Curriculum

Quantitative Program

University of Notre Dame

Course Schedule Spring 2017 – Fall 2018

 

This schedule will be updated if necessary due to Faculty leaves. The goal is to repeat the schedule every two years (i.e., Fall ’18 = Fall ’20, etc.)

(R) = required for quantitative students

(A) = every year

(B) = every other year

NOTES:

1. Statistical Inference I and II are taught at ACMS. Note that Statistical Inference I is called Applied Probability. There is also a summer course offered by ACMS that can serve as an alternative to Applied Probability to fulfill the Statistical Inference I requirement. Statistical Inference II is called Statistical Inference.
 

1. Spring 2017

Quantitative Methods II (R)(A)

Scott Maxwell

60101

 Advanced SEM (B)

 Ke-Hai Yuan

tba

Applied Longitudinal Analysis (R)(A)

Peggy Wang

60155

Generalized Linear Model (R)(B)

Gitta Lubke

60135

Mixture Modeling (B)

Gitta Lubke

60151


 2. Fall 2017

Quantitative Methods (R)(A)

 Scott Maxwell

60100

Multivariate Statistics (R)(A)

Guangjian Zhang

60125

 Structural Equation Models (R)(A)

Johnny Zhang

 60130

Computational Statistics (R)(B)

Ke-Hai Yuan

60142

Item Response Theory (R)(B)

Alison Cheng

60152


3. Spring 2018

Quantitative Methods II (R)(A)

Ross Jacobucci

60101

Exploratory Data Analysis (B)

Johnny Zhang

60105

Applied Longitudinal Analysis (R)(A)

Peggy Wang

60155

Linear Model (R)(B)

Gitta Lubke

60123

Introduction to Statistical Learning (B)

Gitta Lubke

60122

Matrix Algebra (R)(B)

Guangjian Zhang

tba

 Missing Data (B)

 Ke-Hai Yuan

 60139

 Psychological Measurement (R)(B)

 Alison Cheng

 60121


4. Fall 2018

Quantitative Methods I (R)(A)

tbd

60100

Multivariate Statistics (R)(A)

Guangjian Zhang

60125

Statistical Methods (B)

Ke-Hai Yuan

60158

 Applied Bayesian Analysis (R)(B)

Johnny Zhang

  60130

 Computer Age Statistical Inference

Gitta Lubke

tba