Graduate Group in Epidemiology & Biostatistics

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MS Program in Biostatistics

Overview

The goal of the MS program is to train students in the basic theory and applications of statistical methods, as applied to problems in the biomedical sciences. The program typically consists of two years of full-time study, including the successful completion of a written exam and the preparation of a Master's thesis. Requirements include courses in probability, mathematical statistics, and statistical methods including discrete data analysis, linear models, multivariate methods, survival analysis, statistical computing, and applied data analysis. All students take a course in epidemiology. An overview of the program appears here; for complete details see the GGEB Handbook

Academic Advisor

Each incoming MS student is assigned an academic advisor who serves as the student's primary mentor during the program, advising in course selection and related academic matters. An attempt is made to assign advisors to students with similar backgrounds and interests, although a student may petition the Director of Graduate Studies at any time to request a change of academic advisor.

Course Requirements

Candidates for the MS degree must complete 12 units of course credit, pass the written qualifications exam, and prepare a Master’s thesis.  Required courses cover probability, mathematical statistics, and statistical methods including categorical data analysis, linear models, survival analysis, and applied data analysis.  All students also take a course in epidemiology.

The MS in Biostatistics typically requires four semesters of formal course work.  Students must complete nine units of required courses, three units of electives, and the Biostatistics in Practice I and II requirements (see Section 7.3.9). The required courses are described below.  The courses in bold type are the “core” courses for the MS degree that are covered on the written qualifications examination.

Theory:

BSTA 620 Probability (1 unit)

BSTA 621 Statistical Inference I (1 unit)

Methods:

BSTA 630 Methods I (1 unit)

BSTA 632 Statistical Methods for Categorical and Survival Data (Methods II) (1 unit)

BSTA 651 Introduction to Linear Models & Generalized Linear Models (1 unit)

BSTA 656 Longitudinal Data Analysis (1 unit)

BSTA 660 Design of Observational Studies (1 unit) OR BSTA 661 Design of Interventional Studies I (1.0 unit)

BSTA 670 Statistical Computing (1 unit)

Applications:

BSTA 509 Introductory Epidemiology (0.5 unit)

BSTA 510 Introduction to Human Health and Diseases (0.5 unit) Note:  This course will not be required nor offered for students matriculating after 2016

BSTA 511: Biostatistics in Practice I (0.5)

General Examination

MS students must pass a written qualifying examination covering material in the core courses. This exam is offered each year after the fall semester in conjunction with the Qualifications Evaluation Examination for the PhD MS students typically take this exam in the summer after completing the second semester of coursework.

Elective Courses

Students in the MS program choose three additional units from a list of advanced courses in biostatistics and related topics.  At least two of these courses must be quantitative; the third may be in a related scientific field subject to approval by the Curriculum Committee Chair and Program Director.  A partial listing appears under the section on electives for the PhD program (Section 7.3.3).  In addition to these electives, BSTA 622 Inference II and BSTA 754 Advanced Survival Analysis, which are required courses for the PhD program, may be used as advanced electives for the MS program.  Courses not described here may be used as advanced electives for the MS program upon receiving approval from the Chair of the Curriculum Committee and the Program Chair.

Biostatistics in Practice and the MS Thesis

All MS students must participate in the Biostatistics in Practice I seminar and complete a Biostatistics in Practice II (BIP II) project, which serves as the MS thesis.  The BIP II project consists of a comprehensive analysis of a dataset and a report of the results. The BIP II project may be completed in any semester.

 

Typical Course Sequence for Full-Time Students in the MS Program:

  Semester Required Credit Courses (units)

 

 

 

 

Year 1

Fall

BSTA 620: Probability (1)
BSTA 630: Statistical Methods and Data Analysis I (1)
BSTA 509: Introductory Epidemiology (0.5)
BSTA 510: Introduction to Human Health and Diseases (not required or offered after 2016)
BSTA 511: Biostatistics in Practice I (0.5)

Spring

BSTA 621 Statistical Inference I (1)
BSTA 632 Statistical Methods for Categorical and Survival Data
BSTA 651 Introduction to Linear Models & GLM (1)
BSTA 511: Biostatistics in Practice I (cont.)


Summer


Written Qualifications Examination

 


 

Year 2

Fall

BSTA 670 Statistical Computing (1)
Advanced Electives (2)

Biostatistics in Practice II / MS Thesis

Spring

BSTA 656 Longitudinal Data Analysis (1)
BSTA 660: Design of Observational Studies (1) or BSTA 661: Design of Interventional Studies (1)
Advanced Elective (1)

Biostatistics in Practice II / MS Thesis Presentation

Transfer of Credit

Only courses considered at the graduate level may be transferred from previous training.  At least eight course units of the total program required for the MS degree must be completed while enrolled in a graduate program at UPenn.  Because the MS program requires only 12 total course units, no more than four may be satisfied by transfer credit.  Similarly, at least twelve course units of the twenty required for the PhD degree must be completed while enrolled in a degree program at UPenn; thus a maximum of eight units may be transferred from graduate work.  Courses proposed for transfer credit must be relevant to training in biostatistics and may include courses in theory, methods, or towards a minor (see Section 7.3.6 regarding minors).  Transfer of credit must be approved by the Program Chair and the GGEB Chair.

Academic Program Proposals and Approvals

At the beginning of each academic year, each student, in collaboration with his/her advisor, will prepare a proposal for the academic program including courses to be taken, courses to be transferred, and timelines for examinations and thesis preparation.