Title: Explain techniques for presenting data in a visual format.
Course: Modeling and Simulation Technology (21015) > Section: Visualizing Data

Explanation should include

- the process by which data are converted to visual representations (e.g., graphs, 3D models, charts, maps, vectors, rasters, coordinates)
- applications in a variety of fields (e.g., medicine, meteorology, topography)
- platforms
- interfaces.

Teacher Resources:

Data Visualization and Analysis with Python courses on Open P-Tech:

IBM SkillsBuild (https://yl-ptech.skillsnetwork.site/courses/course-v1:CognitiveClass+DV0101EN+v2)

IBM SkillsBuild (https://yl-ptech.skillsnetwork.site/courses/course-v1:CognitiveClass+DA0101EN+v1)

Intro to VR on CodeHS (http://codehs.com/course/introvr/overview)

Introduction to VR Development in Unity  (http://learn.unity.com/project/introduction-to-vr-development-in-unity)

Process/Skill Questions:

- What is the difference between vectors and rasters?
- How is this difference important in data visualization?
- What are the relative strengths of the different visualization tools?
- How can one determine the best way to present numeric data?
- How can data be misrepresented?
- How does interactivity change the impact of data visualization, negatively and/or positively?
- What are potential uses of virtual reality (VR), augmented reality (AR), mixed reality (MR), and extended reality (XR) in communicating complex information?
- What are some sources of bias that might occur in data visualization?
- How can sources of bias be mitigated?