Search | Directories | Reference Tools
UW Home > Discover UW > Student Guide > Degree Programs 


Department Overview

B309 Padelford

Probability provides the conceptual foundation and mathematical language for the logic of uncertainty and induction. Statistics is concerned with procedures for the acquisition, management, exploration, and use of information in order to learn from experience in situations of uncertainty and to make decisions under risk. Statistical practice includes design of experiments and of sampling surveys; exploration, summarization, and display of observational data; drawing inferences, and assessing their uncertainty; and building mathematical models for systems with stochastic components.

Instruction is enriched through academic contacts with the Foster School of Business; the College of Engineering; the departments of Applied Mathematics, Atmospheric Sciences, Biology, Cardiology, Computer Science, Earth and Space Sciences, Economics, Genetics, Mathematics, Psychology, Radiology, and Sociology; the Quantitative Ecology and Resource Management program; the Center for Statistics and the Social Sciences; the Applied Physics Laboratory; the Applied Statistics Division of the Boeing Company; Microsoft Research; and Insightful Corporation. The department has an especially close relationship with the Department of Biostatistics; for example, the two departments are jointly developing new curricula in statistical genetics.

Undergraduate Program

B309 Padelford, Box 354322
(206) 543-8296

The Department of Statistics offers the following programs of study:

  • The Bachelor of Science degree with a major in statistics. Provides training in theoretical foundations of statistics, statistical modeling and methodology, and applied data analysis. Also offered is a Data Science option that in addition emphasizes computation and data management.
  • In conjunction with the departments of Applied Mathematics, Computer Science and Engineering, and Mathematics, the Bachelor of Science degree with a major in applied and computational mathematical sciences (ACMS).
  • A minor in statistics

Bachelor of Science

Suggested First-and Second-Year College Courses: MATH 324; one of CSE 142 or CSE 160; STAT 311. Additional courses in the sciences and quantitative methods add strength to this major.

Department Admission Requirements

Admission is competitive. Completion of minimum requirements described below does not guarantee admission. All applicants have the right to petition and appeal the departmentís admission decision. Applications are considered once each academic year and are due on the third Friday in April.

Minimum course requirements for admission applications as follows:

  1. MATH 124, MATH 125, MATH 126 (or MATH 134, MATH 135, MATH 136)
  2. One of STAT 311 (highly recommended), STAT 390, or an approved substitute. See website for approved list.
  3. MATH 324; one of CSE 142 or CSE 160
  4. Factors in the admission decision include but are not limited to academic performance as measured by GPA in courses listed above and any additional advanced quantitative courses presented for application consideration.
  5. Admission is competitive. Successful applicants typically have a cumulative GPA higher than 3.00 in courses listed above under course requirements, with no individual course grade lower than 2.5.

Major Requirements

Minimum 65 credits

  1. Mathematics (25-30 credits): either MATH 124, MATH 125, MATH 126, MATH 300, MATH 307, MATH 308, MATH 324, and MATH 327; or the Honors sequence MATH 134, MATH 135, MATH 136, MATH 334, and MATH 335.
  2. Computing (7-9 credits): For the major in statistics: CSE 142 or CSE 160; either STAT 302 (recommended), CSE 143, or an approved substitute. For the data science option: 9 credits from the following: CSE 142, CSE 143, STAT 302, CSE 160, CSE 163
  3. Statistics (24-27 credits): STAT 311 (highly recommended), or STAT 390, or an approved substitute (STAT 220, STAT 221, or STAT 301 which is seldom allowed); either STAT 340 (highly recommended) or both STAT 394/MATH 394 and STAT 395/MATH 395. (Note that both STAT 394/MATH 394 and STAT 395/MATH 395 are required to replace STAT 340 as a prerequisite for STAT 341.) STAT 341, STAT 342, STAT 421, STAT 423. (STAT 342 is required for enrollment in STAT 421 or STAT 423 by a statistics major; STAT 390 is not sufficient for a statistics major.)
  4. Electives: For the major in statistics: at least three courses for a minimum total of 9 credits. Elective choices require prior approval of the Statistics undergraduate adviser. For the data science option: two courses from STAT 435, STAT 403, STAT 425; CSE 491, SOC 225, or another 1-credit seminar covering privacy, security, ethics, and societal implications of data science; CSE 414 or INFO 340; one of the following: HCDE 411, INFO 474, CSE 412, CSE 442
  5. Minimum 2.0 grade in all courses used to satisfy major requirements.
  6. Minimum 2.50 cumulative GPA for all courses used to satisfy major requirements.

A "Majors Factsheet" is available from the Statistics department.


Minor Requirements: 26 credits, as follows:

  1. MATH 126 or MATH 136 (5 credits)
  2. STAT 302, STAT 390/MATH 390, STAT 394/MATH 394, STAT 395/MATH 395 (13 credits)
  3. either STAT 425/BIOST 425 or STAT 396/MATH 396 (3 credits)
  4. Minimum 5 credits of approved electives. See adviser for approved list.
  5. Minimum grade of 2.0 in each course used to satisfy minor requirements
  6. Maximum 5 credits may be applied to a studentís major.
  7. At least 20 credits must be taken through the UW.

Student Outcomes and Opportunities

  • Learning Objectives and Expected Outcomes: Statistics emphasizes decision making in the face of uncertainty. Tools developed by the major include probability theory, mathematical statistics, experience with data analysis, and use of statistical tools via the computer. Graduates have pursued careers in actuarial science, financial planning, drug development, statistical consulting, teaching, public health, military science, aerospace, computer technology, and forest resources.
  • Instructional and Research Facilities: Computer workstations are available on a drop-in basis through the College of Arts & Sciences Instructional Computing Laboratory. Tutoring in a set of introductory statistics courses is currently available at the Statistics Tutor and Study Center.
  • Honors Options Available: For Interdisciplinary Honors, see University Honors Program.
  • Research, Internships, and Service Learning: A special seminar series for undergraduates is offered in conjunction with the ACMS program.
  • Department Scholarships: None offered.
  • Student Organizations/Associations: The Actuary Club at the University of Washington

Graduate Programs

Graduate Program Coordinator
B309 Padelford, Box 354322
(206) 685-7306

The graduate programs emphasize both the theory and application of statistics, including probability theory, mathematical statistics, data analysis, statistical computing, and scientific applications. Computing facilities in the department reflect the department's expertise in the field of statistical computing. An ongoing statistical consulting program provides students practical experience in using statistics and in communicating with clients. Under faculty supervision, participants in the program assist members of the University community in applying statistical methodology. The department offers master of science and doctor of philosophy degrees.

Admission Requirements

  1. Background in mathematics, statistics, or a quantitative field, with 30 or more quarter credits in mathematics and statistics, to include a year of advanced (second-year) calculus, one course in linear algebra, and one course in probability theory
  2. Graduate Record Examination scores (the Advanced Mathematics subject test is encouraged but not required)
  3. Three letters of recommendation from appropriate former or current faculty

Master of Science

Degree Requirements (36-49 credits)

Part-time/Concurrent Track (minimum 36 credits)

At least twelve approved courses numbered 400 or above (minimum 36 credits); of these, at least six courses numbered in the 500 series (exclusive of STAT 512, STAT 513) Ė minimum18 credits or more, representing a coherent theme. Approved proficiency in statistical computing. Satisfactory participation in statistical consulting and the departmental seminar. Passage of an appropriate final master's examination or successful completion of a master's thesis which can count as up to three courses worth 9 credits but cannot replace any of the six courses in the 500 series mentioned above. All programs must be approved by the departmental Graduate Program Coordinator.

Advanced Methods and Data Analysis Track (minimum 49 credits)

  1. Core Courses: STAT 502, STAT 504, STAT 512, STAT 513, STAT 534, STAT 536, STAT 570, STAT 571
  2. Statistics capstone data analysis: STAT 528
  3. Satisfactory participation in at least one quarter of the departmental seminar
  4. Passage of the first year MS theory examination

Doctor of Philosophy

Degree Requirements

Minimum 90 credits, to include:

  1. Training in statistics and related sciences
  2. General examinations of basic graduate-level knowledge in statistics and probability (including two preliminary examinations)
  3. MATH 574, MATH 575, MATH 576
  4. Three approved core-course sequences chosen from STAT 570, STAT 571, STAT 572; STAT 581, STAT 582, STAT 583; STAT 521, STAT 522, STAT 523; STAT 534, STAT 535, STAT 538; and STAT 516, STAT 517, STAT 518. (In some circumstances, other graduate-level mathematical science courses may be used as a substitute.)
  5. Statistical consulting (typically STAT 598 and STAT 599)
  6. Proficiency in computing
  7. STAT 590 (1 credit per quarter)
  8. Final examination

Graduation requirements for PhD tracks in statistical genetics and statistics in the social sciences may replace or be in addition to some of the requirements listed above.

Financial Aid

The department annually awards a limited number of teaching and research assistantships and fellowships for the support of new and continuing graduate students on the basis of academic promise.