PHYS 5002 [0.5 credit] (PHY 5344) Computational Physics
Computational methods used in analysis of experimental data. Introduction to probability and random variables. Monte Carlo methods for simulation of random processes. Statistical methods for parameter estimation and hypothesis tests. Confidence intervals. Multivariate data classification. Unfolding methods. Examples taken primarily from particle and medical physics.
Includes: Experiential Learning Activity
Prerequisite(s): an ability to program in FORTRAN, Java, C, or C++ or permission of the Department.
Also offered at the undergraduate level, with different requirements, as PHYS 4807, for which additional credit is precluded.
Prerequisite(s): an ability to program in FORTRAN, Java, C, or C++ or permission of the Department.
Also offered at the undergraduate level, with different requirements, as PHYS 4807, for which additional credit is precluded.
Physics
http://calendar.carleton.ca/grad/gradprograms/physics/
...accelerated pathway: students must complete PHYS 5002 Computational Physics and PHYS 5602 Physics of Elementary...
Biomedical Engineering
http://calendar.carleton.ca/grad/gradprograms/biomedicalengineering/
...5308 , COMP 5401 , COMP 5703 , COMP 5704 , PHYS 5002 , SYSC 5001 , SYSC 5003 , SYSC 5004...
Data Science (Collaborative Program)
http://calendar.carleton.ca/grad/gradprograms/datascience/
...5308 , COMP 5401 , COMP 5703 , COMP 5704 , PHYS 5002 , SYSC 5001 , SYSC 5003 , SYSC 5004...