Courses Taught by Erin Craig
BIOSTAT501: Introduction to Biostatistics
- Graduate level
- Both Residential and Online MPH
- This is a second year course for Online students
- Fall term(s) for residential students; Fall term(s) for online MPH students;
- 3 credit hour(s) for residential students; 2 credit hour(s) for online MPH students;
- Instructor(s): Matt Zawistowski, Erin Craig, (Residential); Myra Kim (Online MPH);
- Prerequisites: SPH MPH or permission of instructor
- Description: Statistical methods and principles necessary for understanding and interpreting data used in public health and policy evaluation and formation. Topics include descriptive statistics, graphical data summary, sampling, statistical comparison of groups, correlation, and regression. Students will learn via lecture, group discussions, critical reading of published research, and analysis of data.
- This course is required for the school-wide core curriculum
- Syllabus for BIOSTAT501
| Department | Program | Degree | Competency | Specific course(s) that allow assessment | Population and Health Sciences | MPH | Compare population health indicators across subpopulations, time, and data sources | PUBHLTH515, BIOSTAT592, EPID590, EPID592, EPID643, BIOSTAT595, BIOSTAT501 | Population and Health Sciences | MPH | Estimate population health indicators from high quality data resources from diverse sources | PUBHLTH515, EPID643, NUTR590, BIOSTAT592, BIOSTAT501 |
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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): Erin Craig, Michele Peruzzi, (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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BIOSTAT800: Seminar in Biostatistics
- Graduate level
- Residential
- Fall, Winter term(s) for residential students;
- 0.5 credit hour(s) for residential students;
- Instructor(s): Erin Craig, Dylan Cable, (Residential);
- Prerequisites: Graduate level Biostatistics students only
- Description: Presentations and discussions of current consulting and research problems. Enrollment limited to biostatistics majors. Students must attend 2/3 of all seminars offered during the semester to receive credit. Maximum credit is 0.5 per semester. No more than 1 credit total allowed. May only be taken a maximum of 2 semesters.
