Biostatistics

Program Overview

The Master of Science in Biostatistics at the University of Illinois Chicago School of Public Health equips students with the statistical tools and expertise to design, analyze, and interpret data in public health research settings. The program emphasizes real-world application through coursework and offers a concentration in Health Data Science for those seeking a deeper understanding of data analysis and utilization. Graduates are prepared for careers in biostatistics, research, or further academic pursuits.

Program Outline

Program: Master of Science in Biostatistics (MS)

Degree Overview:

The Master of Science (MS) in Biostatistics at the University of Illinois Chicago School of Public Health equips students with the statistical tools and expertise needed to design, analyze, and interpret data in various public health research settings. The program emphasizes real-world application through coursework and offers a concentration in Health Data Science for those seeking a deeper understanding of data analysis and utilization.

Objectives:

• Develop a solid foundation in biostatistical theory and methods
• Effectively communicate statistical findings through written and oral reports
• Prepare graduates for careers in biostatistics, research, or further academic pursuits

Description:

This 42-credit program typically takes two years to complete and can be pursued as a full-time or part-time option. The core curriculum covers essential topics like:

• Biostatistical Methods I & II
• Statistical Learning in Health Analytics
• Survival Analysis
• Longitudinal Data Analysis
• Categorical Data Analysis
• Biostatistical Consulting
• Biostatistical Investigations
Students can further tailor their learning through electives in areas such as:
• Design of Clinical Trials
• Sampling Methods
• Machine Learning
• Programming with R and Python

Concentration in Health Data Science:

For individuals focusing on data analysis and its application, the program offers a Health Data Science concentration. This option requires additional coursework in:

• Health Analytics Investigations
• Big Data Analytics in Public Health
• Programming for Public Health Data

Outline:

Program Structure:

• The program comprises 42 credit hours, including core and elective courses.
• Students may choose a traditional thesis option or a non-thesis option with a comprehensive exam.

Course Schedule:

• Courses are offered in the fall, spring, and summer semesters.
• A typical full-time student takes two to three courses per semester.

Modules:

Core Modules:

• Introduction to Biostatistics
• Probability and Statistical Inference
• Biostatistical Methods I & II
• Biostatistical Computing
• Statistical Learning in Health Analytics
• Survival Analysis
• Longitudinal Data Analysis
• Categorical Data Analysis
• Biostatistical Consulting

Elective Modules:

• Design of Clinical Trials
• Sampling Methods
• Machine Learning
• Programming with R and Python
• Health Analytics Investigations (Concentration)
• Big Data Analytics in Public Health (Concentration)

Assessment:

Evaluation Methods:

• Evaluation methods vary across courses and can include a combination of:
• Exams (midterm and final)
• Quizzes
• Assignments (problem sets, projects, case studies)
• Presentations
• Participation

Assessment Criteria:

• Each course syllabus provides specific grading criteria based on the assessment components mentioned above.
• Generally, performance is evaluated based on:
• Understanding and application of statistical concepts
• Critical thinking and problem-solving
• Effective communication of statistical results
• Active participation in class activities

Teaching:

Teaching Methods:

• The program utilizes various teaching methods to cater to diverse learning styles:
• Interactive lectures
• Hands-on computer labs and workshops
• Collaborative group projects
• Case-based learning
• Individualized mentoring

Faculty:

• The program boasts experienced faculty with expertise in diverse areas of biostatistics, public health, and data science.
• Faculty actively engage in research and collaborate with students on research projects.

Unique Approaches:

• The program emphasizes practical application through:
• Real-world case studies and datasets
• Collaboration with faculty on research projects
• Opportunities to participate in internship experiences
• Access to state-of-the-art computing resources
• Focus on developing communication and presentation skills

Careers:

Potential Career Paths:

• Biostatistician
• Research Analyst
• Epidemiologist
• Data Scientist
• Public Health Consultant
• Clinical Research Coordinator
• Biopharmaceutical Statistician

Career Opportunities:

• Graduates are employed in diverse settings:
• Academic institutions
• Government agencies
• Pharmaceutical companies
• Healthcare organizations
• Research institutions
• Public health consulting firms

Career Outcomes:

• The program prepares graduates with the skills and knowledge to succeed in various biostatistics-related careers.
• The program offers several scholarships and financial aid opportunities.
• Students have access to various academic and professional support services.
• The program fosters a collaborative learning environment with opportunities for networking and professional development.
• The curriculum is updated regularly to incorporate advancements in biostatistics and public health research.