The Master of Science in Statistics program is designed for students who wish to pursue careers as practicing statisticians in industry, government, or academia. It is also designed to prepare students for community college teaching or entry into a Ph.D. in Statistics degree program. The degree is also valuable for people working in other fields who need mastery of a broad range of statistical methods.
Admission
Program prerequisites
Transcript(s) must show successful completion of at least the following undergraduate courses: Advanced Statistical Methods, Introductory Analysis/Advanced Calculus, Linear Algebra, and Differential Equations. These courses are equivalent to PSU's Stat 452 or higher, Mth 311, Mth 261, and Mth 256.
In addition to program prerequisites, applicants must meet the university's minimum admission requirements including English language proficiency.
Degree Requirements
Candidates must complete an approved 45-credit program, which includes at least 30 core credits in courses with the Stat prefix. In addition, students must satisfy Other Requirements (see below).
A student must have a minimum 3.00 GPA on the courses applied to the program of study, as well as a minimum 3.00 GPA in all graduate-level courses taken at PSU. Although grades of C+, C, and C- are below the graduate standard, they may be counted as credit toward a master’s degree with the specific written approval of the department if taken at PSU after the term of formal admission to the graduate program.
Students are responsible for knowing University-level graduate policies and procedures for obtaining the degree. These policies and procedures are in the Graduate School section of the PSU Bulletin. Several of the most frequently asked about University-level graduate policies and procedures can also be found on the Graduate School website.
Core requirements (30 credits)
The 30 core credits must include courses distributed as follows:
Two 9-credit sequences:
| Stat 561 | Mathematical Statistics I | 3 |
| Stat 562 | Mathematical Statistics II | 3 |
| Stat 563 | Mathematical Statistics III | 3 |
| | And | |
| Stat 564 | Applied Regression Analysis | 3 |
| Stat 565 | Experimental Design: Theory and Methods I | 3 |
| Stat 566 | Experimental Design: Theory and Methods II | 3 |
One 9-credit sequence chosen from
| Stat 661 | Advanced Mathematical Statistics I | 3 |
| Stat 662 | Advanced Mathematical Statistics II | 3 |
| Stat 663 | Advanced Mathematical Statistics III | 3 |
| | or | |
| Stat 664 | Theory of Linear Models I | 3 |
| Stat 665 | Theory of Linear Models II | 3 |
| Stat 666 | Theory of Linear Models III | 3 |
| | or | |
| Mth 667 | Stochastic Processes and Probability Theory I | 3 |
| Mth 668 | Stochastic Processes and Probability Theory II | 3 |
| Mth 669 | Stochastic Processes and Probability Theory III | 3 |
| | or | |
| Stat 671 | Statistical Learning I | 3 |
| Stat 672 | Statistical Learning II | 3 |
| Stat 673 | Statistical Learning III | 3 |
Topics in Statistical Consulting (3 credits)
Electives (15 credits)
A total of 15 elective credit hours must be completed. The following list of courses is pre-approved for elective credit.
| Stat 501 | Statistical Literature and Problems | 3 |
| Stat 571 | Applied Multivariate Statistical Analysis | 3 |
| Stat 572 | Bayesian Statistics | 3 |
| Stat 573 | Computer Intensive Methods in Statistics | 3 |
| Stat 576 | Sampling Theory and Methods | 3 |
| Stat 577 | Categorical Data Analysis | 4 |
| Stat 578 | Survival Analysis | 3 |
| Stat 580 | Nonparametric Methods | 3 |
| Stat 661 | Advanced Mathematical Statistics I | 3 |
| Stat 662 | Advanced Mathematical Statistics II | 3 |
| Stat 663 | Advanced Mathematical Statistics III | 3 |
| Stat 664 | Theory of Linear Models I | 3 |
| Stat 665 | Theory of Linear Models II | 3 |
| Stat 666 | Theory of Linear Models III | 3 |
| Stat 567 | Applied Probability I | 3 |
| Stat 568 | Applied Probability II | 3 |
| Mth 667 | Stochastic Processes and Probability Theory I | 3 |
| Mth 668 | Stochastic Processes and Probability Theory II | 3 |
| Mth 669 | Stochastic Processes and Probability Theory III | 3 |
| Stat 671 | Statistical Learning I | 3 |
| Stat 672 | Statistical Learning II | 3 |
| Stat 673 | Statistical Learning III | 3 |
| CS 545 | Machine Learning | 3 |
| Ec 572 | Time Series Analysis and Forecasts | 4 |
| USP 655 | Advanced Data Analysis: Structural Equation Modeling | 3 |
Other statistically oriented courses outside the Department and other mathematics courses may be substituted, but must be approved as electives by the statistics graduate program adviser. "Approved as elective" means that it is approved inside the 15 elective credit hours but not inside the 30 statistical credit hour core requirements. A course or sequence cannot be counted both within the 30-hour core and as an elective course or sequence.
Other Requirements
The student must satisfy one of the following options:
Option A: Pass both Master’s examinations.
Option B: Pass the Mathematical Statistics exam and successfully complete Stat 501.
Option C: Pass the Applied Statistics exam and successfully complete Stat 501.
MS Examinations
There are two examinations:
(i) The Mathematical Statistics Exam which covers Stat 561, Stat 562 and Stat 563
(ii) The Applied Statistics Exam which includes the core topics covered in Stat 564, Stat 565, and Stat 566.
Examinations are offered twice a year, the week prior to the start of fall term and during the first week of spring term. Students may take any examination at most two times. Students must be registered for and complete at least one graduate credit during the term(s) in which they take an exam. For complete details see the full MS Exam Policy (https://www.pdx.edu/math/ms-exam-policy).
Grading Policy for the MS Exam in Applied Statistics
The Applied Statistics Exam is comprised of two components:
-
Applied regression analysis
-
Design of experiments and ANOVA
Both components consist of a written exam portion and a separate, in-laboratory, statistical computing applications portion. The Applied Statistics Exam may be repeated once; that is, a maximum of two tries is permitted.
A Pass (P) or Fail (F) is given on each component.
-
Two P's equal a PASS on the exam.
-
One P equals a CONDITIONAL PASS on the exam. The Examination Committee will inform the student of the requirements for removal of the Conditional.
-
Two F's equal a FAIL on the exam. In this case the entire exam must be retaken.
Stat 501 Statistical literature and problems
In this course, a student works under the supervision of a faculty member in an area of probability and statistics in which the student has acquired the background needed to read current probability and statistical literature, prepare a research paper, and present this research in a colloquium. Requirements for the course are contained in the handout: Guidelines and Deadlines for Stat 501 Statistical Literature and Problems.
Planning an MS degree program
The Course Projection Guide (CPG) lists the projected future 600-level course offerings. These projections enable students to plan programs that include any necessary 500-level prerequisites. Students also need to plan a program that will prepare them to pass the two MS examinations. Students entering the program with core courses Stat 561, Stat 562, Stat 563 and Stat 564, Stat 565, Stat 566 successfully completed and considering future pursuit of the Ph.D. are encouraged to take Mth 511, Mth 512 and in addition to the required 600 level sequence, at least one additional sequence from among Stat 661, Stat 662, Stat 663, Stat 664, Stat 665, Stat 666, and Mth 667, Mth 668, Mth 669. All students are urged to meet with the graduate program adviser regarding degree requirements and for help with program planning.