DATA 201 - Statistical Methods in Data Science

Statistical concepts and applications related to data science including advanced exploratory data analysis, nonparametric inference and simulation for larger datasets, logistic regression modeling, statistical programming, and basics of machine learning. PREREQUISITE(S): A grade of C or better in DATA 101 or consent of department. Three hours each week.

3 semester hours

Course Outcomes:
Upon course completion, a student will be able to:

Select appropriate existing analytical and presentational tools for specific analyses of large databases.
Develop new and appropriate analytical and presentational tools for specific analyses of large databases through programming.
Demonstrate a competency with data science practices that allows for reproducible results.
Summarize findings based on complex analyses in a concise way for a general audience using multivariate graphics and statistical measures.

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