Program Overview

Introduction to the Master's in Survey and Data Science

The University of Maryland offers a Master of Science in Survey and Data Science, a program designed to meet the increasing demands from the federal statistical system and the private sector to expand their data science capabilities. This program has three tracks of study: Statistical Science, Social and Psychological Science, and Data Science.

Program Overview

The Master of Science in Survey and Data Science is a designated STEM program. The program requires the completion of 46 credit hours of academic work, including a set of general core courses, track-specific core courses, and elective courses. A summer internship or work in a job related to survey methodology is also required to satisfy the internship requirement.

Tracks of Study

The program has three tracks of study:

• Statistical Science: Designed for students who wish to specialize in areas such as sample design, estimation in complex samples, variance estimation, statistical measurement error models, and statistical adjustments for missing data.
• Social Science: Designed for students who wish to specialize in areas such as questionnaire design, design of interviewing systems, computer assistance in data collection, effects of mode of data collection, cognitive psychological insights into survey measurement, and efforts to reduce various non-sampling errors in data collection.
• Data Science: Designed for students who wish to specialize in the more computational aspects of survey methodology and research involving "big data," including data visualization, management and analysis of large and messy data sets, human-computer interaction in survey research, and machine learning algorithms.

Program Requirements

The key components of the program are:

• Total of 46 credit hours with an average grade of B, or better
• 3-month internship with a government agency or private survey firm

General Core Courses

The general core courses for all tracks include:

• Surv621 Fundamentals of Data Collection 1
• Surv622 Fundamentals of Data Collection 2
• Surv615 Statistical Modeling and Machine Learning 1
• Surv616 Statistical Modeling and Machine Learning 2
• Surv617 Applications of Statistical Modeling
• Surv720 Total Survey Error and Quality 1
• Surv721 Total Survey Error and Quality 2
• Surv727 Fundamentals of Data Display and Computing
• Surv740 Fundamentals of Inference
• Surv745 Practical Tools for Study Design and Inference
• Surv772 Survey Design Seminar

Track-Specific Core Courses

The track-specific core courses are:

• Social Science:
  • Surv625 Applied Sampling
  • Surv630 Questionnaire Design
  • Surv632 Cognition, Communication & Survey Measurement
  • Surv701 Analysis of Complex Sample Survey Data
• Statistics:
  • Surv410 Introduction to Probability
  • Surv420 Introduction to Statistics
  • Surv440 Sampling Theory
  • Surv742 Inference from Complex Surveys
• Data Science:
  • Surv613 Machine Learning for Social Science
  • Surv625 Applied Sampling
  • Surv701 Analysis of Complex Sample Survey Data

Potential Electives

Any core courses listed as required in other tracks can be taken as electives. Additional elective courses may be available.

Internship

A summer internship is typically between the first and second years of the full-time program. Part-time students can use their work experience to substantiate an equivalent internship experience. The internship serves three main purposes:

1. Practical Experience: To provide students with hands-on experience in a real-life survey and data environment.
2. Career Pipeline: Many organizations use internships as a pathway to future full-time employment.
3. Professional Skills: Beyond substantive knowledge, internships help students understand team dynamics, organizational workflows, communication, and other essential professional skills.

Academic Background Required

The academic background required for each track is:

• Statistical Science: Prior coursework in calculus, linear algebra, and statistics.
• Social and Psychological Science: Prior coursework in the social sciences and quantitative courses, including at least one statistics course.
• Data Science: Formal training in programming and at least one semester of statistics.

Tuition and Funding

The University of Maryland is a public institution, committed to providing excellent education at affordable prices. The 46-course MS program’s flat tuition rate is $1,223 per credit. The total cost of the MS program (46 credits / 2 years) is $56,258 (tuition) + $2,908 (university fees) = $59,166.

Financial Aid

Financial aid for graduate students is typically limited, and JPSM is mostly self-pay. However, financial assistance is available to qualified JPSM students in the form of graduate research assistantships, teaching assistantships, internships at federal statistical agencies, and University of Maryland awarded fellowships.

International Students

International applicants who will need the University of Maryland to sponsor an F-1 student visa must apply for fall enrollment to UMD. International applicants who already reside in the US on existing visas that permit study may apply to any version of the program.

English Language Proficiency Requirements

Any student whose previous degrees are all from non-English speaking countries must submit TOEFL, IELTS, or PTE scores. The requirements for full admission are:

• iBT TOEFL: Total: 96, Speaking: 22, Listening: 24, Reading: 26, Writing: 24
• IELTS: Total: 7.0, Speaking: 6.5, Listening: 7.0, Reading: 7.0, Writing: 7.0
• PTE: Minimum score of 68

Official copies of scores must be sent directly to the UMD Graduate School.

Conclusion

The Master's in Survey and Data Science at the University of Maryland is a comprehensive program that offers students a range of specializations and opportunities for practical experience. With its affordable tuition and available financial aid, this program is an excellent choice for students looking to pursue a career in survey methodology and data science.