DA 821 Dynamic Healthcare Data Analytics Techniques & Methods: 821

Prerequisites: None. This course covers the statistical methods used for the time series analysis in healthcare data analysis. The course introduces the students to concepts of time series decomposition, stationary vs. non-stationary univariate series, various forms of ARIMA models (white noise, AR, MA, ARMA, unit root, co-integration, ARIMA, and seasonal ARIMA), as well as exponential smoothing, multivariate time series models, and advanced forecasting techniques. Students will learn how to apply these methods using the statistical software package R.

Credits

3