GDEV 3295 - Introduction to Data Science with R

Fall. 3 credits. Letter grades only.

Forbidden Overlap: due to an overlap in content, students will receive credit for only one course in the following group: AEM 2850, NTRES 6100, GDEV 4290, GDEV 5290, STSCI 3040, STSCI 5040.
C. Liao.

The goal of this course is to introduce to students the applied aspects of R programming for conducting basic data-driven research. As one of the most popular programming languages, R provides a rich environment for working with data, especially for statistical modeling and graphics. In this course we will cover data import and management, basic functions, plotting tools, loops and functions, basic linear models, and various graphing tools. Course content focuses on design and implementation of R programs to meet routine and specialized data manipulation, management, and analysis objectives. Attention will be given to mastering concepts and tools necessary for implementing reproducible research, with examples in the context of global development, environmental sustainability, and food systems.

Outcome 1: Implement the syntax of base R and ggplot2 package.

Outcome 2: Import a variety of data formats into R.

Outcome 3: Clean a dataset and make it ready for analysis.

Outcome 4: Conduct basic summary statistics for a dataset.

Outcome 5: Perform basic statistical analysis (e.g. linear regression).

Outcome 6: Produce data visualizations using base R and more advanced packages.