MSDS 402-DL Research Design for Data Science.

This course introduces the scientific method and research design for data science. It distinguishes between primary and secondary research, drawing on survey, observational, and experimental studies. Students learn about sampling techniques and ways of obtaining relevant data. They see how to prepare data for modeling and analysis. They employ feature engineering, constructing new measures from original measures. They learn how to assess the reliability and validity of measures, construct valid research designs, and build trustworthy models. Numerous case studies illustrate rational decision making guided by science. Prerequisites: None.

Although not an elective of the specialization, this course may be of interest to students in Analytics and Modeling.

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