INTERACTIVE DATA ANALYTICS

Prerequisites & course information

Requisites: I SY E/PSYCH 349 and ( I SY E 210 , E C E 331 , MATH/STAT 310 , STAT 312 , 324 , or 340 ), graduate/professional standing, or member of Engineering Guest Students Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2025 Learning Outcomes: 1. Approach visualization as a design process, using the critical response process and paper prototypes Audience: Both Grad & Undergrad 2. Design visualizations for different audiences and different purposes Audience: Both Grad & Undergrad 3. Use the concepts of abstraction and aggregation to translate raw data into meaningful information Audience: Both Grad & Undergrad 4. Use the flexibility of the grammar of graphics to craft graphs for effective communication Audience: Both Grad & Undergrad 5. Develop replicable data analyses and visualizations with R and RShiny Audience: Both Grad & Undergrad 6. Create specialized data analytic visualizations such as time series decompositions and ROC curves Audience: Graduate Learning Outcomes: 1. Approach visualization as a design process, using the critical response process and paper prototypes Audience: Both Grad & Undergrad 2. Design visualizations for different audiences and different purposes Audience: Both Grad & Undergrad 3. Use the concepts of abstraction and aggregation to translate raw data into meaningful information Audience: Both Grad & Undergrad 4. Use the flexibility of the grammar of graphics to craft graphs for effective communication Audience: Both Grad & Undergrad 5. Develop replicable data analyses and visualizations with R and RShiny Audience: Both Grad & Undergrad 6. Create specialized data analytic visualizations such as time series decompositions and ROC curves Audience: Graduate