Master of Science in Biostatistics
The Master of Science in Biostatistics is designed for students interested in applying statistical methods to the design and analysis of biomedical research and clinical investigations data.
The program focuses on the theory of biostatistics, data analytic methods, experimental design (including the design, conduct and analysis of clinical trials), statistical methods in human genetics, biomedical informatics and advanced statistical computing methods. Statistical methods are taught both from a practical and theoretical perspective.
Priority: December 1st
Final: May 1st
Program at a glance
Typically completed in 2 years, the 39-unit degree consists of 8 core courses (28 units), 2 to 5 elective courses (at least 7 units) and a master’s thesis (4 units). During the program, students take part in research teams assisting with study design, data coordination and management, statistical analysis and reporting of results.
Core Coursework (28 Units)
PM 510 Principles of Biostatistics (4 units)
Concepts of biostatistics; appropriate uses and common misuses of health statistics; practice in the application of statistical procedures; introduction to statistical software including EXCEL, SPSS, nQuery.
PM 511a Data Analysis (4 units)
Major parametric and nonparametric statistical tools used in biomedical research, computer packages including SAS. Includes laboratory.
PM 511b Data Analysis (4 units)
Statistical methods for analysis of categorical data including dichotomous, ordinal, multinomial and count data, using Stata package. Includes laboratory.
PM 512 Principles of Epidemiology (4 units)
Terminology/uses of epidemiology and demography; sources/uses of population data; types of epidemiologic studies; risk assessment; common sources of bias in population studies; principles of screening.
PM 513 Experimental Designs (3 units)
Statistical methods for analysis of various experimental designs. Parametric analysis of variance (ANOVA), repeated measures methods, crossover designs, non-parametric ANOVA.
PM 518a Statistical Methods for Epidemiological Studies I, II (3 units)
Principles and methods used in epidemiology for comparing disease frequencies between groups. Restricted to the analysis of binary outcome variables.
PM 522a Introduction to the Theory of Statistics (3 units)
Density distribution and hazard functions; normal, chi-square, student’s t and F distributions; and sampling procedures for single factor and multiple factor designs, distributions.
PM 522b Introduction to the Theory of Statistics (3 units)
Theory of estimation and testing, inference, analysis of variance, theory of regression. Recommended Preparation: college-level calculus and linear algebra.
Electives (7 units)
For elective offerings, visit the USC Course Catalogue.
Thesis (4 units)
The program culminates in a master’s thesis on a topic of the student’s choosing. The research consists of original work worthy of submission to a publication or peer-review journal.
Full-time students begin working on their thesis at the beginning of their second year and register for the thesis courses over two consecutive semesters.
PM 594a Master’s Thesis (2 units)
PM 594b Master’s Thesis (2 units)
The program culminates in a master’s thesis on a topic of the student’s choosing. The thesis provides a structure for the development of a plan to address a research problem and a suitable approach to the analysis and presentation of the results. The equivalent of one year of full-time effort must be devoted to research leading to a master’s thesis.
Trevor Pickering, PhD
Director of the Master of Science in Biostatistics program
A Message from Trevor Pickering
When I reflect on my motivation to become a biostatistician, the words of John Tukey come to mind: “The best thing about being a statistician is that you get to play in everyone’s backyard.” As part of the Keck School of Medicine, we are positioned in an environment with tremendous research opportunities (or should I say, “backyards to play in”). The Master of Science in Biostatistics program connects you to these opportunities, whether your interest is in data analysis, clinical research, or methods development.
Using compensation data site Payscale, Forbes takes an annual look at mid-career data on 45 popular master’s degrees. The ranking considers pay growth from early to mid-career, job satisfaction, stress, projected employment growth of jobs associated with each degree, and more.