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The use of
statistical methodology is highly relevant for any person carrying
research where data has been collected. Thus, Statistics is frequently
used to validate research in fields such as engineering, biology,
psychology, medicine, agriculture, etc.
The main goal of this graduate program is to prepare students that
will be able to apply statistical techniques to other fields in a correct
way. The emphasis of the program is more in applied statistics than in
theoretical statistics and probability. However, theoretical
foundations of statistics and probability is considered in most of
the courses. Students wishing to pursue a doctoral degree in statistics
are encouraged to take more courses in theory of statistics, probability
and stochastic processes.
Applicants
should have an undergraduate degree in Mathematics or its equivalent.
Candidates are expected to have approved undergraduate courses in Linear
Algebra and Multivariate Calculus. The approval of at least an
undergraduate course in Statistics is also required. Knowledge of
computer programming is highly desirable.
In addition
to the requirements of the Office of Graduate Studies, the Master of
Science degree in Mathematics, Statistics track with Thesis, option I,
requires:
1.
9 credits in core courses
·
MATE 6261,
Real Analysis I
·
ESMA 6600,
Probability Theory
·
ESMA 6661,
Theory of Statistics I
2.
9 credits from the following (area of
specialization)
·
ESMA 5015,
Stochastic Simulations
·
ESMA 6205,
Applied Regression
·
ESMA 6305,
Statistical Methods
·
ESMA 6607, Advanced
Sampling Theory
·
ESMA 6616,
Linear Models
·
ESMA 6660,
Bio-statistical Analysis
·
ESMA 6662,
Theory of Statistics II
·
ESMA 6665,
Computational Statistics
·
ESMA 6787,
Experimental Design
·
ESMA 6835,
Topics in Statistics I
·
ESMA 6836,
Topics in Statistics II
3.
6 credits outside the area of specialization or
major. The requirement of a
minimum of two out-of-discipline courses is to ensure cross-disciplinary
breadth. The courses must be related to mathematics and should be chosen
in a coherent way. These should be of level 5000 or higher. It is
recommended that student choose these courses with the help of their
advisor.
·
6000 or
5000 level courses not listed in the major, or
·
6000 or
5000 level courses outside the math department
4.
2 credits in Seminar
·
MATE 6991,
Seminar (1
credit)
·
MATE 6992,
Seminar (1
credit)
5.
6 credits in Thesis
·
MATE
6999
(6 credits)
In addition, the candidate must
pass one qualifying
exam from
·
Probabiltiy and Statistical Methods
·
Theoretical
Statistics and Regression
Option II: project option: the course and examination
requirements are similar to Option I, however the
6 Thesis credits must be replaced by 6 Project credits. An oral
examination on the project is also required.
Option III, no project, no thesis: the student should approve a
minimum of 36 course credits:
·
A minimum
of 27 credits at graduate level
·
A minimum
of 21 credits in the area of specialization
·
A minimum
of 6 credits in courses related to, nut outside the area of
specialization.
In addition the student must pass two (2) exams from
the above list.
List of faculty associated with this track and their research
areas
Edgar Acuña, ( Data analysis, Computational and Statistical Learning)
Edgardo Lorenzo, (Applied
statistics, Nonparametric statistics, Survival analysis)
Julio C. Quintana, (Applied
statistics, Sampling, Regression)
Wolfgang Rolke, (Mathematical statistics, Probability theory)
Tokuji Saito, (Applied
statistics)
Damaris Santana, (Applied
statistics)
Robert W. Smith, (Statistics,
Stochastic processes)
Pedro Vasquez, (Time Series,
Stochastic processes)
Wei Wei, (Biostatistics,
Statistical Analysis of microbial community data)
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