EE5373
EE 5373 - Data Modeling Using R (1 Cr.)
Electrical and Computer Engineering (11122)
TIOT - College of Science and Engineering
EE 5373 - Data Modeling Using R (1 Cr.)
Course description
Introduction to data modeling and the R language programming. Multi-factor linear regression modeling.
Residual analysis and model quality evaluation. Response prediction. Training and testing. Integral lab.
An introductory course in probability and statistics is suggested but not required; basic programming skills in some high-level programming language, such as C/C++, Java, Fortran, etc also suggested.
Residual analysis and model quality evaluation. Response prediction. Training and testing. Integral lab.
An introductory course in probability and statistics is suggested but not required; basic programming skills in some high-level programming language, such as C/C++, Java, Fortran, etc also suggested.
Minimum credits
1
Maximum credits
1
Is this course repeatable?
No
Grading basis
A-F - A-F Grade Basis
Laboratory
Requirements
000356
Fulfills the writing intensive requirement?
No
Typically offered term(s)
Periodic Fall & Spring