Courses Taught by Walter Dempsey

BIOSTAT617: Theory and Methods of Sample Design (Soc 717 and Stat 580 and SurvMeth 617)

  • Graduate level
  • Residential
  • Winter term(s) for residential students;
  • 3 credit hour(s) for residential students;
  • Instructor(s): Walter Dempsey (Residential);
  • Prerequisites: Three or more courses in statistics, and preferably a course in methods of survey sampling
  • Description: Theory underlying sample designs and estimation procedures commonly used in survey practice.
  • This course is cross-listed with Stats 580 Soc 717 SurvMeth617 in the Rackham department.
DempseyWalter
Walter Dempsey

BIOSTAT629: Case Studies in Health Big Data

  • Graduate level
  • Residential
  • Winter term(s) for residential students;
  • 1-2 credit hour(s) for residential students;
  • Instructor(s): Nicholas Henderson, Walter Dempsey, (Residential);
  • Prerequisites: BIOSTAT 601, BIOSTAT 602, BIOSTAT 650, BIOSTAT 651, BIOSTAT 625, BIOSTAT620
  • Description: Being a project-based course, it integrates all competencies learned in HDSC to provide a culminating research experience. Students will work on two to three health big data projects, through which they learn to identify scientific objectives and analytical strategies and report findings through oral presentation and written documents.
  • Learning Objectives: Students will learn how to identify a scientific goal of the project and to develop analytic strategies. Students will learn to integrate and apply quantitative skills to handle real-world health big data, including data modification and cleaning, data visualization and scalable computing. From presentations, students will improve their communication skills.
HendersonNicholas
Nicholas Henderson
DempseyWalter
Walter Dempsey
Concentration Competencies that BIOSTAT629 Allows Assessment On
Department Program Degree Competency Specific course(s) that allow assessment
BIOSTAT Health Data Science MS Apply quantitative techniques commonly used to summarize and display big public health data BIOSTAT629
BIOSTAT Health Data Science MS Apply descriptive and inferential methodologies according to the type of study design or sampling technique for answering a particular public health question BIOSTAT629

BIOSTAT802: Advanced Inference II

  • Graduate level
  • Residential
  • Winter term(s) for residential students;
  • 3 credit hour(s) for residential students;
  • Instructor(s): Walter Dempsey (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.
DempseyWalter
Walter Dempsey
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