BANL 510 - Data Analytics I

An introduction to statistical models used in predictive analytics, with a focus on linear regression models, students explore the challenges of building meaningful models from large data sources, with an emphasis on model building and the use of numerical and graphical methods for assessing model fit. The course addresses model selection and appropriate methodology based on the objectives and available data to carry out analysis. Interpretation and communication of results is emphasized, using SAS Studio and basic SAS programming techniques.
Prerequisite(s): Complete MATH-180 or equivalent and CMIT-130 or equivalent.
Credit(s): 6