MATH 439 - Intermediate Data Analysis (3)

Simple and multiple linear regression, testing hypotheses, dummy variables, ANOVA, ANCOVA, confounding and interaction, diagnostics, influence and outliers, transformation and weighting and model selection. Introductory nonlinear and logistic regression. SAS statistical software will be used.

Prerequisite: MATH 250B or MATH 270B with a C (2.0) or better; MATH 338 with a C (2.0) or better; or graduate standing.

400-level Undergraduate Course available for Graduate Credit