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    CSU East Bay
  Jul 22, 2017
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2015-2016 CSU East Bay Catalog [ARCHIVED CATALOG]

Statistics, Computational Statistics Option, M.S.

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Program Description

The Department of Statistics and Biostatistics offers graduate study leading to the degree Master of Science in Statistics. The program is flexible in order to serve the needs of students with varying backgrounds (including statistics, mathematics, computer science, engineering, business, economics and other quantitative fields) and with different career objectives. The program includes options in Applied Statistics, Computational Statistics, Mathematical Statistics, and Actuarial Science. All students are expected to master a wide variety of applied statistical, computational, and probabilistic techniques and the theoretical foundations upon which these techniques are based. Students are expected to be familiar with recent developments in the field and to be able to use the statistical literature to learn new techniques and theories throughout their professional careers. In addition to the general requirements stated elsewhere in this catalog, students must satisfy the departmental requirements stated in the following paragraphs.

Students interested in pursuing an M.S. degree in Biostatistics should see the Biostatistics chapter in the university catalog.

Student Learning Outcomes

Students graduating with an M.S. in Statistics from Cal State East Bay will be able to:

  1. Apply statistical methodologies, including a) descriptive statistics and graphical displays, b) probability models for uncertainty, stochastic processes, and distribution theory, c) hypothesis testing and confidence intervals, d) ANOVA and regression models (including linear, and multiple linear) and analysis of residuals from models and trends.
  2. Derive and understand basic theory underlying these methodologies
  3. Formulate and model practical problems for solutions using these methodologies
  4. Produce relevant computer output using standard statistical software and interpret the results appropriately
  5. Communicate statistical concepts and analytical results clearly and appropriately to others; and
  6. Understand theory, concepts, and terminology at a level that supports lifelong learning of related methodologies.

Admission Requirements

  1. A baccalaureate degree or equivalent.
  2. Differential and Integral Calculus, including multiple integration and infinite series (MATH 1304 , MATH 1305 , MATH 2304 ).
  3. Departmental approval.
  4. For “Classified Graduate” status, fulfillment of the University Writing Skills Requirement. For information on meeting the University Writing Skills Requirement, see the Testing Office website at or call 510.885.3661.

In addition to the above minimal requirements for admission, if students have some of the following background they will be at an advantage both as to selection for admission to the program and optimal progress toward the degree if admitted:

  • basic statistics and probability at the level of STAT 3401 , STAT 3502  (or beyond)
  • additional mathematics at the level of MATH 2101  (or beyond)
  • knowledge of a computer programming language
  • experience in a setting where studies or experiments are conducted for the collection of data.

Advancement to Candidacy Requirements

  1. Completion of at least 15 quarter units of approved coursework beyond the baccalaureate, with an average of “B” (3.0) or higher.
  2. Departmental approval.

Degree Requirements (48 units)

Successful completion of the following unit, grade, and course requirements.

Unit and Grade Requirements

The M.S. in Statistics program consists of at least 48 quarter units of approved upper division and graduate work. The university requirement for the minimum number of 6000-level units applies. All work applied toward the 48 units must be at an average grade of “B” (3.0) or higher. No graduate-level required course may be at a grade below “B-.”

Computational Statistics Option (20 Units)

Topics include regression modeling, multivariate statistics, factor analysis, Monte Carlo simulations, Markov Chain, Monte Carlo methods, bootstrapping, data mining, and other computationally intensive methods.

Required Courses:

Choose two additional courses from those not taken above, or:

Comprehensive Examination

Successful completion of a departmental examination is required. This written examination will cover the contents of the courses in the candidate’s approved program. Other material may be included, the general nature of which will be specified in advance. The examination is given only in the Fall and Spring quarters, and will cover both applied and theoretical topics.

In each quarter of offering, the department Chair will appoint three or more members of the graduate faculty to administer the examination. Each student will generally take the Comprehensive Examination in the quarter of intended graduation or in the preceding quarter, after consulting with the graduate advisor. Students enrolled in the Actuarial Science Option may substitute a passing grade on an approved national actuarial exam for a designated portion of the comprehensive examination, with the approval of the graduate advisor. The examination committee is the final departmental authority in deciding eligibility to take the examination.

Other Degree Requirements

In addition to departmental requirements, every student must also satisfy the university requirements for graduation which are described in the Graduate Degree Information  chapter in this catalog. These include the 32-unit residence requirement, the five year rule on currency of subject matter, the minimum number of units of 6000-level courses, the 3.00 grade point average, and the University Writing Skills requirement.

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