PHYS 5002 [0.5 credit] (PHY 5344) Statistical Data Analysis Techniques for 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 Python, Java, C, or C++, and 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 Python, Java, C, or C++, and permission of the Department.
Also offered at the undergraduate level, with different requirements, as PHYS 4807, for which additional credit is precluded.
Physics
Graduate Calendar
http://calendar.carleton.ca/grad/gradprograms/physics/
Of the 2.5 credits of course work, no more than 1.5 credits may be fulfilled by Selected Topics such as PHYS 5900 [1.0] , PHYS 5901 [0.5] . In special cases, the requirements may also be met by taking 5.0 credits of course work. 1.0 credit must be the Selected Topics course PHYS 5900
Biomedical Engineering
Graduate Calendar
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 Specialization)
Graduate Calendar
http://calendar.carleton.ca/grad/gradprograms/datascience/
...5308 , COMP 5401 , COMP 5703 , COMP 5704 , PHYS 5002 , SYSC 5001 , SYSC 5003 , SYSC 5004...