QBS 119 Foundations of Biostatistics I: Applied Biostatistics

In this course, students will learn foundational topics for biostatistics including probability, probability distributions, random variables, moments of distributions, variable transformations, sampling distributions, the central limit theorem, P-values and confidence intervals, hypothesis testing, parametric and non-parametric test statistics, power and sample size calculations, and study designs for biomedical research. Statistical testing approaches covered in the course will include bivariate analyses (including simple linear regression) to prepare the student for multivariable modeling in future courses. Course content will be drawn from the course text book and peer-reviewed research studies. In-class activities will prominently feature active learning activities. The course will require extensive use of the R Language for Statistical Computing.

The course is intended for students who need a strong foundation in statistical thinking and basic biostatistics concepts to enable them to continue to more advanced applied biostatistical coursework in multivariable statistical modeling. The content will largely parallel that of QBS 120 yet will differ from that course by emphasizing the application of biostatistics and not the underlying mathematical theory. Graduate students who intend to pursue methods development (either within biostatistics or bioinformatics) or those who wish to understand the mathematical foundations of statistical theory should enroll in QBS 120.

Instructor

Dr. Jennifer Emond

Prerequisite

N/A