Courses Taught by Peisong Han

BIOSTAT602: Biostatistical Inference

  • Graduate level
  • Residential
  • Winter term(s) for residential students;
  • 4 credit hour(s) for residential students;
  • Instructor(s): Han, Peisong Zhang, Min (Residential);
  • Prerequisites: Biostat 601
  • Description: Fundamental theory that is the basis of inferential statistical procedures. Point and interval estimation, sufficient statistics, hypothesis testing, maximum likelihood estimates, confidence intervals, criteria for estimators, methods of constructing test and estimation procedures.
  • Syllabus for BIOSTAT602
Concentration Competencies that BIOSTAT602 Allows Assessment On
Department Program Degree Competency Specific course(s) that allow assessment
BIOSTAT MPH Derive the theoretical mathematics of statistical inferences BIOSTAT602
BIOSTAT MS Derive the theoretical mathematics of statistical inferences BIOSTAT602

BIOSTAT802: Advanced Inference II

  • Graduate level
  • Residential
  • Winter term(s) for residential students;
  • 3 credit hour(s) for residential students;
  • Instructor(s): Han, Peisong (Residential);
  • Prerequisites: Biostat 601, Biostat 602, and MATH 451 or equivalent
  • Description: This sequence covers advanced topics in probability theory, theory of point estimation, theory of hypothesis testing, and related large sample theory. This sequence replaces STAT 610/611 as biostatistics Ph.D. requirements.
Concentration Competencies that BIOSTAT802 Allows Assessment On
Department Program Degree Competency Specific course(s) that allow assessment
BIOSTAT PhD Derive the advanced theoretical mathematics of statistical inferences BIOSTAT802

BIOSTAT870: Analysis of Repeated Measurements

  • Graduate level
  • Residential
  • Winter term(s) for residential students;
  • 3 credit hour(s) for residential students;
  • Instructor(s): Han, Peisong (Residential);
  • Not offered 2022-2023
  • Prerequisites: Math 417, Biostat 602, Biostat 651 and one of Biostat 690, Biostat 851, or Biostat 890
  • Description: Mixed model analysis of variance; multivariate profile analysis; linear mixed effects models with unbalanced designs, time-varying covariates, and structured covariance matrices; maximum likelihood (ML), restricted maximum likelihood (REML), and Bayes estimation and inference; nonlinear mixed effects models.
  • Syllabus for BIOSTAT870

BIOSTAT885: Nonparametric Statistics

  • Graduate level
  • Residential
  • Winter term(s) for residential students;
  • 3 credit hour(s) for residential students;
  • Instructor(s): Han, Peisong (Residential);
  • Not offered 2022-2023
  • Prerequisites: Biostat 601/602 or Perm. Instr.
  • Description: Theory and techniques of nonparametrics and robustness. M-estimation, influence function, bootstrap, jackknife, generalized additive models, smoothing techniques, penalty functions, projection pursuit, CART.
  • Syllabus for BIOSTAT885