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Master of Science in Applied Statistics
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.
Many of our part-time students are full-time professionals
who want to learn state-of-the art statistical techniques
to enhance their careers and their value to their companies.
Other part-time students are full-time professionals who want
to change careers and become statistical consultants for their
companies. MS students who do not fit the full-time professional
category typically attend RIT on a full-time basis and use
the degree to gain employment as statisticians.
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.
- Seven core courses
0307-742 Statistical Computing
0307-717 Design and Analysis of Experiments I
0307-818 Design and Analysis 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.
- Four required courses form a career option
There are three standard career options, each of which is
designed to allow 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
0307-803 Design and Analysis of Experiments III
0307-856 Interpretation of Data
0307-862 Reliability Statistics I
0307-883 Quality Engineering by Design
Statistical Theory and Methods
0307-824 Probability Models
0307-830 Multivariate-Analysis Theory
0307-831 Multivariate-Analysis Applications
0307-862 Reliability Statistics I
Advisers can help identify an appropriate career option
and develop a total program structured to meet individual
professional objectives.
- 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. Students
who desire a more rigor focus, for example, may consider
courses
from the Mathematics and Statistics department. 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.
- 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.
- Statistics seminar
Full-time 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.
- 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 develop their writing,
speaking, presentation, and computer skills further as they
progress through the program.
- 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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