Statistical Theory (STAT 417)

Time: 9:00-10:15am, TTH
Location: UNIV 203
Instructor: Jiashun Jin
TA: TBA
Office Hours: 2:00-3:00pm, TH

 

STAT 417 is an introduction to the mathematical theory of statistical inference, with an emphasis on standard parametric families of distributions. Major topics that will be covered include: sampling distributions such as Student's t, Chi-square and F distributions; Bayes and maximum likelihood estimators; properties of estimators such as bias/variance, consistency, sufficiency and efficiency; hypothesis testing methods and their properties. Those topics correspond to chapters 7-10 of the required textbook [1].

Prerequsites for this course are multivariate calculus and undergraduate probability (such as STAT 416). The students should feel comfortable with chapters 1-5 of [1].

 

Textbooks: [1] (required) Mathematical Statistics with Applications (6th edition). Dennis Wackerly, William Mendenhall and Richard L. Scheaffer, Duxbury, 2002.
[2] (recommended: covers the same material as [1]) Probability and Statistics (3rd edition). Morris H. Degroot and Mark J. Schervish, Addison Wesley, 2002.
[3] (recommended: covers more topics in statistical inference) All of Statistics: A Concise Course in Statistical Inference, Larry Wasserman, Springer, 2004.
Created: 08/01/2006