Stat 550 Course Calendar
Homework assignments, lecture notes and handouts will be posted in D2L. Readings will be denoted by "550" for the Course Notes: Statistics 550 Advanced Mathematical Statistics and by "505" for A Pair of Primers: Primer on Matrix Analysis and Primer on Linear Statistical Models.
Date

Day

Topics

Reading/Assignment


Jan 19

Thur

Casella and Berger review; Course introduction; Kronecker products and the vec operator 
Syllabus; 550 Ch. 2; 505 Secs. 7.1, 7.2.17.2.3, 8.18.4

Jan 24

Tue

Review Kronecker product and vec operator proof exercises 

Jan 26

Thur

Matrix differentiation 
550 Chapter 3; 505 Chapter 13 
Jan 31

Tue

Matrix differentiation (cont); eigenvalue/eigenvector review 
505 Ch. 9 
Feb 2

Thur

Types of proofs; order of magnitude 
505 Sec. 2.22.3; 550 Sec. 5.15.2 Homework 1 Due 
Feb 7

Tue

Review of types of convergence in probability; order of magnitude in probability 

Feb 9

Thur

Order of magnitude in probability(cont) 

Feb 14

Tue

Multivariate Taylor series; NewtonRaphson and Fisher Scoring algorithms 
550 Sec. 4.1; 550 Sec. 7.17.4; Casella and Berger Sec. 5.5

Feb 16

Thur

NewtonRaphson and Fisher Scoring algorithms for logistic regression 
Homework 2 Due

Feb 21

Tue

Finish coding NewtonRaphson algorithm for logistic regression; Missing data and the EM algorithm 
550 Sec. 7.6

Feb 23

Thur

Missing data and the EM algorithm 

Feb 28

Tue

EM algorithm (cont) 
Journal Project: Article Proposal Due 
Mar 2

Thur

Coding the EM algorithm

Homework 3 Due 
Mar 7

Tue

Sufficiency Quiz 2: Order of magnitude and order of magnitude in probability (550 Ch 5) 
550 Sec. 9.1

Mar 9

Thur

Sufficiency (cont)

Journal Project: Executive Summary Due

Mar 1317


Spring Break


Mar 21

Tue

Sufficiency (cont)


Mar 23

Thur

Exponential families and invariance Quiz 3: Taylor series expansions, NewtonRaphson and Fisher Scoring algorithms (550 Ch 4, Sec 7.37.4) 
550 Sec. 9.29.3 Journal Project: Proof Sketch Due 
Mar 2731


Journal article presentations via D2L No class meetings 
Fri: Homework 4 Due

Apr 4

Tue

Equivariance and maximal invariants 
550 Sec. 9.3

Apr 6

Thur

Conditionality principle and ancillary statistics Quiz 4: Missing data, EM algorithm, sufficiency (550 Sec 7.6, 9.1)

550 Sec. 9.4

Apr 11

Tue

Completeness 
550 Sec. 9.6

Apr 13

Thur

Likelihoodbased inference 
550 Ch. 10 Optional reading: Ly et al. (2017) Homework 5 Due 
Apr 18

Tue

Likelihoodbased inference (cont) Quiz 5: Exponential families, invariance, equivariance, maximal invariants, conditionality principle, ancillary statistics, completeness 

Apr 20

Thur

Likelihoodbased inference (cont) 

Apr 25

Tue

Likelihoodbased inference (cont) 

Apr 27

Thur

Information criteria

550 Sec. 10.4 Homework 6 Due 
May 2

Tue

Information criteria (cont) The likelihood principle and pvalues Quiz 6: Score function, information, and likelihoodbased inference 

May 4

Thur

Generalized estimating equations

550 Ch. 13

Finals Week 
Tue

Final Exam: Tuesday, May 2, 10:0011:50am

