FAQ

This MS program is a good choice if you like working with numbers and solving problems and want to sharpen your data-analysis and analytical skills. It's also great for those who are interested in learning how and when to use advanced statistical methods and how to interpret the results. It's ideal for individuals who want to use these skills to address important social problems or to inform policy and practice across any number of applied fields. The program is designed to help you develop and improve your ability to perform and understand complex quantitative research in the social, behavioral, and health sciences.

NYU offers different options to study applied statistics and data science. See the Center for Data Science website for information about the MS in Data Science and the Stern website for information about the MS in Business Analytics. The College of Global Public Health offers a related MS in Biostatistics and our programs share some courses.  A3SR has a strong focus on statistical methods, including machine learning algorithms, and is geared more towards social science and policy rather than industry. 

Yes. Although the program is designed for students with some statistical and data analysis skills, it is possible for candidates from other quantitative backgrounds to gain admission to the program. In general, students should be familiar with the concepts covered in a non-calculus based introductory statistics course series. Your knowledge of these topics will be assessed through a placement exam process to better help us advise you into a proper course sequence.

Our course sequence and substantive focus prepares students for data analytic work in the social, behavioral, health, and education sciences, as well as social policy. We do not offer many of the courses that would be necessary to pursue a career in investment banking or finance.

We welcome students who are recent college graduates as well as those who have worked in a related field or are interested in changing the direction of their professional career.

Our deadline is January 15 for September matriculation. Late applications may be accepted if space is available. We currently only accept students for September matriculation.

In addition to a strong academic record, we prefer applicants who should have majored or minored in a quantitative discipline that provides a solid foundation for advanced study of applied statistics or completed a selection of courses typically found in such quantitative disciplines. Successful applicants also include students who majored in a social science or other empirically driven field but have taken a sufficient number of math, statistics, and programming classes and performed well in them. On occasion students without this type of background have been able demonstrate sufficient background in experience through self-study or data-analytic work in their post-college career.

For additional information, please visit the How to Apply page.

Applicants whose first language is not English are required to take one of the following English proficiency exams and submit the scores: TOEFL, IELTS, Duolingo, or PTE Academic. See more information on English proficiency testing.

Successful candidates have generally scored at or above 105 on the internet-based exam, an IELTS score at or above a 7.5, or a Duolingo score of 125 or above.

• Online application form
• Application fee
• Resume
• Statement of Purpose
• Applied Statistics Essay
• All college transcripts
• Two letters of recommendation
• Writing sample

For more information on the application process, please refer to the How to Apply page.

Currently, the GRE is optional for this year for the MS program. This policy may change in the future.

Yes, please submit two letters from professors or former employers from the last five years. These should speak to your proven abilities in statistics, mathematics, or computer science as well as your professional interests and promise as a student and researcher.

No, an interview is not required for admission.

All admissions materials, including letters of recommendation, transcripts, and the supplemental one-page statement, are submitted through the online application. If you have additional questions regarding the online application system, please contact Graduate Admissions at steinhardt.gradadmissions@nyu.edu.

Our review of candidates for admission is holistic; we consider all components of the application when making admission decisions. Successful candidates for admission will demonstrate a strong record of academic achievement either at the undergraduate level or from previous graduate-level course work from accredited institutions.

On-campus housing at NYU is limited. Most graduate students live off-campus. Graduate Admissions serves as the liaison office to NYU Housing so general questions about the process may be directed to them. Learn more about on and off-campus housing.

Our schedule of courses is posted online each semester. If you would like to attend a class, please email us at steinhardt.a3sr@nyu.edu.

Online and in-person information sessions are hosted in the fall semester.

We recommend you attend one of our online Information Sessions, where you will be able to hear about the program from faculty, advisers, and current students. To RSVP, please visit the Information Sessions website. If you can't attend, you can also be sent a link to watch a recording of the session. To receive the link of the recording or if you wish to ask specific questions, please email steinhardt.a3sr@nyu.edu.

You can also email our ASH Ambassadors to connect directly with a current master's student in the department.

This is a variable 34–43 credit program. Those who accelerate by showing competency in certain topics may be able to reduce the number of credits required below 43.

The required credits for a student with no prior related course work is 43. Students will have the opportunity to decrease their number of credits during the advisement process, prior to the start of the first semester. Students will be asked to complete assessments in relevant topics/fields.

This is a variable 34–43 credit program. The full-time program can be completed in 3 or 4 semesters, depending on your prior statistical training. Part-time enrollment is permitted and will, of course, take longer – usually up to 6 semesters.

Our cohort size varies from year to year but we often enroll small cohorts so that we can provide personal attention to all of our students.

Yes, there is a process by which you can switch your concentration during your degree.

You may not transfer credits from other institutions and have them count toward the MS degree, however, certain course requirements may be waived based on the successful completion of the acceleration exam(s) or at the discretion of the Applied Statistics for Social Science Research program. Waiving will decrease the number of credits needed to complete the program and will allow students greater flexibility in pursuing course work relevant to their specific interests.

It is possible to work full time and still take classes, however our classes are offered at all times of day, including during the standard work day.  Part-time students that work need to have the flexibility to schedule their hours to accommodate their class schedule. Asynchronous engagement in standard courses is not an option for this program. For more information see the FAQs related to the Part-Time Experience.

Not all courses will be offered each semester. Courses are scheduled, however, such that full-time and part-time students will be able to complete the program in a timely fashion.

We generally do not offer required courses or electives in the summer, but some of the elective courses offered in other departments are often offered in summer. With careful planning in conjunction with their advisor, students could fulfill certain program requirements (including an internship) during the summer.

Candidates for this degree are able to participate in an internship during the program for academic credit. The internship course (APSTA-GE 2310) can count as an elective for the program. 

NYU's Wasserman Career Center for Career Development provides assistance to all graduate students and alumni from NYU Steinhardt. In addition, a semi-monthly newsletter with career opportunities is sent to all students, the A3SR program page will be periodically updated with relevant career-related resources, and students can consult with program advisors about career matters. The program also offers several professional development events each year.

After accepting your offer there are a few required steps to ensure that you are fully prepared for the fall semester. Your admission letter will provide a link to some important next steps. In addition, the A3SR program requires an online placement exam to gauge your background in mathematics and statistics. This will allow us to place you in the most appropriate courses for your first semester. The Placement Exam page provides more information.

Students may complete the program on a full- or part-time basis. Current rates for tuition and fees are available on the Admissions page. These charges are assessed on a per-credit basis. You'll also find estimated expenses for housing, books and supplies, transportation, and health insurance. The Admissions site offers detailed information on applying for scholarships and other forms of financial aid.

Yes. Information on scholarships is listed on the Steinhardt Graduate Admissions website under Financial Aid. 

All applicants who are interested in being considered for scholarships MUST complete the Free Application for Federal Student Aid (FAFSA) by going to www.fafsa.ed.gov and submitting it electronically to NYU. Detailed instructions can be found on the Graduate Admissions Financial Aid web pages. 

The deadline for submitting the FAFSA to NYU is March 1. Please note that the earliest time you can access the form is October 1.

For the past few years, the PRIISM Center at NYU has also been able to offer the PRIISM Opportunity Fellowship to two incoming A3SR students each year. Decisions on fellowships are decided by the faculty during the admissions process and awardees are generally contacted soon thereafter.

NYU Steinhardt is committed to assisting graduate applicants in the process of financing their education. One way we do this is by offering partial tuition scholarships (such as the Centennial Scholarship for new part-time master's students), fellowships, and assistantships that are based on merit and financial need. Fellowships and assistantships, however, are comparatively uncommon for part-time students. Other forms of aid, such as loans, college work-study, and student employment can help part-time students complete their advanced degrees. For more information, visit our Financial Aid website.

NYU Steinhardt encourages international applicants to investigate scholarship support offered by their home country to support their studies at NYU. Master's and advanced certificate applicants who are US citizens or permanent residents and eligible for federal financial aid may receive consideration for school-based financial aid. Non-US citizens may be eligible for non-NYU sources of funding. NYU provides a list of external Scholarship Search Services that may be helpful in researching funding.

All international students may also seek on and off-campus employment opportunities. For more information and resources for working in the US, please visit the NYU Office of Global Services website.

Many of our students are able to find part-time work either within or beyond the university while they are pursuing their degree. The program directors regularly send out announcements from faculty or employers who are looking to hire students with data analytic skills.

Part-time students generally complete 6 - 9 credits in the Fall and Spring semesters, and 3 - 4 credits in the Summer.

Students attending the program part-time generally can complete their degrees in two and a half to three years, depending on the number of credits completed per semester. 

Classes in the A3SR program are offered at a variety of times, but most are scheduled either fully or partially within normal business hours.  Part time students are most successful when they have a flexible work schedule that can accommodate attending regularly scheduled classes. Unfortunately, we cannot accommodate remote or asynchronous attendance for most courses. Previous course offerings and times are available for review.