MS in Civic Analytics

Admission Requirements

Applicants are considered on an individual basis. In addition to the Graduate College minimum requirements, applicants must meet the following program requirements:

  • Baccalaureate Field: Baccalaureate degree holders in any field may be admitted to the program. Students will be advised that prior coursework in statistics, geographic information systems, mathematics, or information technology disciplines is desirable.
  • Grade Point Average: Minimum 2.75/4.00 for the final 60 semester (90 quarter) hours of undergraduate study.
  • Evidence of Quantitative and Analytical Skills: Due to the quantitative nature of the Master of Science in Civic Analytics (MSCA) degree, applicants are asked to have or prove evidence of one or more of the following:
    • Bachelor or higher degree with coursework in data analysis or visualization
    • Transcripts that include a grade of B or higher in a course in statistics or calculus
    • Completion of a data science boot camp, training in coding and data, or relevant professional certifications
    • Professional or volunteer experience, internship placement, or works products related to quantitative analysis
    • GRE or GMAT scores
    • Other supporting evidence that the applicant deems appropriate

Students who are unable to provide any of the items listed above are still encouraged to apply. The department offers supplemental instruction for students needing additional preparation.

  • Minimum English Competency Test Score:
    • TOEFL iBT 90, with subscores of Reading 21, Listening 21, Speaking 25, and Writing 23, OR,
    • IELTS Academic 6.5, with 6.0 in each of the four subscores, OR,
    • PTE-Academic 61, with subscores of Reading 51, Listening 47, Speaking 53, and Writing 56.
  • Personal Statement Required. The brief personal statement shall address how the MSCA degree will further the student’s educational and career objectives. The student will also provide an expanded narrative that discusses their familiarity with information technology and applied statistics.
  • Additional Materials   
    • Required: Applicants must submit a resume.
    • Prerequisites: The applicant must provide documentation that they have completed an undergraduate or graduate‐level data analysis or statistics course in the last three years with a grade of B or higher. This course will be more than a research design course and cover descriptive and inferential statistics. If the student does not have such a course but meets the other requirements for admission, they will be required to enroll in PA 402 or equivalent course. This requirement would be waived for those coming to the program with a statistics degree. 
    • Optional: Applicants may submit a 5–10 page writing sample and up to three letters of recommendation. These letters should be from instructors familiar with the applicant’s academic training or supervisors familiar with the applicant’s professional experiences. 
  • Nondegree Applicants Nondegree Applicants must submit an official transcript from their baccalaureate institution, resume, and a letter stating which courses they would like to take and why they feel nondegree admission would be beneficial.

Degree Requirements

In addition to the Graduate College minimum requirements, students must meet the following program requirements:

  • Minimum Semester Hours Required 53.
Foundational Core Courses (25 hours)
Foundations of Public Service
Introduction to Data Management and Analysis
Economics for Management and Policy
Public Policy Development and Process
Strategic Management: Planning and Measurement
Capstone and Portfolio in Public Policy, Management, and Analytics
Managing Your Career
MSCA Core (20 hours)
Civic Technology
Intermediate Data Management and Analysis
Coding for Civic Data Applications
AI & Machine Learning
Advanced Data Analysis I
Electives (8 hours)
Select 8 semester hours from the following: a
Public Program Evaluation
Advanced Data Analysis II
Social Network Analysis
Qualitative Research Methods in Public Administration
Survey Data Collection Methods: Theory and Practice
Intermediate GIS for Planning and Policy
Complexity-based Models for Planning and Policy
Advanced Visualization Techniques
Foundations of Analytics and AI for Supply Chain and Operations Management
Deep Learning and Modern Applications
Rating Scale and Questionnaire Design and Analysis
Item Response Theory/Rasch Measurement
Hierarchical Linear Models
Non-Parametric Modeling
Structural Equation Modeling
Python for Data Science and Large Language Models
Longitudinal Data Analysis
a

Another course may be used to fulfill these requirements with the permission of the program director.

  • Grade Point Average Students must maintain an overall GPA of 3.00/4.00 in the program in order to graduate and must receive a C or higher in all required courses.
  • Comprehensive Examination: None
  • Thesis, Project, or Coursework-Only Options: Coursework only. No other options available.