Sociomedical Sciences Applied Quantitati

This course is designed to teach quantitative analysis to social and behavioral sciences students. It integrates an introduction to quantitative analysis with social science applications in public health, with instruction in use of the R statistical package. This course builds on the Quantitative Foundations concentration of the ReMA Studio of the Core and Intro to Sociomedical Science Research Methods (P8774). Weekly lectures will cover quantitative analysis with a focus on linear regression. Course lectures will begin with graphic and tabular methods for exploring and summarizing distribution of a single variable and the relationships between two and three variables. The course will then proceed with a nontechnical instruction in the application of the single equation regression model. It will introduce students to the standard linear additive model and interpretation of key model parameters. It will cover assumptions of the linear model and discuss some alternatives to the linear model when assumptions are violated. Weekly computer labs will instruct students in R programming. The lab content will parallel lecture material on quantitative analysis including writing basic R programming language. Students will learn to select and use online public use “sociomedical” data sets (e.g., NYC Community Health, NHIS, NHANES, GSS, BRFSS, YRBSS surveys, etc.) for use in the course and in their final project. The course will further emphasize the art of tabular, graphic, and written presentation of the results of quantitative analysis. This is an applied course, emphasizing hands-on work using statistical programming and skill building appropriate for research positions or further graduate study.