THE MASTER OF SCIENCE (STATISTICS) PROGRAM

The Master of Science in Statistics program 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.

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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).

 

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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.
  • Social Statistics - the generation of official statistics by the government requires statistical methods that are commonly used in social and economic applications. This area targets students working/intends to work for the government and those who eventually wish to pursue further studies in the social sciences or in economics.
  • 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

  • Statistics 231 Probability Theory
  • Statistics 232 Parametric Statistical Inference
  • Statistics 233 Linear Models
  • Statistics 234 Multivariate Analysis
  • Statistics 250 Sampling Designs

Other Courses

  • Statistics 230 Special Topics in Mathematics for Statistics
  • Statistics 290 Statistical Consulting (2 units)
  • Statistics 300 Thesis
  • Statistics 300 Multivariate Analysis
  • Electives in Statistics 12 Units

List of Elective Courses

  • 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
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