DATA STORYTELLING WITH VISUALIZATION

Prerequisites & course information

Requisites: Sophomore standing and satisfied Quantitative Reasoning (QR) A Course Designation: Core GenEd - Social & Behavioral Science Breadth - Social Science Level - Intermediate L&S Credit - L&S Liberal Arts and Science Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Understand theories of data visualization Audience: Undergraduate 2. Explain how and why visualization can be an effective tool for summarizing, analyzing and communicating about data Audience: Undergraduate 3. Understand and apply best practices for communicating about data for targeted and broad audiences Audience: Undergraduate 4. Understand and apply theories and best practices for creating visualizations Audience: Undergraduate 5. Design and develop informative and persuasive visualizations Audience: Undergraduate 6. Identify and choose appropriate software for creating visualizations Audience: Undergraduate 7. Choose appropriate visualization types based on source data, audience, and goal Audience: Undergraduate 8. Critically analyze visualizations created by others for effectiveness and bias Audience: Undergraduate 9. Understand the limitations and challenges of data visualization Audience: Undergraduate Learning Outcomes: 1. Understand theories of data visualization Audience: Undergraduate 2. Explain how and why visualization can be an effective tool for summarizing, analyzing and communicating about data Audience: Undergraduate 3. Understand and apply best practices for communicating about data for targeted and broad audiences Audience: Undergraduate 4. Understand and apply theories and best practices for creating visualizations Audience: Undergraduate 5. Design and develop informative and persuasive visualizations Audience: Undergraduate 6. Identify and choose appropriate software for creating visualizations Audience: Undergraduate 7. Choose appropriate visualization types based on source data, audience, and goal Audience: Undergraduate 8. Critically analyze visualizations created by others for effectiveness and bias Audience: Undergraduate 9. Understand the limitations and challenges of data visualization Audience: Undergraduate