Master of Science in Applied Statistics, Analytics and Data Science

Program Overview

The Master of Science in Applied Statistics, Analytics and Data Science from the University of Kansas Medical Center is a 100% online program that equips graduates with practical statistical computing skills for careers in statistics, biostatistics, analytics, and data science. The program offers three areas of emphasis: Analytics, Statistics, and Data Science, and emphasizes the importance of statistical theory and practical application. Graduates are expected to demonstrate proficiency in industry-standard statistical software, collaborate on project teams, and communicate effectively about statistics and analytics.

Program Outline

Degree Overview:

The Master of Science in Applied Statistics, Analytics and Data Science is a 100% online program offered by the Department of Biostatistics & Data Science at the University of Kansas Medical Center, delivered through the University of Kansas-Edwards campus. The program equips graduates with practical statistical computing skills, focusing on proper application and problem-solving, preparing them for careers in the growing fields of statistics, biostatistics, analytics, and data science. The program emphasizes the importance of statistical theory and practical application, with students choosing from three areas of emphasis:

• Analytics Emphasis: Provides experience working with and analyzing large datasets using statistical software tools.
• Statistics Emphasis: Offers hands-on statistical computing in the context of statistical methods commonly used in industry and government agencies.
• Data Science Emphasis: Equips students with skills in statistical and computational methods for acquiring and analyzing Big Data.

Graduates of this program are expected to be able to:

Demonstrate an understanding of statistical theory and practice. Function as collaborators on project teams. Demonstrate proficiency in industry-standard statistical software. Take responsibility for the design and implementation of analyses for projects within their field. Assist with the design and implementation of data management systems for projects within their field of application. Prepare reports and publications resulting from their projects. Communicate effectively about statistics and analytics to peers with varying statistical backgrounds. Advocate for good statistical design and practice.

Outline:

The M.S. in Applied Statistics, Analytics and Data Science program requires the completion of 30 credit hours.

Program Structure:

• Foundation Courses (Minimum 12 credit hours):
• STAT 805: Professionalism, Ethics and Leadership in the Statistical Sciences (3 hours)
• STAT 835: Categorical Data Analysis (3 hours)
• STAT 840: Linear Regression (3 hours)
• STAT 850: Multivariate Statistics (3 hours)
• Emphasis Courses (Minimum 12 credit hours):
• Analytics Emphasis:
• STAT 820: SAS Programming I (3 hours)
• STAT 823: Introduction to Programming and Applied Statistics in R (3 hours)
• STAT 830: Experimental Design (3 hours)
• STAT 880: Data Mining and Analytics (3 hours)
• Statistics Emphasis:
• STAT 820: SAS Programming I (3 hours)
• STAT 825: Nonparametric Methods (3 hours)
• STAT 830: Experimental Design (3 hours)
• STAT 871: Mathematical Statistics (3 hours)
• Data Science Emphasis:
• STAT 823: Introduction to Programming and Applied Statistics in R (3 hours)
• DATA 824: Data Visualization and Acquisition (3 hours)
• DATA 881: Statistical Learning I (3 hours)
• STAT 880: Data Mining and Analytics (3 hours) or DATA 882: Statistical Learning II (3 hours)
• Elective Courses (Minimum 6 credit hours): Specific courses are determined in consultation with the student's advisor.
Courses taken externally must be approved by the department's curriculum committee.

Course Schedule:

• Typical plans of study are provided for each emphasis area, with students completing the program within two years, although a maximum of seven years is allowed.

Assessment:

• General Examination: A comprehensive examination administered during the final term of enrollment.
• It assesses the student's strengths and weaknesses and determines their eligibility for the M.S.
degree.
• The examination is created and administered by a committee of at least three members of the Department Graduate Faculty.
• A second examination may be taken if the first is failed, subject to committee approval.

Careers:

• The program prepares graduates for careers as statisticians, analysts, and data scientists.

Other:

• The program emphasizes the importance of developing professional attributes, including:
• Observation skills
• Communication skills
• Motor function
• Intellectual, conceptual, integrative, and quantitative abilities
• Behavioral and social attributes
• The program is designed to be flexible, allowing students to take time off without a leave of absence for up to one academic year.
• Students can reactivate their enrollment after a period of non-enrollment.
• Leaves of absence are available in extraordinary circumstances, such as illness, emergency, financial hardship, military leave, or pregnancy/childbirth.
• Students must complete a Leave of Absence Checklist and obtain approval from their Program Director and the Dean of Graduate Studies for a leave of absence.
• Students must complete a Request for Return from Leave of Absence Checklist to return from a leave of absence.