DATA 511 Introduction to Data Science
Introduction to the analysis of data using a data scientific methodology. Topics include data preparation, missing data, data cleaning, exploratory data analysis, statistical estimation and prediction, cross-validation, model evaluation techniques, misclassification costs, cost-benefit analysis, classification and regression trees and report writing.
B or better in a first semester statistics course, such as STAT 104
or STAT 200
or STAT 215
or permission of department chair.