Our 36 credit, STEM-OPT approved, terminal master’s degree program prepares students to collect, interpret and communicate the results of data analysis across a wide berth of social science fields.
Academics
Students are first introduced to basic/intermediate statistics courses and computation programming/data manipulation. They will then take research courses both within and outside of their preferred discipline, culminating in a research project or thesis on a topic of their choice (in conjunction with an advisor).
Additional academic and pre-professional opportunities include:
Professionalization Seminars. In addition to formal coursework, professionalization seminars will be held every semester (typically, two to three), in coordination with Graduate Student Associations, to discuss various career interest and issues related to the field of data science.
Advisement
Each student will meet with the Director of Graduate Studies for the DASS program each semester. At this meeting, the director will provide academic advice to students on every relevant matter, including the students’ course schedule for the upcoming semester. Students will also select a faculty member in their specialty department for thesis or project guidance. The project advisor must be selected no later than at the end of students’ second semester of full-time study.
In addition to meeting with the Director of Graduate Studies for the program, students will also select a faculty member in their specialty department for thesis or project guidance. The project advisor must be selected no later than at the end of students’ second semester of full-time study. Below is a list of faculty members who are currently able to accept students for DASS project advisement. Please refer to individual departments’ faculty directories to learn more about a faculty member’s research areas.
Note that this list will be updated regularly to reflect faculty availability to advise DASS students.
6 credits of computation programming/data manipulation
6 credits of research methods
6-9 credits of coursework in advanced data analysis within one social science discipline
3-6 credits of project or thesis guidance
Each student will be required to take at least 9 credit hours in a department other than their specialty discipline to increase familiarity with the methods of adjacent fields.
Final Project/Thesis
The MS project or thesis will be submitted to two faculty members from two distinct departments (including the student’s project advisor), who have the sole responsibility for its review, revision and acceptance. Each committee member must be in one of the participating social sciences departments and hold membership in UB’s graduate faculty. In exceptional cases (and if the project warrants), one member of the MS committee might be from a non-social science department.
What is a Master's Project?
A master's project takes an applied approach to developing a practical solution or solving a specific problem in your chosen field in the social sciences. The structure of a project can be more flexible and may include a project report, design documentation or a prototype, with the goal of demonstrating your ability to apply theoretical knowledge in a practical setting. Examples of master's project topics include:
Develop a predictive model to assess the impact of lifestyle factors on health outcomes.
Develop a predictive model to identify high-risk areas for crime in a city. This project could involve analyzing historical crime data, identifying patterns, and creating a model to predict future crime hotspots. The findings could help law enforcement agencies allocate resources more effectively.
Study the factors that influence consumer behavior and economic decision-making.
Develop a policy framework to enhance community resilience to climate change. This project could involve analyzing climate data, assessing community vulnerabilities, and proposing policy measures to mitigate risks and improve adaptive capacity.
Develop and evaluate a mental health intervention program for college students.
Conduct an epidemiological study on the spread of an infectious disease in a specific population.
Design and implement a health promotion campaign to address a public health issue, such as smoking cessation or obesity prevention.
Document and analyze an endangered language and develop strategies for language preservation and revitalization.
Create a detailed map of urban heat islands in a city using remote sensing and GIS, and suggest mitigation measures.
Study the process of gentrification in a particular neighborhood and analyze demographic and economic data to understand the effects on local communities.
Investigate how climate change is affecting coastal erosion in a specific region and model future erosion scenarios.
Study the impact of urban development projects on social equity in a specific city and propose strategies to ensure equitable development.
Develop predictive models to forecast economic trends using big data. This project might include collecting and analyzing economic data, building machine learning models, and evaluating their accuracy in predicting economic indicators.
Analyze migration patterns and their impact on urbanization. This project could involve collecting demographic data, mapping migration flows, and identifying trends and factors driving migration.
Admissions
Fall Application Deadline: May 1 Spring Application Deadline: November 1
Admissions guidelines for the program are as follows:
BA/BS in a social science discipline, though special provision may be made for students with degrees in the humanities (particularly those interested in digital humanities)
3.0 undergraduate GPA in social science area courses
Two (2) letters of recommendation
Resume or curriculum vitae (CV)
One (1) writing sample
Statement of educational and career goals
International students will need to provide proof of English proficiency via standardized test scores.