Courses Taught by Gen Li
BIOSTAT601: Probability and Distribution Theory
- Graduate level
- Residential
- Fall term(s) for residential students;
- 4 credit hour(s) for residential students;
- Instructor(s): Gen Li, Thomas Braun, (Residential);
- Prerequisites: Three terms of calculus
- Description: Fundamental probability and distribution theory needed for statistical inference. Probability, discrete and continuous distributions, expectation, generating functions, limit theorems, transformations, sampling theory.
- Syllabus for BIOSTAT601
| Department | Program | Degree | Competency | Specific course(s) that allow assessment | BIOSTAT | MS | Apply the theoretical foundations of probability theory and distribution theory | BIOSTAT601 |
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BIOSTAT629: Case Studies In Health Big Data
- Graduate level
- Residential
- Winter term(s) for residential students;
- 3 credit hour(s) for residential students;
- Instructor(s): Gen Li, Nicholas Henderson, (Residential);
- Prerequisites: Biostatistics or Health Data Science students only
- Description: Being a project-based course, it integrates all competencies learned in HDS MS program 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.
- Syllabus for BIOSTAT629
| 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 |
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