Numerical and statistical methods for Civil Engineering aims at providing students with fundamental knowledge on numerical and statistical methods for civil engineering problems, and at developing the competences required for designing and coding simple numerical and statistical models, also to learn how apply high level softwares for engineering analysis. The course aims at providing in depth knowledge of 1) a technical/scientific programming language; 2) main numerical methods for the solution of ordinary and partial differential equations; 3) descriptive and inferential statistics. Students shall be able of: 1) using a technical/scientific programming language to develop numerical models and to carry out statistical analyses; 2) designing, developing, validating and applying algorithms for the integration of ordinary and partial differential equations of interest for the civil engineering field; 3) carrying out statistical analysis on large datasets; 4) designing and carrying out statistical analyses; 5) finding and understanding scientific publications for specific problems of interest, also using scientific search engines/databases (Scopus, Web Of Science)
teacher profile | teaching materials


1-Introduction to programming in Matlab
2-Ordinary differential equations
3-Partial differential equations
4-CFD for maritime hydraulics

Core Documentation

-Lecture notes
-Chapra S., 2018. Applied Numerical Methods with MATLAB for Engineers and Scientists, 4th Edition, McGrawHill Education.
-Chapra S., Canale R., 2015. Numerical Methods for Engineers 7th Edition, McGrawHill Education.

Type of evaluation

During the exam the students develop 9 exercise, automatically checked by a software.