|
THE
MASTER OF SCIENCE (STATISTICS) PROGRAM
The MS Statistics aims to prepare students
for advanced work in the profession as well as provide them with necessary
foundation for high quality PhD for both theoretical and practical aspects.
ADMISSION AND GRADUATION OF STUDENTS
The student will be required to take a
validation examination in the areas of Calculus, Matrix Algebra, and
Introductory Statistics. If the student failed the examination, one or two of
Stat 100, Stat 195, or Stat 117 will be taken during the summer/term prior to
admission to the MS program.
To facilitate monitoring of progress of
students, they will be required to submit a concept paper of possible research
topic as part of the application requirement.
The student will be considered candidate
for graduation upon completion of all required and elective courses with a
weighted average of “2.0” or better and submission and successful defense of a
Thesis.
For the MS Thesis, the student should be
able to demonstrate capability of conducting basic research in statistics. The
work should contribute in the body of knowledge in the statistical science. The
new knowledge generated from the thesis can be derived analytically or
computationally (simulations).
AREAS OF ELECTIVES
The following areas of electives can be
pursued by the MS students.
-
Industrial Statistics
– there is a wide range of applications of statistics in the industry.
Quality assurance, quality improvement, product development, etc. are some
of the areas where statistics can be very useful.
-
Statistical Methods for Market
Research and Business Intelligence - from data
collected through face-to-face interviews, focused group discussions,
product testing, etc., the paradigm of market research is gradually
changing. Data is now generated from actual usage/purchase history of
consumers, cases where streaming data is generated from continuous consumer
activities. While the data collection does not really follow some
probabilistic methods, their volume is huge enough to treat it as
approximating the population. This area incorporates both the ‘traditional’
and modern methods of market research leading towards business
intelligence.
-
Mathematical Statistics
– many statistical theories were developed with the aid of mathematical
tools. Large sample properties, approximations, exact distributions, are
some of the important results of mathematical statistics. This area may
help prepare the students for more advanced work in statistical theory.
-
Computational Statistics
–the emergence of computational statistics was stimulated by the
availability of very large data sets. These data are often generated by
heterogeneous mechanisms, from unknown process, or from non-random
mechanism. The availability of powerful computing facilities and efficient
algorithms simplified the analysis of these data. Oftentimes, the methods
used are iterative in nature, thus, exact sampling distributions are not
mathematically tractable. Computational statistics is a venue where
statistical theory evolves from a dominantly nonparametric framework and
uses computing technology.
-
Risk Assessment Methods
– financial systems are vulnerable to random shocks that can easily topple
old institutions. Many statistical methods can be tailor-fitted to address
the concern of the financial sector, specifically, for risk management. The
area of focus aims to produce students with quantitative skills they can use
in effective risk management especially in the finance sector.
THE MS CURRICULUM
Core Courses
-
Stat 231 Probability Theory
-
Stat 232 Parametric Inference
-
Stat 233 Linear Models
-
Stat 234 Multivariate Analysis
-
Stat 250 Sampling Designs
Other Courses
The elective courses should be taken in one
of the list below:
-
Industrial Statistics:
Stat 210, Stat 211, Stat 224, Stat 241, Stat 243, Stat 244, Stat 245, Stat
246, Stat 266, Stat 270, Stat 271, Stat 272, Stat 273, Stat 276
-
Statistical Methods for Market
Research and Business Intelligence: Stat 210, Stat
211, Stat 225, Stat 226, Stat 241, Stat 243, Stat 247, Stat 266, Stat 267,
Stat 268, Stat 270, Stat 274, Stat 276
-
Social Statistics:
Stat 210, Stat 224, Stat 225, Stat 226, Stat 242, Stat 243, Stat 251, Stat
266, Stat 267, Stat 270, Stat 275, Stat 276, Cognates in Demography
-
Mathematical Statistics:
Stat 211, Stat 226, Stat 235, Stat 240, Stat 241, Stat 249, Stat 252, Stat
261, Stat 262, Stat 263, Stat 264, Stat 265, Stat 267
-
Computational Statistics:
Stat 210, Stat 211, Stat 226, Stat 240, Stat 241, Stat 247, Stat 249, Stat
252, Stat 262, Stat 265, Stat 267, Stat 277
-
Risk Assessment Methods:
Stat 211, Stat 225, Stat 226, Stat 241, Stat 242, Stat 260, Stat 261, Stat
264, Stat 267, Stat 268
Checklist for MS
|
Term |
Course |
Units |
|
Summer |
Stat 117 Mathematics for Statistics |
(3) |
|
Stat 195 Introduction to Mathematical
Statistics |
(3) |
|
Total |
(6) |
|
First Semester |
Stat 230 Special Topics in Math for Statistics
|
3 |
|
Stat 231 Probability Theory |
3 |
|
Elective |
3 |
|
Total |
9 |
|
Second Semester |
Stat 232 Parametric Inference |
3 |
|
Stat 250 Sampling Designs |
3 |
|
Elective |
3 |
|
Total |
9 |
|
|
Student will start working for the thesis
at this point. |
|
Third Semester |
Stat 233 Linear Models |
3 |
|
Stat 290 Statistical Consulting |
1 |
|
Elective |
3 |
|
Elective |
3 |
|
Total |
10 |
|
Fourth Semester |
Stat 290 Statistical Consulting |
1 |
|
Stat 300 Thesis |
6 |
|
Stat 234 Multivariate Analysis |
3 |
|
Total |
10 |
|
Total |
38 |
|