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.