Program Introduction
The Master of Science in Statistical Practice (MSSP) program at Boston University is an intensive, practice-oriented program designed for students seeking professional careers in data analysis, statistical modeling, and predictive analytics. The program teaches modern statistical methodologies, programming skills, data visualization, and machine learning, focusing on developing students' ability to solve complex real-world data problems. MSSP is a STEM (Science, Technology, Engineering, and Mathematics) designated program, making international students eligible to work in the United States through Optional Practical Training (OPT) for up to three years after graduation. The program balances statistical theory with practical application, ensuring students acquire practical skills immediately applicable in industry settings. Through hands-on training and capstone projects, students gain experience working with real datasets and learn to effectively communicate statistical analysis results. The program can be completed in either two semesters (including a summer session) or three semesters, preparing students as statistical experts needed across various industries (healthcare, finance, technology, marketing, etc.). Boston University's strong industry connections and the rich employment opportunities in the Boston area help graduates launch successful careers in data science, biostatistics, financial analysis, and other fields.
- Language of InstructionEnglish
- Program Length12 months
- Teaching MethodsOffline
- Core Statistical Foundations: Mathematical Statistics, Regression Analysis, Statistical Inference, Experimental Design, Multivariate Analysis, Time Series Analysis, Bayesian Statistics - Programming and Computing Skills: R, Python, SQL, SAS, Data Management, Database Systems, Big Data Processing - Data Visualization: Visual Data Exploration, Creating Interactive Dashboards, Effective Graphic Design, Visualization Tools (Tableau, ggplot2) - Machine Learning and Predictive Modeling: Supervised Learning, Unsupervised Learning, Classification Algorithms, Clustering, Dimensionality Reduction, Model Selection and Evaluation - Applied Analytical Methodologies: Biostatistics, Financial Analytics, Marketing Analytics, Text Mining, Social Network Analysis, Healthcare Data Analysis - Professional Skills Development: Presentation Skills, Technical Report Writing, Data Storytelling, Effective Communication, Collaboration - Capstone Project: Comprehensive statistical project conducted in collaboration with real clients or industry partners - Practical Statistical Tools: Statistical Software Utilization, Automation Tools, Version Control, Documentation, Reproducible Research Methodologies - Ethics and Professionalism: Data Ethics, Privacy Considerations, Bias and Fairness, Ethical Aspects of Statistical Research - Elective Specialization Courses: Specialized courses based on individual interests, interdisciplinary courses with other departments, industry-specific tracks
Data Scientist
$75,000 ~ $110,000
Data Analyst
$65,000 ~ $95,000
Statistical Consultant)
$90,000 ~ $120,000
| Intakes | Application Deadlines |
|---|---|
| 2025 Fall | 2025-01-15 |
Admission Requirement
- GPANo Min Score
- GRE/GMATNo Min Score
100
7.0
- Online ApplicationRequired
- Undergraduate TranscriptRequired
- Resume or CVRequired
- Letters of RecommendationRequired
- Statement of PurposeRequired
- Video Interview Required
- Certified English Test Score ReportRequired
- GRE / GMATOptional
Fees and Funding
$66,670/Year
$15,450/Year
$125