The Master of Science in Statistical Computing, Data Mining track focuses on data mining and its application to business, social, and health problems.
|Total Credit Hours Required:|
Credit Hours Minimum beyond the Bachelor's Degree|
The Data Mining track in the Statistical Computing MS program is composed of 24 credit hours of required courses and 12 credit hours of restricted electives. Students must also pass a comprehensive written examination.
Required Courses—24 Credit Hours
- STA 5104 Advanced Computer Processing of Statistical Data (3 credit hours)
- STA 6714 Data Preparation (3 credit hours)
- STA 6238 Logistic Regression (3 credit hours)
- STA 6326 Theoretical Statistics I (3 credit hours)
- STA 6327 Theoretical Statistics II (3 credit hours)
- STA 6236 Regression Analysis (3 credit hours)
- STA 5703 Data Mining Methodology I (3 credit hours)
- STA 6704 Data Mining Methodology II (3 credit hours)
Note: STA 5703 and 6704 both require research projects that fulfill the independent learning requirement for the program.
Elective Courses—12 Credit Hours
Select electives from the following courses.
- COP 4710 Database Systems (3 credit hours)
- STA 5205 Experimental Design (3 credit hours)
- STA 5505 Categorical Data Methods (3 credit hours)
- STA 5825 Stochastic Processes and Applied Probability Theory (3 credit hours)
- STA 6106 Statistical Computing I (3 credit hours)
- STA 6226 Sampling Theory and Applications (3 credit hours)
- STA 6237 Nonlinear Regression (3 credit hours)
- STA 6507 Nonparametric Statistics (3 credit hours)
- STA 6707 Multivariate Statistical Methods (3 credit hours)
- STA 6857 Applied Times Series Analysis (3 credit hours)
- STA 6705 Data Mining Methodology III (3 credit hours)
- FIN 6406 Strategic Financial Management (3 credit hours)
All students must take a comprehensive written examination covering the five courses STA 6326, STA 6327, STA 5103, STA 6714 and STA 6238. For full-time students, this examination will normally be taken just prior to the start of the second year of their graduate work. Students are allowed two attempts to pass the exam. Failure to pass after the second attempt will result in dismissal from the program.
INDEPENDENT LEARNINGSTA 5703 and 6704 both require research projects that fulfill the independent learning requirement for the program. Both courses require students to build models for target variables of projects with very large sets of data, write a report, and then give an oral presentation on their independent learning experiences.
For information on general UCF graduate admissions requirements that apply to all prospective students, please visit the Admissions section of the Graduate Catalog. Applicants must apply online. All requested materials must be submitted by the established deadline.
In addition to the general UCF graduate admission requirements, applicants to this program must provide:
- One official transcript (in a sealed envelope) from each college/university attended.
- Official, competitive GRE or GMAT score taken within the last five years.
Applicants not qualified for regular graduate status may be initially admitted to the university in non-degree-seeking status and later admitted to regular status once all deficiencies have been eliminated, although only nine hours of graduate course work taken as a non-degree-seeking student can count toward a graduate degree.
Meeting minimum UCF admission criteria does not guarantee program admission. Final admission is based on evaluation of the applicant's abilities, past performance, recommendations, match of this program and faculty expertise to the applicant's career/academic goals, and the applicant's potential for completing the degree.
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International Transfer Applicants
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