Concept E1.6

Parallel visual-type construction

Align the type of data (numeric, categorical, string, other) to a visualization type designed for that use-case.

K–2 Competencies

Explore hands-on activities with students, helping them understand the difference between data types. e.g., bar graphs for numerical data such as votes of favorite fruit, picture graph for categorical data such as favorite colors

K-2.E.1.6a

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Data Science Starter Kit Module 5: Telling the Story - Visualization and Communication

Welcome to the culminating skill of data science—communicating your findings effectively so others can understand and act on them! This module focuses on how to create clear visualizations and compelling narratives that make data accessible and meaningful to different audiences.🔗

Visualization and Communication isn’t about creating fancy graphics or impressive presentations. It’s about developing the empathy and clarity to think, “How can I help others understand what this data means and why it matters to them?” The best data science in the world is useless if it can’t be understood and applied by the people who need it.

3–5 Competencies

Visualize multiple types of data (e.g., numeric, categorical, string data) during in-class data collection exercises.

3-5.E.1.6a

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Data Science Starter Kit Module 5: Telling the Story - Visualization and Communication

Welcome to the culminating skill of data science—communicating your findings effectively so others can understand and act on them! This module focuses on how to create clear visualizations and compelling narratives that make data accessible and meaningful to different audiences.🔗

Visualization and Communication isn’t about creating fancy graphics or impressive presentations. It’s about developing the empathy and clarity to think, “How can I help others understand what this data means and why it matters to them?” The best data science in the world is useless if it can’t be understood and applied by the people who need it.

6–8 Competencies

Describe and discuss the typical visualization characteristics of numeric, categorical, and string data while identifying and outlining the differences between them.

6-8.E.1.6a

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Data Science Starter Kit Module 5: Telling the Story - Visualization and Communication

Welcome to the culminating skill of data science—communicating your findings effectively so others can understand and act on them! This module focuses on how to create clear visualizations and compelling narratives that make data accessible and meaningful to different audiences.🔗

Visualization and Communication isn’t about creating fancy graphics or impressive presentations. It’s about developing the empathy and clarity to think, “How can I help others understand what this data means and why it matters to them?” The best data science in the world is useless if it can’t be understood and applied by the people who need it.

9–10 Competencies

Demonstrate the wrong type of data (e.g., numeric, categorical, string) entered into a misaligned visualization package (e.g., scatterplot of categorical data) and explain why the visualization fails to work or clearly represent the data.

9-10.E.1.6a

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Data Science Starter Kit Module 5: Telling the Story - Visualization and Communication

Welcome to the culminating skill of data science—communicating your findings effectively so others can understand and act on them! This module focuses on how to create clear visualizations and compelling narratives that make data accessible and meaningful to different audiences.🔗

Visualization and Communication isn’t about creating fancy graphics or impressive presentations. It’s about developing the empathy and clarity to think, “How can I help others understand what this data means and why it matters to them?” The best data science in the world is useless if it can’t be understood and applied by the people who need it.

11–12 Competencies

Produce a data visualization parallel to the type of data (e.g., numeric, categorical, string, image, unstructured).

11-12.E.1.6a

Defend your visualization choice to others and explain the data type and visualization type including suitability for continuous or discrete variables.

11-12.E.1.6b

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Data Science Starter Kit Module 5: Telling the Story - Visualization and Communication

Welcome to the culminating skill of data science—communicating your findings effectively so others can understand and act on them! This module focuses on how to create clear visualizations and compelling narratives that make data accessible and meaningful to different audiences.🔗

Visualization and Communication isn’t about creating fancy graphics or impressive presentations. It’s about developing the empathy and clarity to think, “How can I help others understand what this data means and why it matters to them?” The best data science in the world is useless if it can’t be understood and applied by the people who need it.

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