Statistical linear models for application in science, business and social science. Topics include simple and multiple regression; linear models with categorical explanatory variables; model diagnostics; inference for linear models; polynomial regression; models for time dependence; methods for variable selection; and weighted regression.
Note(s): Students who have not yet passed one of 161.122 or 161.220 or 233.214 may enrol in 161.220 in the same semester as 161.221, provided that they meet the prerequisites for 161.220. Access to a Windows PC and an approved statistics package are required for analysis of data.
