Program Overview
The Master of Science in Statistics program at the University of Illinois Chicago provides advanced training in theoretical and applied statistics, preparing graduates for careers in industry, government, or academia. The program offers a core curriculum in statistical theory and methods, along with elective courses for specialization in areas such as biostatistics, data science, or actuarial science. Students can choose to complete a master's thesis, demonstrating their ability to apply statistical methods to real-world problems.
Program Outline
Degree Overview:
Overview:
The MS in Statistics program provides students with advanced training in theoretical and applied statistics. The program is designed to prepare graduates for careers in industry, government, or academia.
Objectives:
- To develop a deep understanding of statistical theory and methods
- To provide students with the skills to apply statistical methods to real-world problems
- To prepare students for further study in statistics or related fields
Description:
The MS in Statistics program typically requires 36 semester hours of coursework. The program includes a core curriculum of required courses, as well as elective courses that allow students to specialize in areas such as biostatistics, data science, or actuarial science.
Outline:
Program Content:
The program covers a wide range of topics in statistics, including:
- Probability theory
- Statistical inference
- Linear models
- Regression analysis
- Multivariate analysis
- Time series analysis
- Nonparametric methods
- Bayesian statistics
Structure:
The program is typically completed in two years of full-time study. The curriculum is divided into three parts:
Core courses:
These courses provide students with a foundation in statistical theory and methods.
Elective courses:
Students choose elective courses to specialize in their area of interest.
Master's Thesis:
Students have the option to complete a master's thesis, which is a significant research project that demonstrates their ability to apply statistical methods to a real-world problem.
Course Schedule:
The course schedule varies depending on the semester. For a complete list of available courses, please refer to the UIC Graduate Catalog.
Individual modules:
- STAT 401: Introduction to Probability
- STAT 411: Statistical Theory
- STAT 416: Nonparametric Statistical Methods
- STAT 431: Introduction to Survey Sampling
- STAT 451: Computational Statistics
- STAT 461: Applied Probability Models I
- STAT 471: Linear and Non-Linear Programming
- STAT 473: Game Theory
- STAT 481: Applied Statistical Methods II
- STAT 485: Intermediate Statistical Techniques for Machine Learning and Big Data
- STAT 486: Statistical Consulting
- STAT 494: Special Topics in Statistics, Probability and Operations Research
- STAT 496: Independent Study
- STAT 501: Probability Theory I
- STAT 502: Probability Theory II
- STAT 511: Advanced Statistical Theory I
- STAT 512: Advanced Statistical Theory II
- STAT 521: Linear Statistical Inference
- STAT 522: Multivariate Statistical Analysis
- STAT 531: Sampling Theory I
- STAT 532: Sampling Theory II
- STAT 535: Optimal Design Theory I
- STAT 536: Optimal Design Theory II
- STAT 585: Advanced Statistical Techniques for Machine Learning and Big Data
- STAT 591: Advanced Topics in Statistics, Probability and Operations Research
- STAT 593: Graduate Student Seminar
- STAT 595: Research Seminar
- STAT 596: Independent Study
- STAT 598: Master's Thesis
- STAT 599: Doctoral Thesis Research
Assessment:
Students are assessed through a variety of methods, including:
- Exams: Midterm and final exams are used to assess students' understanding of the course material.
- Projects: Some courses require students to complete projects, which allow them to apply their skills to a more in-depth problem.
- Master's thesis (optional): The master's thesis is a major research project that demonstrates the student's ability to conduct independent research and apply statistical methods to a real-world problem.
Teaching:
The MS in Statistics program is taught by a team of experienced faculty members who are actively engaged in research. The program uses a variety of teaching methods, including:
- Lectures: Lectures are used to introduce new concepts and theories.
- Discussions: Discussion sections are used to allow students to ask questions and discuss the course material in more detail.
- Computer labs: Computer labs are used to provide students with hands-on experience with statistical software.
- Guest speakers: The program occasionally invites guest speakers to talk about their research or work in the field of statistics.
Careers:
Graduates of the MS in Statistics program have a wide range of career options. Some common career paths for graduates include:
- Statistician: Statisticians work in a variety of industries, including government, academia, and the private sector. They use their skills to collect, analyze, and interpret data.
- Data scientist: Data scientists use their skills in statistics and computer science to analyze large datasets. They work in a variety of industries, including technology, finance, and healthcare.
- Actuary: Actuaries use their skills in mathematics and statistics to assess risk. They work in the insurance industry, as well as other industries that deal with risk, such as finance and healthcare.
- Biostatistician: Biostatistician apply statistical methods to problems in biology and medicine. They work in a variety of settings, including academia, government, and the pharmaceutical industry.
Other:
- The program offers a variety of financial aid options, including scholarships, fellowships, and teaching assistantships.
- The program is accredited by the American Statistical Association (ASA).
-
