This course will offer a series of in-class demonstrations and hands-on practice in computer lab sessions where graduate students in the Health Sciences program, and in the Department of Community Health and Epidemiology will learn various features of SAS, a statistical software frequently used in health research. This course will provide an overview on data entry, data management, visualization using SAS, and some commonly used techniques (descriptive statistics, T-test, ANOVA, linear regression, and logistic regression). To demonstrate their competency, students will complete a final project incorporating the SAS skills they have learned during the course to analyze and interpret results from a provided data set. Prerequisite(s): An upper-level undergraduate statistics course.
This course will offer a series of in-class demonstrations and hands-on practice in computer lab sessions where graduate students in the Health Sciences program, and in the Department of Community Health and Epidemiology will learn various features of SAS, a statistical software frequently used in health research. This course will provide an overview on data entry, data management, visualization using SAS, and some commonly used techniques (descriptive statistics, T-test, ANOVA, linear regression, and logistic regression). To demonstrate their competency, students will complete a final project incorporating the SAS skills they have learned during the course to analyze and interpret results from a provided data set. Prerequisite(s): An upper-level undergraduate statistics course.
