Matrix-based, applied linear regression procedures at a mathematical level appropriate for a first-year graduate statistics major. Topics include basic methodological development for simple and multiple linear regression, model building and diagnostics, analysis of variance/covariance and multiple comparison methods. Other topics from ANOVA modeling may also be covered if time permits.
Note: A student may not receive graduate credit for both STAT 705 and STAT 713.
Repeat for Credit N
Requisites: Prerequisite: Math 515/551 or an equivalent course and one prior course in statistics.
