Statistics and Data Science (MS)

Program Overview

The Master of Science in Statistics and Data Science from the University of Central Florida provides a solid theoretical foundation and practical skills in statistical methods, numerical analysis, and data science. Required courses cover experimental design, statistical computing, regression analysis, and statistical applications of matrix algebra. Electives allow students to specialize in areas such as linear models, multivariate statistical methods, data mining, and big data analytics. Students choose a thesis or nonthesis option for the program's final component.

Program Outline

Degree Overview:

The Master of Science in Statistics and Data Science provides a strong foundation in statistical theory, methods, numerical methods, and the application of computer methodology to statistical analyses. The program is designed for individuals with undergraduate degrees in mathematics, statistics, or computer science, but is also open to those from other disciplines who want to develop expertise in statistics and data science.

Outline:

The program requires a minimum of 36 credit hours beyond the bachelor's degree. It consists of:

• Required Courses (21 credit hours):
• STA5205 - Experimental Design (3)
• STA6106 - Statistical Computing I (3)
• STA6236 - Regression Analysis (3)
• STA6326 - Theoretical Statistics I (3)
• STA6327 - Theoretical Statistics II (3)
• STA6329 - Statistical Applications of Matrix Algebra (3)
• At least 1 of the following:
• STA6246 - Linear Models (3)
• STA6707 - Multivariate Statistical Methods (3)
• Elective Courses (9 credit hours):
• Students must earn at least 9 credits from a list of courses including:
• STA5505 - Categorical Data Methods (3)
• STA5825 - Stochastic Processes and Applied Probability Theory (3)
• STA6107 - Statistical Computing II (3)
• STA6226 - Sampling Theory and Applications (3)
• STA6224 - Bayesian Survey Methods (3)
• STA6237 - Nonlinear Regression (3)
• STA6346 - Advanced Statistical Inference I (3)
• STA6347 - Advanced Statistical Inference II (3)
• STA6507 - Nonparametric Statistics (3)
• STA6662 - Statistical Methods for Industrial Practice (3)
• STA6709 - Spatial Statistics (3)
• STA6857 - Applied Time Series Analysis (3)
• STA5104 - Advanced Computer Processing of Statistical Data (3)
• STA6704 - Data Mining Methodology II (3)
• STA6705 - Data Mining Methodology III (3)
• STA6714 - Data Preparation (3)
• COP5711 - Parallel and Distributed Database Systems (3)
• COP6730 - Transaction Processing (3)
• COP6731 - Advanced Database Systems (3)
• STA6238 - Logistic Regression (3)
• STA7722 - Statistical Learning Theory (3)
• STA7734 - Statistical Asymptotic Theory in Big Data (3)
• STA5738 - Data and Analytical Methodology for Metropolitan and Regional Areas (3)
• STA6223 - Conventional Survey Methods (3)
• STA7239 - Dimension Reduction in Regression (3)
• STA7348 - Bayesian Modeling and Computation (3)
• STA7719 - Survival Analysis (3)
• STA7935 - Current Topics in Big Data Analytics (3)
• CNT5805 - Network Science (3)
• STA5176 - Introduction to Biostatistics
• Thesis/Nonthesis Option (6 credit hours):
• Thesis Option:
• Students must complete a thesis (6 credit hours) and an oral defense.
• Nonthesis Option:
• Students must complete 3 credit hours of electives and 3 credit hours of independent study for a research project.
They must also complete a research project report and an oral presentation.

Other:

• Students must have completed specific prerequisite courses before applying to the program.
• Students must maintain a minimum GPA of 3.0 in their Plan of Study (POS) and a "B" (3.0) in all courses completed toward the degree and since admission to the program.
• The program has one track: Data Science Track.
• Students can receive financial assistance through fellowships, assistantships, tuition support, or loans.
• The program is offered at the University of Central Florida.