This course consists of two sections:
Section 1 demonstrates linear regression to model the linear relationship between a response and predictor(s) when both the response and predictors are continuous variables. We will cover the computation of the regression equation and the analysis of variance table. We will also discuss S, R-Sq, R-Sq (adj), predicted values, confidence intervals, prediction intervals, and how to check for unusual observations and assumptions.
Section 2 introduces Structural Equation Modeling (SEM). We will cover time –related latent variables, the use of modification indices and critical ratio in exploratory analyses, and computation of implied moments, factor score weights, total effects, and indirect effects.