STAT 450 - Introduction to R for Data Science

Units: 3
Introduction to the R environment and data analysis. Topics include use of dataframes and lists, importing and exporting different kinds of data files, writing user defined functions, R packages, Regression, Principle Components Analysis (PCA), and Clustering.

Prerequisites: One of: STAT 110, STAT 303, STAT 310, STAT 315, STAT 330.
Possible Instructional Methods: On-ground or Online-Asynchronous.
Grading: A-F or CR/NC (student choice).
Course Typically Offered: Fall ONLY

Student Learning Outcomes - Upon successful completion of this course students will be able to:
• Understand and apply fundamental R programming concepts: vectors, data frames, logical operators, if-else statements, for loops, and functions.

• Perform relevant transformations of data sets: subset rows and columns; create new columns, or variables, with functions of existing variables; merge data sets that share a common variable.

• Create and interpret meaningful visualizations of data.

• Communicate the results of a data analysis clearly and appropriately to others using reproducible research techniques (R Markdown).