Summary and Setup

  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]

  1. 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

  2. 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.