Summary and Schedule

1. What is Data Viz

   Explain the purpose of data visualization in communicating a scientific story or idea Identify the components of a data visualization and their function

   • terminology
   • purpose of data visualization
   • elements of a plot

2. Understanding your Data

   Recognize properties of a dataset (categorical vs. continuous, grouping, dependency in time) suitable for visualization Make decisions for what to share in a visual format Identify and list any critical context for understanding the information/results

3. Creating a Data Viz

   Choose visual aesthetics (position, shape, color, size) appropriate for aspects of a dataset (quantity, label, etc.) Demonstrate different approaches to creating a data visualization Assess a dataset for appropriate data visualization options

[ref: https://clauswilke.com/dataviz/aesthetic-mapping.html]

4. Consuming a Data Viz

   • Compare and contrast interpretation of different visualizations from the same dataset
   • Propose questions about choices made during the data visualization process

5. Error Awareness / Improvement / Iteration

   • Recognize common mistakes responsible for misleading plots or misinterpretations.
   • Evaluate a plot for areas of potential sources of confusion.
   • Suggest improvements to plots that clarify its points.

	Setup Instructions	Download files required for the lesson
Duration: 00h 00m	1. Using Markdown	How do you write a lesson using Markdown and sandpaper?
Duration: 00h 12m	2. What is Data Visualization	TODO
Duration: 01h 12m	3. Understanding Your Data	TODO
Duration: 02h 12m	4. Creating Data Visualizations	How do I choose a data visualization? How do I help readers understand my data? How do I visualize uncertainty and weird data?
Duration: 02h 12m	5. Evaluating Data Visualization	TODO
Duration: 02h 12m	6. Error Awareness	TODO
Duration: 02h 12m	Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.