Description: Simple linear regression, multiple linear regression, model adequacy checking, transformations and weighting to correct model inadequacies, diagnostics for leverage and influence. Polynomial regression models, orthogonal polynomials. dummy variables, variable selection and model building, multicollinearity. Nonlinear regression. Generalized linear models, autocorrelation, measurement errors, calibration problem, bootstrapping.
Resources: OpenCourseware from NPTEL (India), Sheridan College, MIT, UC Berkeley, Stanford & many other of the World's finest University's.
Professors: Default Professor