Admissions - MACSS

Admissions

Who should apply?

Applicants with an undergraduate degree (or its equivalent) in a social science discipline are encouraged to apply. This includes (but is not limited to) disciplines like anthropology, demography, economics, geography, history, linguistics, psychology, political science, and sociology, as well as interdisciplinary social-science programs like communications, ethnic studies, gender and sexuality studies, global studies, and political economy.

We are looking for undergraduate students in their final year of study and early career professionals who are eager to learn new statistical and computing tools and techniques, and to use them to generate new insights into social data and solve real-world problems.

Application Requirements

Application Requirements

The statement of purpose should convey why an applicant is interested in the MaCSS program, their interest in interpreting social data using computational methods and statistical analysis, and how this degree aligns with their professional and personal interests.
Personal statements allow the admission committee to gain insight into who applicants are as people. Applicants can share how they’ve overcome challenges or barriers to education, their ability to work collaboratively with people from diverse backgrounds, or the implications of social data analysis on marginalized or underrepresented groups.
From your undergraduate institution(s) and any higher-degree-granting institution(s) you attended. Additional details are located on the Graduate Division website
We only require two letters of recommendation with at least one (1) recommendation from a faculty member.

Instructions:

The application system requires you to enter 3 email addresses even though we only require 2 recommendation letters. Please put your own email address as the third option. This will prompt the system to send you an email with instructions to submit which you can ignore.

If you are applying for priority admission (Jan 8th deadline), please let your recommenders know that their letter must be received by January 8th. The email they receive from the application system only includes the second deadline (March 1st). Please note that only applications received by the priority deadline can be considered for fellowships.
Applicants whose first language is not English and who did not receive a bachelor’s degree from a country whose official language is English, must submit official evidence of English language proficiency. Additional information is located on the Graduate Division website
The Graduate Record Examination (GRE) is not required, although you are welcome to submit your GRE score. If you choose not to take the GRE, you are required to submit a quantitative skills statement.
Please submit a 1-page statement about your experience with quantitative methods. Click here to view an example and for additional information.

Some of the information included in this statement may overlap with your traditional resume; it is fine to include it in both. Uploading a duplicate copy of your traditional resume will not fulfill this requirement.

Please include the following:

A list of no more than five (5) entries which includes your quantitative courses (mathematics, statistics, and physical-science or social-science methods), and your experience using quantitative methods in a professional environment (paid, volunteer, or internship).

For each course, please include (1) the course name, (2) the school where it was taken, (3) semester/quarter and year it was completed, (4) grade received, and (5) a short course description or summary of major concepts covered.

Your professional experience may include regular work tasks and/or substantive projects completed. Please address any analytical skills acquired (e.g., use of data-analysis software or data-visualization tools.
Please upload a current resume reflecting your work experience, education, and other relevant information. There is no page limit for the resume. Your resume should be submitted under the "Supporting Materials" section of the on-line application.

We value a diversity of backgrounds and accept candidates with a wide range of experiences. Work experience is not required for admission, and the committee is not looking at quantity but rather the quality, range, and substance of your experiences.
Please upload a 1-2 minute video or audio file on the Audio/Visual page answering the following prompt: Tell us about how analyzing data impacts people, groups, cities, or regions in the U.S., another country, or around the world.

Tips:
  • Collect your thoughts before recording
  • Speak with confidence and enthusiasm
  • Be aware of your environment when recording and try to reduce any disturbances or background noise.
  • Keep it simple - use a smartphone or laptop to record your audio/video prompt.
  • Be yourself!

    • Additional details on application requirements are located on the Graduate Division website

    Application Review Process

    We take a holistic approach to the application review process, paying attention to the demonstrated ability to overcome hardships and non-traditional educational and career paths.

    The statement of purpose should convey why an applicant is interested in the MaCSS program, their interest in interpreting social data using computational methods and statistical analysis, and how this degree aligns with their professional and personal interests.

    An applicant’s personal statement allows the admission committee to gain insight into who applicants are as people. Applicants can share how they’ve overcome challenges or barriers to education, their ability to work collaboratively with people from diverse backgrounds, or the implications of social data analysis on marginalized or underrepresented groups.

    Important admissions deadlines

    JAN 8,
    2024

    Application Deadline for Fellowship Consideration

    MAR 1,
    2024

    Final Application Deadline

    APR 1 (Jan 8 apps)
    APR 5 (Mar 1 apps)

    Last Date to Accept Admission Offer

    About MaCSS