The Ph.D. Program in Statistics
At Carnegie Mellon University, the program of study leading to the
degree of Doctor of Philosophy in Statistics seeks to strike a balance
between theoretical and applied Statistics. Your actual course of
study may be arranged according to your individual interests and
background. The Ph.D. program prepares you for university teaching
and research careers, and for industrial and governmental positions
involving research in new statistical methods. Two to three years beyond the Master's degree are usually needed to complete
all requirements for the Ph.D. degree.
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Preparation for the Ph.D. Program
Although the Ph.D. program formally begins
in the Fall Semester following the Master's program, most students intending to continue in the Ph.D. program typically take
several of the following courses as electives in their final
year in the M.S. program:
- Real Analysis and Lebesgue Integration (Summer or Fall)
- 36-753: Advanced Probability I (Fall)
- 36-754: Advanced Probability II (Spring)
- 36-755: Advanced Statistics I (Spring)
- 36-757: Advanced Data Analysis (Spring)
Preparation in Real Analysis and Lebesgue Integration is helpful
in getting the most out of the Ph.D. coursework in Statistics
and Probability. We typically offer an informal summer course which
covers this material.
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Roberto Carta and Dan Cork discuss a point in ADA with Prof. Kathryn
Roeder.
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Advanced Probability is a rigorous treatment of probability and
stochastic processes.
Advanced Statistics is a rigorous treatment of statistical
inference and decision theory. Both advanced probability and advanced
statistics are taught at the same mathematical
level as Real Analysis and Lebesgue Integration.
Advanced Data Analysis (ADA) is a
Ph.D. level seminar on advanced methods in statistics, including
computationally intensive smoothing, classification, variable
selection and simulation techniques. Most students take the ADA
seminar during the spring of their final M.S. year or the spring of
their first Ph.D. year.
First Year of the Ph.D. Program
The first Ph.D. year usually consists of coursework in the
advanced theory of Probability and Statistics, and Reading and
Research aimed at finding a dissertation topic and dissertation
advisor. Written Ph.D. qualifying exams follow completion of
the theory courses in Probability and Statistics.
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Three Typical Course Schedules in the First Year of the Ph.D.
Program. See also the MS program. The core Ph.D. courses are indicated
in green. |
| Plan |
Fall Semester |
Spring Semester |
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| A |
Reading and Research; or
36-753: Advanced Probability I |
Reading and Research: or
36-754: Advanced Probability II |
| 36-756: Advanced Statistics II |
Elective |
| ADA Project |
Reading and Research |
|
| B |
36-753: Advanced Probability I |
36-754: Advanced Probability II |
| 36-756: Advanced Statistics II |
Two Half-Semester Methods Courses (*) |
| ADA Project |
Reading and Research |
|
| C |
36-753: Advanced Probability I |
36-754: Advanced Probability II |
| 36-756: Advanced Statistics II |
Two Half-Semester Methods Courses (*) |
| Two Half-Semester Methods Courses (*) |
36-757: Advanced Data Analysis (**) |
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| (*) See the description of the M.S.
in Statistics for a description of these methods courses.
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| (**) These students complete the ADA project in the Fall
of their second Ph.D. year.
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ADA Project
During the ADA seminar (36-757), you work with the seminar
instructor to identify an ADA project for yourself.
The ADA project is an extended project in applied statistics, done
in collaboration with an investigator from outside the Department,
under the guidance of a faculty committee, culminating in a
publishable report that is presented orally and in writing during
the Fall semester following the ADA seminar.
Experience in statistical practice and collaborative research is
gained from participation in workshop courses, in the ADA project, and
in independent projects with individual faculty members.
Second and Third Years of the Ph.D. Program
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Graduate students Alix Gitelman, Ashish Sanil and Xu Fan in the
Ph.D. seminar with Profs. Jay Kadane (second from left) and Pantelis
Vlachos (nearest camera).
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Reading and
research leading toward the selection of a Ph.D. dissertation advisor
and the development of a dissertation topic usually begins in the
Fall of the first Ph.D. year and is carried on more intensively
during the following Spring, Summer and Fall. An oral dissertation proposal
precedes work on the Ph.D. dissertation itself.
The second and third Ph.D. years are devoted mainly to dissertation
research. In addition, you continue to participate in the
intellectual culture of the department by joining seminar and workshop
courses, assisting with teaching, and aiding in research projects.
Candidates for the degree of Doctor of Philosophy (Ph.D.) in
Statistics must demonstrate proficiency at the M.S. and Ph.D. levels
by passing the M.S. and Ph.D. comprehensive/qualifying exams, and by
successfully completing and presenting the ADA project. Of course the
most important requirement is that you successfully propose, write and
defend an acceptable Ph.D. dissertation.
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Next Topics, Joint Ph.D. Program in Statistics and Public
Policy,
The Ph.D. in Statistics with an Emphasis on
a Substantive Field
