Preliminaries on probability theory; exact and asymptotic sampling distributions; unbiasedness, consistency, efficiency, sufficiency and completeness; properties of maximum likelihood estimators; least squares estimation of location and scale parameters based on order statistics and sample quantiles; Best Asymptotically Normal (BAN) estimators. Prerequisite(s): STAT 3559 or permission of the School. Also offered at the graduate level, with different requirements, as STAT 5600, for which additional credit is precluded. Lectures three hours a week.
Preliminaries on probability theory; exact and asymptotic sampling distributions; unbiasedness, consistency, efficiency, sufficiency and completeness; properties of maximum likelihood estimators; least squares estimation of location and scale parameters based on order statistics and sample quantiles; Best Asymptotically Normal (BAN) estimators. Prerequisite(s): STAT 3559 or permission of the School. Also offered at the graduate level, with different requirements, as STAT 5600, for which additional credit is precluded. Lectures three hours a week.
