Basic concepts of statistics with applications in health and life sciences. Descriptive statistics, principles of statistical inference, uncertainty assessment, hypothesis testing, public health surveys, and biomedical experimental design are considered. Methods include t-tests, simple linear regression, and categorical data analysis.

Basic concepts of statistics, with applications in health and life sciences. Descriptive statistics, principles of statistical inference, uncertainty assessment, hypothesis testing, public health surveys, and biomedical experimental design are considered. Methods include t-tests, simple linear regression, and categorical data analysis.

A survey of statistical methods, with applications in public health and the biological sciences, including multiple regression, clinical trials, analysis of variance, categorical data analysis, and logistic regression. Motivating examples are drawn from public health and biomedicine.

A survey of statistical methods, with applications in public health and the biological sciences, including multiple regression, clinical trials, analysis of variance, categorical data analysis, and logistic regression. Motivating examples are drawn from public health and bio-medicine.

Independent, intensive, and extended research conducted under the supervision of a faculty member.

Methods for comparing time-to-event data, including univariate parametric and nonparametric procedures, regression models, diagnostics, group comparisons, and use of relevant statistical computing packages.

Faculty-supervised independent or collaborative inquiry into fundamental and applied problems within a discipline that requires students to gather, analyze, synthesize, and interpret data and to present results in writing and other relevant communication formats.

Faculty-supervised independent or collaborative inquiry into fundamental and applied problems within a discipline that requires students to gather, analyze, synthesize, and interpret data and to present results in writing and other relevant communication formats.

Faculty-supervised independent or collaborative inquiry into fundamental and applied problems within a discipline that requires students to gather, analyze, synthesize, and interpret data and to present results in writing and other relevant communication formats.

Faculty-supervised independent or collaborative inquiry into fundamental and applied problems within a discipline that requires students to gather, analyze, synthesize, and interpret data. Students will write or produce a thesis or other professional capstone product, such as a report or portfolio that describes their systematic and in-depth inquiry.

Research while enrolled for a master's degree under the direction of a faculty member.

Students will develop statistical literacy in public health. Course will provide the fundamentals of biostatistics and will apply them to public health research. Topics will include exploratory data analysis, probability theory, and how to interpret the statistical output.