Biostatistics
- Department Information
- Program Description
- M.S. in Biostatistics
- Other Degree Requirements
- Graduate Courses
- Footnotes
Department Information
Department of Statistics and Biostatistics
College of Science
Office: North Science 229
Phone: (510) 885-3435
Professor Emerita
Julia A. Norton Ph.D. Harvard University
Professor
Eric A. Suess (Chair), Ph.D. University of California, Davis
Associate Professors
Lynn Eudey, Ph.D. University of California, Berkeley
Shenghua (Kelly) Fan, Ph.D. University of Minnesota
Mitchell R. Watnik, Ph.D. University of California, Davis
YanYan Zhou, Ph.D. University of Maryland
Assistant Professor
Joshua D. Kerr, Ph.D. University of California, Davis
Graduate Coordinator: Lynn Eudey
Program Description
The Department of Statistics and Biostatistics offers graduate study leading to the degree Master of Science in Biostatistics. The program is designed to serve the needs of students with varying backgrounds in Statistics, Biological Sciences, Public Health, Computer Science, Mathematics and other sciences. The program includes curriculum designed to prepare students to work in the pharmaceutical and biotech industries. All students are expected to master a wide variety of applied statistical and probabilistic techniques and the theoretical foundations on which these techniques rest. They are expected to be familiar with recent developments 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, a student must satisfy the departmental requirements stated in the following paragraphs.
Student Learning Outcomes
Students graduating with an M.S. in Biostatistics from Cal State East Bay will have achieved the following:
- theoretical, interpretive and basic computational skill in (a) descriptive statistics, probability, and graphical displays, (b) distributions, hypothesis testing and confidence intervals, and (c) uncertainty, likelihood, modeling and error analysis;
- ability to derive basic theory and communicate to others results involving (a) descriptive statistics, probability, and graphical displays, (b) distributions, hypothesis testing and confidence intervals, (c) uncertainty, likelihood, modeling and error analysis;
- ability to formulate problem solutions, produce appropriate computer code and to decipher standard computer results covering (a) descriptive statistics, probability, and graphical displays, (b) distributions, hypothesis testing and confidence intervals, (c) uncertainty, likelihood, modeling and error analysis.
Admission Requirements
- A baccalaureate degree or equivalent.
- Differential and Integral Calculus, including multiple integration and infinite series.
- Departmental approval.
- For "Classified Graduate" status, fulfillment of the University Writing Skills Requirement.
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 the program and optimal progress toward the degree if admitted:
- basic statistics and probability at the level of STAT 3401, 3502 (or beyond)
- additional mathematics at the level of MATH 2101 and 3100 or 3300 (or beyond)
- knowledge of a computer programming language
- coursework in biology and/or health sciences
- experience in a setting where studies or experiments are conducted for the collection of data
Advancement to Candidacy Requirements
- Completion of at least 15 quarter units of approved work beyond the baccalaureate, with an average of "B" (3.0) or higher.
- Departmental approval. (May be contingent upon a written or oral qualifying examination.)
M.S. in Biostatistics
Degree Requirements
Successful completion of the following unit, grade, and course requirements.
- Unit and Grade Requirements
The M.S. in Biostatistics program consists of at least 48 quarter units of approved upper division and graduate work. At least 44 of these units must be approved graduate (6000 level) courses. All work applied toward the 48 quarter units must be at an average grade of "B" (3.0) or higher. No graduate-level course may be at a grade below "B-."
- Course Requirements (48 units)
Additional courses referred to in section # 3 below must be approved in writing in advance by an advisor.
- Required First Year Courses (24 units)
- STAT 6204 Probability Theory (4)
- STAT 6205 Statistical Theory (4)
- STAT 6250 SAS Programming (4)
- STAT 6304 Advanced Statistical Inference (4)
- STAT 6305 Analysis of Variance Models (4)
- STAT 6509 Theory and Application of Regression (4)
Students entering the program with acceptable credit for any of these courses (or equivalents) will select additional courses from approved graduate-level coursework, section # 3 below, or courses from other departments designated as acceptable by a graduate advisor.
- Required Second Year Courses (24 units)
- BSTA 6651 Analysis of Categorical Data in Biostatistics (4)
- BSTA 6652 Survival Analysis in Biostatistics (4)
- BSTA 6653 Clinical Trials in Pharmaceutical and Biomedical Industries (4)
- STAT 6501 Mathematical Statistics I (4)
- STAT 6502 Mathematical Statistics II (4)
Select one course from the following:
- BSTA 66901 Statistical Bioinformatics (4)
- STAT 6401 Advanced Probability I (4)
- Additional Courses
Students with department approval can select courses in Biostatistics, Biological Sciences, Computer Science, Mathematics, or Statistics. A partial list of courses is given below:
- BSTA 6690 Statistical Bioinformatics (4)
- BSTA 6843-6849 Selected Topics in Biostatistics (4)
- STAT 6310 Advanced Stochastic Processes and Simulation (4)
- STAT 6401 Advanced Probability I (4)
- STAT 6402 Advanced Probability II (4)
- STAT 6515 Advanced Multivariate Analysis (4)
- STAT 6550 Bayesian Statistics (4)
- STAT 6555 Statistical Time Series Analysis (4)
- STAT 6601 Advanced Statistical Computing (4)
- STAT 6860-6864 Selected Topics in Graduate Probability and Statistics (4)
- STAT 6898 Co-operative Education (1-4)
- STAT 6900 Independent Study (1-4)
- MATH 31002 Linear Algebra (4)
- MATH 33002 Analysis I (4)
- Required First Year Courses (24 units)
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 will generally be 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 s(he) intends to graduate or in the preceding quarter, after consulting with 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 (UWSR). For information on meeting the University Writing Skills Requirement, see the Testing Office website at www.csueastbay.edu/testing or call 510.885.3661.
Graduate Courses
| Course Number | Course Information |
|---|---|
| 6651 |
Analysis of Categorical Data in Biostatistics (4) Applied methods for discrete data in Biostatistics. Topics may include: proportions and counts, contingency tables, loglinear models, logistic regression, Poisson regression, generalized linear models. Data integrity. Computing techniques and analysis of discrete data. Use of SAS. Report writing. Prerequisites: STAT 6205, 6250, 6305, 6509. Cross-listed with STAT 6651. |
| 6652 |
Survival Analysis in Biostatistics (4) Applied methods for survival analysis in Biostatistics. Incomplete data, censored and truncated data, life tables, nonparametric methods, parametric methods, accelerated failure time models, proportional hazards models, partial likelihood, advanced topics. Data integrity. Computing techniques and analysis of clinical data. Use of SAS. Report writing. Prerequisite: BSTA 6651. |
| 6653 |
Clinical Trials in the Pharmaceutical and Biomedical Industries (4) Statistical principles, design, and management of clinical trials. Recruitment, treatment allocation, randomization, blocking, and blinding. Practical applications of advanced statistical procedures for clinical trial data. Ethics of clinical trials design, data collection, data analysis and reporting. Data integrity. Data monitoring. Domestic/International regulatory guidelines emphasized. Use of SAS. Professional protocols are studied. Formal report writing and oral presentation. Prerequisite: BSTA 6652. |
| 6690 |
Statistical Bioinformatics (4) Statistical analysis of genomic data. Includes probability and statistics application to DNA sequence analysis, phylogenetic inference, statistical population genetics and genetic mapping, statistical molecular evolution, and macromolecular structure prediction. Emphasis on large datasets. Prerequisite: STAT 6310. A-F grading only. |
| 6843-6849 |
Selected Topics in Biostatistics (4) Topics in biostatistics. Variable content to be specified at time of offering. Prerequisites: STAT 6305 and graduate standing. May be repeated once for credit with consent of department and when content varies, for a maximum of 8 units. Cross-listed with STAT 6843-6849. |
| 6999 |
Issues in Biostatistics (4) Readings, discussion, research, and applications on contemporary and/or significant issues in Biostatistics. May be repeated for credit when content varies, for a maximum of 8 units. |
Footnotes
- Prerequisite: STAT 6310 Advanced Stochastic Processes and Simulation
- Students considering additional graduate education in Statistics or Biostatistics are strongly advised to take advanced mathematics coursework.
