Testing hypotheses, linear regression, generalized linear models, analysis of variance, factorial design, and nested design. SAS and R applications. Course Information: 3 undergraduate hours. 4 graduate hours. Prerequisite(s): Grade of C or better in STAT 381; or consent of the instructor. Students in the BS in Data Science may satisfy the prerequisite with C or better in IE 342 or ECE 341 instead of STAT 381.