The Master of Science in Statistics and Data Science, Data Science track focuses on data analytics and its application to business, social, and health problems.

The program is particularly suited for individuals who have completed an undergraduate program in mathematics, statistics, economics, business, or other related fields, and wish to pursue a career in data science. Data scientists analyze massive data sets to uncover trends and associations, and make theoretically sound decisions on, for example, business, social, and health subjects. Data scientists have one of the most coveted jobs, as the demand for them far exceeds the existing number of qualified persons in the area. Currently, the work force in the data science industry consists mainly of individuals trained with post college education. To date, very few university degree programs exist for training students for such a large and growing industry in the United States.

The Data Science track in the Statistics and Data Science MS program is composed of 24 credit hours of required courses and 6 credit hours of restricted electives. Students must also pass an oral defense of thesis or complete a research project and an additional elective.

**Total Credit Hours Required: 36 Credit Hours Minimum beyond the Bachelor's Degree**

## Track Prerequisites

Students must have the following background and courses completed before applying to the Statistics & Data Science, Data Science track MS program. These courses are: MAC 2311C: Calculus with Analytic Geometry I, MAC 2312: Calculus with Analytic Geometry II, MAC 2313: Calculus with Analytic Geometry III, MAS 3105: Matrix and Linear Algebra or MAS 3106: Linear Algebra. These pre-required courses are basic undergraduate courses from the Math department.

## Degree Requirements

### Required Courses

24 Total Credits

- Complete all of the following
- Complete the following:
- STA5104 - Advanced Computer Processing of Statistical Data (3)
- STA6714 - Data Preparation (3)
- STA6238 - Logistic Regression (3)
- STA6326 - Theoretical Statistics I (3)
- STA6327 - Theoretical Statistics II (3)
- STA6236 - Regression Analysis (3)
- STA5703 - Data Mining Methodology I (3)
- STA6704 - Data Mining Methodology II (3)

- Note: STA 5703 and STA 6704 both require research projects that fulfill the independent learning requirement for the program.

### Elective Courses

6 Total Credits

- Complete all of the following
- Select electives from the following courses. No more than one Computer Science (COP prefix) course can be selected. Other courses may be included in a Plan of Study with departmental approval. Other electives can be used at the discretion of the student advisor and/or Graduate Coordinator.
- Complete at least 2 of the following:
- COP5711 - Parallel and Distributed Database Systems (3)
- COP6730 - Transaction Processing (3)
- COP6731 - Advanced Database Systems (3)
- STA5205 - Experimental Design (3)
- STA5505 - Categorical Data Methods (3)
- STA5825 - Stochastic Processes and Applied Probability Theory (3)
- STA6106 - Statistical Computing I (3)
- STA6226 - Sampling Theory and Applications (3)
- STA6237 - Nonlinear Regression (3)
- STA6507 - Nonparametric Statistics (3)
- STA6707 - Multivariate Statistical Methods (3)
- STA6857 - Applied Time Series Analysis (3)
- STA6705 - Data Mining Methodology III (3)
- FIN6406 - Strategic Financial Management (3)
- STA6107 - Statistical Computing II (3)
- STA6329 - Statistical Applications of Matrix Algebra (3)
- STA6246 - Linear Models (3)
- STA6346 - Advanced Statistical Inference I (3)
- STA6347 - Advanced Statistical Inference II (3)
- STA6662 - Statistical Methods for Industrial Practice (3)
- STA6709 - Spatial Statistics (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)
- STA6224 - Bayesian 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 Total Credits

- Complete 1 of the following
Thesis Option- Complete all of the following
- For this option, the MS degree requires a total of at least 36 credit hours comprised of at least 30 credit hours of course work and 6 credit hours of thesis. This includes the 24 credit hours of the core courses, 6 credit hours of `Electiveâ€™ courses, and 3-6 credit hours of a two-course sequence. No more than 6 credit hours of independent study or directed research may be credited toward the degree. It is strongly recommended that the student select a thesis adviser and establish a program of study by the completion of the core courses. With the help of a thesis adviser, the student will form a thesis committee of three members, of which at least two must be from the Department of Statistics and Data Science. An oral defense of the thesis is required.
- Earn at least 6 credits from the following:
- STA6971 - Thesis (1 - 99)

Nonthesis Option- Complete all of the following
- Nonthesis students will take an additional 3 credit hours of electives and 3 credit hours of independent study for a research project. The electives should be chosen in consultation with the graduate program director. This will consist of 24 credit hours of the core courses, and 9 credit hours of elective courses, and 3 credit hours of independent study for a research project. It is strongly recommended that the student contacts the academic adviser, Graduate Coordinator, and establish a program of study by the completion of the core courses. In addition, students in the nonthesis option are required to complete the research project based on the core courses. The student will choose a research advisor and write a research project report under that person's advice. An oral presentation of their research project is required.
- Earn at least 3 credits from the following types of courses: Courses listed in "Elective courses" above.
- Earn at least 3 credits from the following:
- STA6908 - Directed Independent Studies (1 - 99)

#### Grand Total Credits: **36**

## Application Requirements

## Financial Information

Graduate students may receive financial assistance through fellowships, assistantships, tuition support, or loans. For more information, see the College of Graduate Studies Funding website, which describes the types of financial assistance available at ¼¤Çé¿ì²¥ and provides general guidance in planning your graduate finances. The Financial Information section of the Graduate Catalog is another key resource.

## Fellowship Information

Fellowships are awarded based on academic merit to highly qualified students. They are paid to students through the Office of Student Financial Assistance, based on instructions provided by the College of Graduate Studies. Fellowships are given to support a student's graduate study and do not have a work obligation. For more information, see ¼¤Çé¿ì²¥ Graduate Fellowships, which includes descriptions of university fellowships and what you should do to be considered for a fellowship.

All MS students must have an approved **Plan of Study (POS)** developed by the student and advisor that lists the specific courses to be taken as part of the degree. Students must maintain a minimum GPA of 3.0 in their POS, as well as a "B" (3.0) in all courses completed toward the degree and since admission to the program.