Statistics & Data Science MS Overview
The M.S. in Statistics and Data Science are terminal degree programs that are designed to prepare individuals for career placement following degree completion. The M.S. does not directly lead to admission to the Statistics Ph.D. program however, those with a strong academic record in statistics and probability theory, and demonstrate promising ability to conduct in-depth research should consider applying to the doctoral program in Statistics.
Students are expected to live within commuting distance of Stanford campus to ensure significant engagement with the department and faculty.
Department orientation for new Stats and DS students
Our mandatory new student orientation typically takes place the Thursday before autumn quarter starts.
University orientation events will be announced in September. The week's events are hosted by the Graduate Life Office: NGSO. Students should plan to arrive on campus 1 to 2 weeks before the quarter starts.
Please orient yourself with the academic calendar in order to anticipate pending deadlines throughout your time in the program: 2022-23 academic calendar will be published in April.
2022-23 First Day of Classes and End of Term
- Autumn 2022-23: September 26 and December 16
- Winter 2022-23: January 9 and March 24
- Spring 2022-23: April 3 and June 14 (Commencement June 18)
- Summer 2022-23: June 26 and August 19
Length of the program
Students typically finish the degree program in 5 or 6 quarters (since summer quarter enrollment is not required, it is not figured into the 5-6 quarters). With a vast schedule of awesome courses offered during the year, the idea of staying longer is quite appealing to many, but one must weigh the cost of tuition and living expenses of enrolling beyond the degree's required 45 units. For those who can manage more than three courses each quarter, enrolling in 11+ units of required courses would allow a student to complete the degree in a shorter period of time (less cost of living/housing expenses).
We advise students to take 1-2 required courses each quarter and an elective course of interest in order to make satisfactory degree progress.
Suggested first quarter enrollment
First quarter enrollment example for the Statistics MS:
Theory of Probability (STATS 116)
Probability spaces as models for phenomena with statistical regularity. Discrete spaces (binomial, hypergeometric, Poisson). Continuous spaces (normal, exponential) and densities. Random variables, expectation, independence, conditional probability. Introduction to the laws of large numbers and central limit theorem.
Prerequisites: Integral Calculus of Several Variables (Math 52) and familiarity with infinite series, or equivalent (4 units)
After taking Stats 116, the students should be able to:
- Understand the principles of probability in discrete and continuous cases without measure theoretic detail.
- Apply counting techniques to solve probability problems in spaces with regularity or symmetry.
- Recognize important distributions in the exponential families and their connections.
- Apply probability models to real-world situations, and recognize famous problems in disguise, like the Birthday problem, the Ballot problem, and the Matching problem.
- Derive expectations and variances of random variables in structured probability spaces.
- Exploit probabilistic symmetries to solve simple problems.
- Understand results such as the Central Limit Theorem and Poisson approximation, and recognize their importance in statistical applications.
- Gain familiarity with more advance topics in probability.
Data Mining and Analysis (STATS 202)
Data mining is used to discover patterns and relationships in data. Emphasis is on large complex data sets such as those in very large databases or through web mining. Topics: decision trees, association rules, clustering, case-based methods, and data visualization.
After taking STATS 202 the students should be able to:
- Understand the distinction between supervised and unsupervised learning and be able to identify appropriate tools to answer different research questions.
- Become familiar with basic unsupervised procedures including clustering and principal components analysis.
- Become familiar with the following regression and classification algorithms: linear regression, ridge regression, the lasso, logistic regression, linear discriminant analysis, K-nearest neighbors, splines, generalized additive models, tree-based methods, and support vector machines.
- Gain a practical appreciation of the bias-variance tradeoff and apply model selection methods based on cross-validation and bootstrapping to a prediction challenge.
- Analyse a real dataset of moderate size using either R or Python.
- Develop the computational skills for data wrangling, collaboration, and reproducible research.
- Be exposed to other topics in machine learning, such as missing data, prediction using time series and relational data, non-linear dimensionality reduction techniques, web-based data visualizations, anomaly detection, and representation learning.
Applied Matrix Theory (MATH 104)
Linear algebra for applications in science and engineering: orthogonality, projections, spectral theory for symmetric matrices, the singular value decomposition, the QR decomposition, least-squares, the condition number of a matrix, algorithms for solving linear systems. MATH 113 offers a more theoretical treatment of linear algebra. MATH 104 and ENGR 108 cover complementary topics in applied linear algebra. The focus of MATH 104 is on algorithms and concepts; the focus of ENGR 108 is on a few linear algebra concepts, and many applications.
Learning objectives: Learn concepts and theorems well enough to formulate real world problems in the language of linear algebra and apply linear algebraic techniques to solve the problems.
First quarter enrollment example for the Stats - Data Science:
Introduction to Statistical Inference (STATS 200)
Introduction to Causal Inference (STATS 209)
This course introduces the fundamental ideas and methods in causal inference, with examples drawn from education, economics, medicine, and digital marketing. Topics include potential outcomes, randomization, observational studies, matching, covariate adjustment, AIPW, heterogeneous treatment effects, instrumental variables, regression discontinuity, and synthetic controls. Prerequisites: basic probability and statistics, familiarity with R.
Terms: Aut | Units: 3
Software Development for Scientists and Engineers (CME 211)
Basic usage of the Python and C/C++ programming languages are introduced and used to solve representative computational problems from various science and engineering disciplines. Software design principles including time and space complexity analysis, data structures, object-oriented design, decomposition, encapsulation, and modularity are emphasized. Usage of campus wide Linux compute resources: login, file system navigation, editing files, compiling and linking, file transfer, etc. Versioning and revision control, software build utilities, and the LaTeX typesetting software are introduced and used to help complete programming assignments. Prerequisite: introductory programming course equivalent to CS 106A or instructor consent.
Autumn quarter only.
Data Science students will be sent a link to the placement test in the summer. Students will be notified whether they can skip CME 211 which is a hard requirement for CME 212 offered winter quarter only.
ICME approved alternative to CME 211 is CS 107: Computer Organization and Systems
M.S. Program advisor assignments
M.S. program advisors assignments will be announced in September. MS advisor assignments are determined over the summer and will be announced in September. To ensure equity and easy distribution rules, students are assigned by their last name (alpha order).
If needed, you'll be able to discuss with your program advisor at the start of the quarter to help you determine the appropriate enrollment before the final study list deadline. Please see the information concerning course placement in the FAQ section below.
- Guidelines and expectations to help establish a professional and respectful academic advising culture
Independent Study (for Elective credit)
While research is not a required component of the degree, the desire to participate in research has been an increasing trend through recent years.
A common request n that has come up in the past few years is regarding the ability to conduct research (for credit), with faculty as independent study/directed reading/independent research.
[More on networking opportunities: Please also browse the information on relevant seminars, student groups and organizations near the bottom of this page.]
While there exists a way to earn credit for independent study/research (STATS299) under the supervision of their program adviser or other Statistics faculty. One must obtain approval from the advisor and provide clearly defined objectives and expected outcome(s) before obtaining permission from the faculty.
- Develop a goal statement for what the student hopes to accomplish and the purpose of the independent study. (List your goals by explaining what you hope to gain in terms of knowledge, skills, etc.)
- Select and/or develop learning objectives related to the goal statement. (Using broad statements, list each objective and/or learning activity in the plan.)
- Develop a timetable for implementation of activities and completion of course requirements. (Include what it is that you expect to do and produce and dates for completion and submission. List the types of activities/assignments that the you will be completing by the end of the quarter.)
Other (teaching/research) opportunities
TA/RA opportunities within the Statistics dept are designated for the doctoral students as it is a predominant training component of their 5-year program. There is very little chance that either of these opportunities would be available to students outside of the Statistics doctoral program. If an opportunity becomes available, it will be announced to the Statistics graduate student population.
The faculty do not manage the hiring of RA/TA, nor do they have funding to support Masters students.
Assistantships may sometimes be obtained from other departments and schools. Some students have had success finding Course Assistantships in the CS or MS&E (both in the School of Engineering), and occasionally other related departments. The onus is on the student to find these opportunities, and there are no guarantees. Begin an online search for Course Assistantship applications at least 3 months before the start of the next quarter as departments need to start the hiring process well before the quarter starts. Do not commit to a TA/CA position if you do not have the time to give to the job.
Some departments/schools solicit hourly research assistant positions from our M.S. students, which are not to be confused with assistantships (GAP 7.3) which carry full or partial tuition allowance. Before accepting a position, confirm with the hiring department whether the position is an hourly position, or if it indeed covers tuition.
At this time, the department does not publish job placement data of its graduates. Instead, we can provide a general trend of job placements in recent years:
Many students find employment in data science, research analytics, software engineering, program management within the technology sector (operations research), or the finance industry (asset management, acquisitions/mergers, business analytics) as well as various governmental services. The majority of our graduates have found employment in the Bay Area and other major cities around the world.
The career center (BEAM) hosts several career fairs throughout the year, and there is a tremendous benefit to our campus being situated in Silicon Valley. To participate, students upload their resumes in advance via Handshake, indicate which field/industry and companies they are interested in and industry partners reach out to schedule interviews.
We don't collect data on salaries. This information can be gathered in an online search of job recruitment and financial education sites.
- Data about mathematicians and statisticians from the U.S. Bureau of Labor Statistics
The number of students who pursue graduate programs is steadily increasing.
Statistics MS students that feel strongly about entering a 5-year program of research in statistical theory and applications should meet with their program advisor to discuss which programs and schools are an appropriate place and time to apply. With careful planning, students will be able to build a strong program that will make them highly competitive applicants wherever they apply.
Previous years' graduates had been accepted to doctoral programs in Statistics at Columbia, University of Washington, Wharton School, UC Berkeley and UCLA.
Common questions from incoming Statistics Masters students
When does autumn quarter registration start?
For Autumn 2021-22, students whose matriculation status is CLEAR will be able to enroll in courses September 1 (12:01 AM Pacific time).
- International students (with an active SEVIS number) will need to clear the enrollment hold by virtually attending the Maintaining Your Legal Status orientation.
Stanford's course registration system allows students to enroll in courses with conflicting meeting patterns. While this is allowed at the start of the quarter (first three weeks), students MUST it is generally discouraged due to time constraints and expectations and the course should be dropped by the end of week 3 (Final Study List deadline).
Instructors will not accommodate a student whose classes have conflicting end-quarter exams.
Does Stanford require a tuition deposit to secure admission?
Stanford does not require a deposit to confirm your acceptance or initiate matriculation.
The student bill for autumn quarter is due in October.
How do I know which courses to enroll in when I start in autumn quarter?
- Statistics M.S. course requirements
Statistics students: autumn quarter
- For those with basic or intro statistics/probability, we recommend starting with STATS116 - Theory of Probability (autumn)
- Students returning to school may wish to brush-up on their skills in statistics and probability and should also enroll in STATS116; Summary notes courtesy of Professor Dembo.
- Students with background in Stochastic Processes (Markov chains, Martingale approach, Poisson processes, Gambler's ruin) should consider STATS 219 autumn quarter or probability theory (STATS 310A)
- Students should be comfortable with probability at the level of STATS116/MATH151 (summary of material) and with real analysis at the level of Math115. Past exposure to stochastic processes is highly recommended.
- A new course STATS221 focuses on topics in discrete probability that are well beyond undergraduate probability, with particular emphasis on random graphs and networks. While at a level and style similar to STATS217, the material of STATS221 is more modern, and do not overlap any of STATS 217/218/219 (nor with the STATS310 sequence or with MATH236).
- Students with prior academic work (or work experience) consisting of advanced statistics and probability may wish to enroll in STATS200 Introduction to Statistical Inference, along with a linear algebra course or other higher-level course in Mathematics.
- For those familiar with the material in this problem set then STATS200 is recommended (autumn). If the problem set poses a struggle, then we suggest starting with STATS116
- Using the STATS200 course description to determine if the course content would be redundant material for you, STATS305A (autumn) is recommended instead.
- Same recommendations for the linear algebra requirement:
- or other higher-level course in Mathematics for those who have prior background in linear algebra:
- CME364A Convex Optimization I
- MATH115 Functions of a Real Variable
- MATH171 Fundamental Concepts of Analysis
- CME302 Numerical Linear Algebra
- For those with some programming experience (introduction to programming/intermediate programming), consider one of the following:
- or other higher-level course in the same area for those who have programming experience beyond the courses described above.
- For those with little or basic programming experience, it is common for students to start with a course in CS106 or CS107 or CME211.
- CME211 (211 notes) is the recognized pre-requisite, however, CS106 or 107 both offer a good foundation to CME212 (a required course).
- For students with better foundation in programming, there is a placement online exam in the summer for CME212 (winter)
- We recommend that students start with STATS200 autumn quarter and STATS203 the following quarter.
- Consider taking a course under the suggested electives section or CME302 Numerical Linear Algebra
Where can I find the course schedule?
ExploreCourses, the university's academic database, can be searched using the program code (e.g., STATS116, CS106, MATH104, etc.) or by subject. Please pay special attention to the quarter(s) that courses will be offered, as not all courses are offered at all times, and some are not offered more than once per year. The course schedule is updated in August each year.
*A new course catalog will be available in August. Explore Courses will redirect to the new database when it goes live.
How many quarters should I expect it to take for me to finish my degree?
Most students take 5-6 quarters to finish their degrees, not including summer quarter. Some students can finish it in as few as 4 quarters, many choose to stay for 6 quarters (A,W,S) over two academic years.
Can I do a Masters thesis (project)?
A thesis is not required for the Master's degree. Those who are interested in pursuing a thesis project, finding the right faculty is vital to starting any level of research. It takes considerable time and planning before permission is granted. Those who are successful then enroll in the Statistics STATS299 Independent Study course (up to 3 units) under the section number of their M.S. program advisor (or other faculty advisor).
As is stated in the admission offer letter, completing the M.S. degree in Statistics at Stanford is not a bridge to the Statistics Ph.D. at Stanford.
When can I expect to receive my new I-20 or transfer my current SEVIS record to Stanford?
Student Visa Application in Axess: "Initiate I-20 or DS-2019; Request." You may do so immediately following accepting in Axess. The I-20 process will begin after submission of required documentation. Bechtel International Center will contact you if they require any further information.
I'm an international student, how do I enroll for Autumn quarter?
New International Students:
- Release of Enrollment Holds: All F and J students are required to bring their passport, I-20 or DS-2019, and a recent print out/screen shot on digital device of your admissions I-94 electronic record to one of the Maintaining Your Legal Status workshops in order to have your enrollment hold removed. The hold will be removed within 24 hours.
- Prior to attending this workshop, you must update your SEVIS (U.S.) address and U.S. phone number on Axess. Instructions on how to update your address can be found on the Bechtel website: How to update your address
F-1 Students Who Attended Other U.S. Schools:
- All F-1 transfer students must complete the check-in process within 15 days of the program start date. This can only be done after you have updated your SEVIS (U.S.) address field and U.S. phone number in Axess and have attended one of the Maintaining Your Legal Status workshops at Bechtel.
- After these two requirements have been met you will receive an e-mail instructing you to come to Bechtel to pick up your Transfer Completed I-20.
Where do students typically live during their first year?
Most first-year students choose to live on campus in graduate housing. However, there are also many students who prefer to live off-campus, in accommodations not contracted with Stanford housing, in the surrounding Bay Area. Graduate students are guaranteed campus housing their first year.
The Graduate Housing Lottery
The Graduate Housing Lottery is the process by which new and continuing graduate students, as well as non-matriculated students such as post-docs, apply for 2022-23 and summer 2022 housing. Students will have the opportunity to rank their desired housing options and form groups. Housing is available for single students, couples, and families.
- The Graduate Housing Lottery Website - Includes information about housing options and the Graduate Housing Lottery
- Housing lottery explained
- Frequently Asked Questions - Includes common questions and answers about The Graduate Housing Lottery
- 2020-21 Graduate Housing Brochure
- Other campus housing options: Community Housing
The campus housing application is available via Axess in April:
- Go to the Student drop-down menu and select Housing and Dining
- Select Apply for Housing
- Follow the instructions to submit your application
R&DE Student Housing Assignments will be hosting a series of webinars so students can learn more about the Graduate Housing Lottery
- April 28 from 4-5 p.m. - Webinar Link
- March 30: Application portal opens.
- May 5: Applications due for summer 2022 and 2022-23
- May 21: Assignments announced for summer 2022 and 2022-23
What modes of transportation do students use to get around Stanford and the Bay Area?
As on most college campuses, Stanford students rely predominantly on a bike to get around. For those without access to a car, Caltrain, VTA or SamTrans provide more than adequately fulfill transportation needs up and down the peninsula (including airport shuttles). In addition, Stanford's free Marguerite shuttle service provides access to the campus to/from surrounding cities (Menlo Park, Palo Alto, parts of Redwood City) and to and from the Caltrain stations in Menlo Park and Palo Alto. Bay Area commute-traffic congestion rivals that of other major cities, which means driving on the peninsula to Stanford is impacted during peak hours.
If I decide to live off-campus, am I eligible for subsidized public transportation?
Stanford offers discounted or even free transit programs to eligible students: for example, off-campus graduate students can receive a free Caltrain Go Pass, which offers unlimited travel on Caltrain between all zones for the calendar year.
Why do some students take longer to finish their degree programs than others?
Some students choose to take fewer required courses each quarter due to a more taxing course-load or due to outside commitments. They may also want to take other courses outside of the degree's requirements.
How many units do students typically enroll in each quarter?
Minimum units allowed during the academic year is 8 units which is considered full-time enrollment. Most students enroll in 8 units each quarter and many are able to enroll 10 units.
A few students are able to manage 11-15 units each quarter to finish their degree in less time.
How easy is it to enroll in required courses each quarter?
Most students report that they were almost always able to enroll in the courses they needed each quarter. It is recommended that students make themselves available at the time that enrollment opens. (Yes, this may mean logging into Axess the middle of the night.)
Students should contact the instructor if enrollment is closed. Explain that the course is needed for your degree and confirm that you will not be enrolled in a course with a conflicting meeting pattern or final exam. Where possible the instructor will try to accommodate your request.
How accessible are faculty and instructors to speak with outside of class?
In addition to their faculty advisor, many students feel comfortable approaching and speaking with faculty and instructors. Bear in mind, Stanford faculty are often committed to various ongoing research projects; it can be difficult to connect or network with Stanford faculty and researchers without learning about what they do. We suggest attending any of the myriad seminars across campus that are of interest to you; which will open up an unparalleled domain of networking possibilities where you can learn about the diverse world of Stanford research.
What software and computing resources are available to students?
The statistics courses taught by the Department typically require some knowledge of the programming language R. Many courses rely on Python coding.
Does the department offer internship credit?
International students who are employed off-campus are subject to the policies outlined by Bechtel International Center concerning Curricular Practical Training.
In order to be eligible to be hired, international students (F-1) MUST file for CPT in Axess and enroll in the course STATS298 Industrial Research for Statisticians.
Are there seminars open to students?
Yes, the Statistics department runs two seminars: Statistics and Probability. Additionally, many other departments hold seminars that are open to students of all disciplines:
Stanford student groups that may be of interest:
How can I get involved in Stanford's student organizations?
- For Leadership lunches to the student activities fair, check out Stanford's SAL hub.
- Engineering student organizations
- Haas Center for Public Service has links to various opportunities for civic opportunities.
- Interested in art, design, music or the performing arts? Find your niche within Stanford Arts Groups.
What academic resources does Stanford offer Masters students?
There are many resources available across Stanford. The ones that Masters students most often take advantage of are the workshops and career fairs sponsored by BEAM and similar events offered by the School of Engineering's Xtend Career Forum for those in the Data Science program.
- Graduate Life Office hosts a New Graduate Student Orientation (NGSO) Week
- Connect with GradConnect to view all NGSO events.
- Vice Provost for Graduate Education (VPGE) hosts a variety of workshops and seminars:
- Academic accessibility office: Office of Accessible Education
Notification/Obligation to Read Email
For many University communications, email to a student's Stanford email account is the official form of notification to the student, and emails sent by University officials to such email addresses will be presumed to have been received and read by the student. Emails and forms delivered through a SUNet account by a student to the University may likewise constitute formal communication, with the use of this password-protected account constituting the student's electronic signature. Read the entire policy pertaining to University Communication with Students.
Summer quarter distance-learning enrollment option (NDO student)
Master’s degree students who will matriculate autumn quarter (2022-23) have the option to take statistics courses online via Stanford Center for Professional Development before arriving on campus. Registration and enrollment is administered through SCPD (NDO student status).
Matriculation will proceed as usual with autumn quarter start.
If you have any questions about course placement for summer quarter, please email Caroline Gates (cgates [at] stanford.edu), your Student Services Officer in Statistics.
- Enrollment in summer courses via SCPD does not require you to be on campus.
- International student visas will be processed over summer with a start date in September.
- CS dept policy: Students are obligated to enroll in the maximum unit for the CS course as a NDO student.
Summer 2022 tuition: $1352/unit (SCPD)
Prior to Graduate Admissions matriculating your student record for autumn, Statistics and Data Science students may enroll in one or two courses online:
- STATS 116 Theory of Probability (4 units)
- STATS 217 Introduction to Stochastic Processes I (3 units)
- STATS 202 Data Mining and Analysis (3 units)
- CS 106A Programming Methodology (5 units)
- The Art and Science of Java by Eric Roberts
- CS 106B Programming Abstractions (5 units)
- Programming Abstractions in C by Eric Roberts