Probability and Statistics for Engineering Applications
Term: 2ndSemester – Academic Year 2019-2020
Institution: UNIPV (DICAR) and IUSS
SSD: ICAR/09 Tecnica delle costruzioni – Structural Engineering
Office hours: by appointment
Most problems in the different fields of Civil Engineering cannot be fully and efficiently addressed without knowledge of probability and statistics. In this course we will make an attempt to cover some basic aspects of probability and statistics that relate to practical matters keeping dice tossing and card games to a bare minimum. Less emphasis will be given to derivations and more to concepts and applications. We will start by discussing why probability and statistics are related but are not the same. Concept and definition of random variables and different functions of random variables will be covered in this initial part of the course. Afterwards, focus is given to commonly used probability distribution functions in civil engineering. Discussions on statistics and sampling are presented towards the last part of the course. In this part, goodness of fit tests, regression a analyses, estimation of distribution parameters from statistics, hypothesis testing and their significance will be discussed. Finally basics of Monte Carlo simulation and an introduction to variance reduction techniques will also be covered.Each topic is discussed with reference to different application problems and their solutions in different fields of civil engineering, such as Structural Engineering, Earthquake Engineering, Transportation Engineering, Water Resources and Environmental Engineering, and Geotechnical Engineering. Basic applications of decision analysis will also be introduced.
The course will be organized will be taught in English.
Theoretical lectures will be complemented by tutorials(aiming at the practical application of the concepts and methods developed during the lectures). The topics that will be discussed in the course are reported in the following.
Knowledge of college-level calculus and basic skills in at least one of the following computer SW tools: Excel, Matlab, R. Proficiency in reading, writing and comprehending English language. Examples from different branches of engineering will be used throughout the course, but no prior in-depth knowledge of engineering is necessary.