Mathematics - Statistics
The Mathematics – Statistics program provides students with a rigorous foundation in mathematical theory, statistical methods, and quantitative analysis. The program emphasizes analytical thinking, problem-solving, and interdisciplinary research, enabling students to model, interpret, and analyze complex data in various scientific, business, and technological contexts. Courses cover probability, statistical inference, linear algebra, calculus, applied mathematics, and computational statistics, while integrating laboratory work, projects, and data-driven research. Students develop practical skills in modeling, simulation, and quantitative reasoning, preparing them to address challenges in data science, research, finance, and technological applications.
Throughout the program, students cultivate strong analytical, computational, and communication skills, essential for careers in data analysis, statistics, finance, research, and technology. Exposure to interdisciplinary approaches, including computer science, economics, engineering, and applied mathematics, ensures graduates are equipped to tackle complex quantitative problems. By fostering independent inquiry, data-driven analysis, and applied research skills, the program prepares students to contribute meaningfully to academic research, data science initiatives, and practical solutions in statistical modeling and quantitative analysis.
Key information
Key Facts
- Program Title: Mathematics - Statistics
- Degree Type: S. Bachelor
- Duration: 4 years
- Mode of Study: Full-time, On Campus
- Application Deadline: 01 January 2026
- Location: Columbia University, United States
- Field of Study: Mathematics
- Language of Instruction: English
Program Structure
Year 1 – Foundations in Mathematics and Statistics
• Calculus I and II
• Linear Algebra
• Introduction to Probability and Statistics
• Academic Writing and Research Methods
Year 2 – Core Studies and Applied Techniques
• Statistical Inference and Regression Analysis
• Multivariable Calculus and Differential Equations
• Applied Probability and Stochastic Processes
• Elective Modules in Data Science, Economics, or Computational Methods
Year 3 – Advanced Analysis and Modeling
• Advanced Statistical Modeling
• Computational Statistics and Programming
• Mathematical Modeling and Optimization
• Seminar: Case Studies in Statistics
Year 4 – Independent Research and Capstone Project
• Independent Research Project
• Advanced Topics in Statistics and Applied Mathematics
• Data Analysis and Interpretation
• Capstone Project and Presentation
Career Opportunities
Graduates of this program are prepared for careers in data science, statistical research, finance, analytics, technology, and academia. They can work in research institutions, financial firms, technology companies, government agencies, and consulting firms that rely on quantitative analysis and modeling. The program equips students with strong analytical, computational, and statistical skills, enabling them to pursue roles in data modeling, statistical consulting, predictive analytics, research, and financial analysis. Alumni may also engage in postgraduate studies, interdisciplinary projects, or leadership positions in data-driven industries, providing versatile and competitive career pathways in both professional and academic contexts.
Why Choose This Program
This program combines mathematical rigor, statistical analysis, and applied research, giving students a comprehensive understanding of quantitative reasoning and data modeling. Small classes and close faculty mentorship provide personalized guidance, fostering analytical thinking, problem-solving skills, and computational proficiency. The curriculum emphasizes practical applications, data-driven decision-making, and interdisciplinary learning, preparing graduates to address complex quantitative challenges in research, industry, and technology. By engaging with modeling, statistical analysis, computational projects, and research initiatives, students gain the knowledge, tools, and experience necessary for impactful careers in statistics, data science, analytics, finance, and further academic study.
Contact Information
For further information, please contact the admissions office at:
Phone: +1 212 854 1754
Email: admissions@columbia.edu
Address: University of Columbia, Admissions Office, New York, NY, United States
