Undergraduate
Courses.We have developed several undergraduate courses aimed at attracting a
wider variety of quantitatively oriented students to interdisciplinary
research in statistics.
36-202*: Statistical Methods.
36-303:
Sampling, Surveys and Society.
36-310:
Fundamentals of Statistical Modeling.
36-315:
Statistical Graphics and Visualization.
36-350:
Data Mining.
36-401/402:
Applied Regression Analysis / Advanced Data Analysis.
36-625/626*: Probability and Mathematical
Statistics.
In
particular, 36-202 is a new course developed from scratch to provide a
bridge from introductory statistics (36-201) to
more-demanding research methods courses in economics, psychology, the social
sciences, and statistics. The one-semester course 36-310 may be
substituted for the usual two-semester undergraduate calculus-based prob/stat
sequence. Both courses allow entree into statistics for many students who
otherwise would not have time in their
schedules.
For
more advanced undergraduates and beginning graduate students, 36-625/626
offers a survey of probability and statistics with an eye toward material
that is directly applicable in modern statistical
practice.
Graduate Courses
MS-level Courses. Students may complete a MS degree in
statistics in just one
year by completing the
following courses, redesigned as part of this VIGRE grant
effort.
In
particular we have adjusted the core graduate courses marked with an
asterisk below, to provide students with
methodology and communication skills more quickly, so that they can
begin
research projects as soon as possible:
- 36-701*: Perspectives on Statistical Practice and
Pedagogy.
- 36-703:
Intermediate Probability.
- 36-705:
Intermediate Statistics.
- 36-707*:
Applied Regression.
- 36-708:
Linear Models.
- 36-711*:
Statistical Computing.
- 36-724*:
Applied Bayesian and Computational Statistics.
- 36-726*:
Statistical Practice.
Students who need more time to obtain or practice basic mathematics
skills needed for these courses can also
stretch the program over two years, to make room for more mathematics
and
related courses.
Several optional half-semester methodology courses are also
available, for students who need particular
methodology to support their program of research:
- 36-713: Nonparametric Methods.
- 36-720:
Discrete Multivariate Analysis.
- 36-722:
Continuous Multivariate Analysis.
- 36-728:
Time Series.
PhD-level Courses. PhD students’ coursework has been reduced
to
- 36-752*: Advanced Probability Overview.
- 36-755:
Advanced Statistics I.
- 36-757/758:
Advanced Data Analysis.
36-752 replaces the usual two-semester advanced probability
sequence usually taught to PhD level students. A
second semester each of Advanced Probability and Advanced Statistics is
available
for students who wish a deeper understanding of these topics; or, with
faculty approval, several upper-level courses in a substantive field that the student
will be working in, may be substituted for these
two courses.
All
of the changes above are designed to minimize the time-to-real research
for students capable of quickly moving into
research-level work. At the same time we must make accommodations
for
students who are less ready, because of mathematical preparation or for
other reasons, to move quickly into research.
Thus our program can be stretched out for an additional year, especially
at the MS
and PhD levels, for students who need additional time to prepare or
practice basic skills in mathematics and/or
other prerequisites.
