Using data to estimate relationships between predictors and responses is an important task in statistics and data science. When datasets are large, modern methods have been developed that allow us to estimate those relationships without making strong assumptions about those relationships- i.e. we can let the data determine how E(y|x) relates to x. In statistics, these methods are generally referred to as ?nonparametric regression.? This applied graduate course will focus on learning to use nonparametric regression to analyze data. We will read a book, ?Semiparametric Regression with R,?

This clinical course provides an opportunity for students to develop beginning skills in gathering patient data and providing safe basic nursing care.