exam is to check the level of achievement of the objectives previously indicated. The examination is carried out through an oral test in which the ability to link and compare different aspects of the course will be evaluated. In particular, it will be required for the student to demonstrate that he has acquired a critical sense to properly set up and solve a statistical problem, to model a random engineering phenomenon. The test will take place individually and will last for 20 to 40 minutes depending on the case.