Master of Science in Statistics
The Master of Science (M.S.) degree in Statistics provides
advanced training in mathematical and applied statistics, exposure to
statistics in a consulting or collaborative research environment and specialized coursework in
a number of areas of emphasis. The program is intended to prepare students for
careers as practicing statisticians, to provide enhanced research expertise for students pursuing
advanced degrees in other fields, and to strengthen the mathematical and statistical training
of students preparing for PhD studies in statistics or a related field. The M.S. degree
requires 32-36 hours (8 or 9 courses) beyond the prerequisites. There is no thesis requirement
for this degree. The entire program must be approved by the Graduate Advisor
before a degree can be awarded.
MATH 415 - Applied Linear Algebra
MATH 241 - Calculus III (Calculus through vector calculus)
STAT 400 - Statistics and Probability I
A. Four required courses (12 or 16 hours)
1. STAT 410 - Statistics and Probability II. This requirement can be waived if the student
has already taken the course, or a course equivalent to it at another institution. (4 hours)
2. STAT 425 - Applied Regression and Design (4 hours)
3. One of the following (4 hours)
STAT 424 - Analysis of Variance
STAT 426 - Sampling and Categorical Data
STAT 429 - Time Series Analysis
STAT 430 - Topics in Statistics
4. STAT 510 - Mathematical Statistics (4 hours)
B. Five elective courses (20 hours)
At least 8 hours must be from the following
list, and any course used to satisfy A.3 may not also be used to satisfy B.
Up to 12 hours may be from other units on campus, subject to the approval of the
Graduate Advisor. All courses below are four hours except STAT 590 and STAT 593,
which have a variable number of hours.
STAT 424 - Analysis of Variance
STAT 426 - Sampling and Categorical Data
STAT 427 - Statistical Consulting
STAT 428 - Statistical Computing
STAT 429 - Time Series Analysis
STAT 430 - Topics in Applied Statistics
STAT 432 - Topics in Biostatistics
STAT 440 - Data Management
STAT 448 - Advanced Data Analysis
STAT 458 - Math Modeling in Life Sciences
STAT 466 - Image Analysis
STAT 511 - Mathematical Statistics II
STAT 525 - Computational Statistics
STAT 530 - Bioinformatics
STAT 542 - Statistical Learning
STAT 553 - Probability and Measure I
STAT 554 - Probability and Measure II
STAT 555 - Applied Stochastic Processes
STAT 563 - Information Theory
STAT 571 - Multivariate Analysis
STAT 575 - Large Sample Theory
STAT 578 - Topics in Statistics
STAT 587 - Hierarchical Linear Models
STAT 588 - Covariance Structures and Factor Models
STAT 590 - Reading Course (at most four hours total for this course)
STAT 593 - Internship (at most four hours total for this course)
C. Experience with statistical practice in an interdisciplinary
environment
This requirement is satisfied by any one of the following:
1. Completing STAT 427 - Statistical Consulting; or
2. Completing an approved internship (STAT 593 - Internship); or
3. For students previously or concurrently admitted to another graduate program
at the University of Illinois that uses statistics, completing at least 12 graduate
hours (3 courses) in that program. The 12 hours would not count toward the
M.S. degree in Statistics.
If STAT 427 or STAT 593 is taken to meet this requirement, those hours can
count toward the 20 described in B.
D. Graduate level course requirement
At least 12 hours (3 courses) must be taken at the 500 level.
MS applicants interested in careers in the financial and insurance industries are encouraged to apply
for the State Farm Research Center's
Modeling and Analytics Graduate Network (MAGNet) program.
Successful applicants for this competitive program will be able to start their professional careers with tuition support
for the MS degree and concurrent employment at the
State Farm Research and Development Center,
which is located
in the University of Illinois Research Park.
Virtually every industry and major organization is becoming
increasingly data intensive in planning processes and business
decision making. There is a strong and increasing demand nationwide
for people with training in statistics, data mining, predictive
modeling and analysis with complex datasets for problems in risk
analysis and demand forecasting.
A good source of general career information
is the American Statistical Association
Careers Center. For further information visit the
ASA web site or write to:
American Statistical Association
1429 Duke Street
Alexandria, VA 22314-3402
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