Program Overview

Overview of the Applied Statistics (MS) Online Program

The Applied Statistics (MS) Online program is designed to provide students with a comprehensive understanding of statistical models, data analysis techniques, and computational software platforms. The program requires a minimum of 48 quarter hours of graduate-level work and offers concentrations in Biostatistics, Data Science, and General Applied Statistics.

Learning Outcomes

Students who complete the Applied Statistics (MS) Online program will be able to:

• Demonstrate knowledge of the mathematical basis and foundations of probability and statistics
• Implement various mathematical, statistical, and data analysis techniques to model and analyze complex problems
• Solve real-world problems using appropriate statistical procedures with a focus on precision and accuracy
• Use computational and statistical software platforms to develop and execute various statistical procedures and algorithms
• Communicate statistical ideas clearly, both verbally and in writing, using appropriate statistical terminology

Degree Requirements

The Applied Statistics (MS) Online program requires a minimum of 48 quarter hours of graduate-level work, including:

• 28 quarter hours of core courses
• 20 quarter hours of concentration requirements
• Candidates must complete at least 48 quarter hours of graduate-level work in applied statistics

Core Course Requirements

The core course requirements include:

• MAT 441: Applied Statistics I (4 quarter hours)
• MAT 442: Applied Statistics II (4 quarter hours)
• MAT 443: Applied Statistics III (4 quarter hours)
• MAT 451: Probability and Statistics I (4 quarter hours)
• MAT 452: Probability and Statistics II (4 quarter hours)
• MAT 453: Probability and Statistics III (4 quarter hours)
• MAT 456: Applied Regression Analysis (4 quarter hours)

Concentration Requirements

Students must choose one concentration: Biostatistics, Data Science, or General Applied Statistics. Each concentration requires a minimum of 20 quarter hours of coursework.

Concentration Options

• Biostatistics Concentration, Applied Statistics (MS)
• Data Science Concentration, Applied Statistics (MS)
• General Applied Statistics Concentration, Applied Statistics (MS)

Program Graduate Academic Student Handbook

The program graduate academic student handbook outlines the academic policies and procedures for the Applied Statistics (MS) Online program, including:

• Academic probation: a student will be placed on academic probation if their cumulative GPA falls below 2.70
• Academic dismissal: a graduate student may be academically dismissed if their cumulative GPA remains below 2.70 after one year of coursework while on academic probation
• Conditional admission: students whose undergraduate degrees were in majors other than mathematics or related fields may be conditionally admitted provided they complete the minimum prerequisites
• Readmission: the same readmission standards outlined in the Graduate Student Handbook and approval of the program director are observed for students in these programs
• Transfer credit: no more than two graduate courses (8 quarter hours or its semester equivalent) may be transferred from another program or institution
• Undergraduate courses: no undergraduate courses shall count toward the graduate degree
• Graduation requirements: requirements include, but are not limited to, twelve graduate courses (48 credit hours) at a minimum cumulative GPA of 2.70
• Graduation with distinction: a minimum cumulative GPA of 3.83 for coursework applied toward the applied statistics degree is required for graduation with distinction
• Time limitation: the degree is expected to be completed in a maximum of six years

Additional Information

The Applied Statistics (MS) Online program is designed to provide students with a comprehensive understanding of statistical models, data analysis techniques, and computational software platforms. The program is well-supported with equipment and software necessary for research, and computers are used for data analysis and to find solutions to problems that arise in numerical analysis, simulations, and mathematical modeling.