RIT is moving to semesters in Fall 2013. Our courses—and much more—are changing.

Master of Science in Applied Statistics, entering students Fall 2013.

This master's degree is also available in our online-learning format.

The MS degree, which requires 45 credits (equivalent to 15 courses), is available to both part-time or full-time students on RIT's campus or to part-time students through online learning. The online learning option makes this degree especially appealing to students who are not able to attend classes on the RIT campus. Students working toward their baccalaureate degree in certain departments at RIT are eligible to apply for a joint BS/MS program. Cooperative education options are also available.

The MS degree is primarily intended for those students who do not wish to pursue a degree beyond the MS. However, a number of our students have continued their studies, and are either working on, or have attained, a Ph.D.

Admission
Admission to the MS degree program will be granted to qualified holders of a baccalaureate degree from an accredited college or university who have an acceptable GPA and mathematics credits, including acceptable grades in a two-semester (or three-quarter) sequence of university-level calculus, and acceptable probability and statistics college credits, equivalent to 0307-711, 712 and 714. An undergraduate GPA of 3.0 is strongly recommended. Applicants who fail to meet these requirements may be admitted on a contingency basis -- they will be required to complete these prerequisites prior to matriculation in the graduate program.

Entrance exams are not required. However, international students whose native language is not English must have a TOEFL score of at least 550 (paper-based) or 213 (computer-based). Full-time students must begin their full-time studies in the fall quarter. Part-time students may begin their studies based on our schedule of courses.

Requirements, Master of Science

Download Requirements PDF

For the Master of Science in applied statistics the satisfactory completion of the following is required.

1. Seven core courses
   0307-742 Statistical Computing
   0307-801 Design of Experiments I
   0307-802 Design of Experiments II
   0307-821 Theory of Statistics I
   0307-822 Theory of Statistics II
   0307-841 Regression Analysis I
   0307-842 Regression Analysis II
   
   Students, in conjunction with their adviser’s recommendations, should take the core courses early in the program. In any event, they must be taken within the first 30 credit hours of the degree. If this is not possible because of scheduling, they must be taken as soon as possible after the first 30 credit hours. Students should fill out a Plan of Study (MS Word Download) form within the first five weeks after matriculation for these and other courses in the program.
2. Four required courses form a career option
   There are three standard career options, each of which is designed to allow the students to specialize within their career endeavors. A personalized career option is also available. The three standard career options are:
   
   Quality Engineering
   0307-721 Statistical Process Control
   0307-731 Statistical Acceptance Control
   0307-781 Quality Management
   0307-782 Quality Engineering
   
   Industrial Statistics (choose 4)
   0307-803 Design and Analysis of Experiments III
   0307-846 Principles of Data Mining I
   0307-862 Reliability Statistics I
   0307-883 Quality Engineering by Design
   0307-884 Categorical Data Analysis
   
   Statistical Theory and Methods
   0307-824 Probability Models
   0307-830 Multivariate-Analysis Theory
   0307-831 Multivariate-Analysis Applications
   0307-862 Reliability Statistics I
   
   Advisors can help to identify an appropriate career option and to develop a total program structured to meet individual professional objectives.
3. Three electives, Thesis option, or Project option
   Three additional courses are chosen by the student with the help of his or her advisor. These courses are usually department courses but may include (along with the transfer credits explained previously) up to nine credits from other courses that are related to the program and that are consistent with the student’s professional objectives. A student, with adviser approval, may choose to write a research thesis or research project instead of taking the full three electives. Theses are usually for six credits, and projects are usually for three credits.
4. Capstone course
   The capstone course is designed to ensure that students can integrate the knowledge from their other courses to solve more complex statistical problems.
5. Statistics seminar
   Full-time funded students must register for and attend the 0307-895 statistical seminar course in fall, winter, and spring quarters. This is a 0-credit course that is graded on a pass-fail basis.
6. Other requirements
   The MS candidate must attain an overall average program grade of 3.0 (B), with no more than two grades of C in distinct courses, for graduation. A minimum of 24 credits in 800-level courses is required in the degree program. Coursework must be completed within seven years. Contact the department for more details on these requirements.
   
   Students are strongly encouraged to further develop their writing, speaking, presentation, and computer skills as they progress through the program.
7. Application for Graduation
   All students must file an Application for Graduation with the Institute at least three quarters before their planned graduation date. The Program Code for the MS degree is "EQAS". This form should be filled out and mailed to the department at:
   
   Rochester Institute of Technology
   The John D. Hromi Center for Quality and Applied Statistics
   98 Lomb Memorial Dr.
   Rochester, NY 14623-5604
   or faxed to: (585) 475-5959

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