Applied statistical methods and optimisation 798


 
Module code SHC 798
Qualification Postgraduate
Faculty Faculty of Engineering, Built Environment and Information Technology
Module content

A research term paper will be prepared.

The course will apply some of the basics theories and methodologies in statistics and operations research to solve common civil engineering problems. The course seeks to demonstrate the use and application in the civil engineering field. Each of the applications seeks to determine how best to design and operate a system, usually under conditions requiring the allocation of scarce resources.  Emphasis will be on the applications of these methods in common civil engineering practice. Some of the applications will include; optimum network design, maximum flow problem, project scheduling, queuing theory, probabilistic analysis, Markov chain applications, etc.

Module credits 24.00
NQF Level 08
Prerequisites No prerequisites.
Contact time 40 Contact hours
Language of tuition Module is presented in English
Department Civil Engineering
Period of presentation Year

The regulations and rules for the degrees published here are subject to change and may be amended after the publication of this information.

The General Academic Regulations (G Regulations) and General Student Rules apply to all faculties and registered students of the University, as well as all prospective students who have accepted an offer of a place at the University of Pretoria. On registering for a programme, the student bears the responsibility of ensuring that they familiarise themselves with the General Academic Regulations applicable to their registration, as well as the relevant faculty-specific and programme-specific regulations and information as stipulated in the relevant yearbook. Ignorance concerning these regulations will not be accepted as an excuse for any transgression, or basis for an exception to any of the aforementioned regulations.

Copyright © University of Pretoria 2024. All rights reserved.

FAQ's Email Us Virtual Campus Share Cookie Preferences