instructions
This exercises tasks you with collecting data and creating a data visualization that communicates that data visually.
Step 1: Collect Data
Pose a “research question,” and collect a set of quantitative (numerical) data to help you answer it.
For example:
How long does it take to get to a specific floor in the elevator vs. climbing the stairs?
What kind of books take up the most space on your shelves?
How much time do the ducks in your yard spend preening vs. foraging?
Think about the various processes that take time or require resources. (How many almonds do you eat in an hour? How long (on average) does it take for you to drink [insert drink of choice]?) Think about the items you have around you and what they are used for. (How many times do you pick up your phone in the span of an hour?) Quantitative data is all around you. Every time you do something, check something, or observe something, you are generating data. And so are the things around you (i.e. stoplights, phones, dogs, squirrels, etc.) Select an item (or items) around you, and collect the data it generates.
Note: You may not use the automatic Screen Time data collection function on your phone.
Step 2: Create a Visualization
Once you have collected your data, draw a data visualization that represents your data. To pick the type of data visualization, go back to the Design chapter you read and review the visualization types. You can use any medium you want to create your visualization (pens, crayons, markers, or, if you are familiar with the technology, an app like Canva (Links to an external site.) or Excel).
Step 3: Share your Visualization
Share your visualization in the discussion below, and provide the following context:
What does your data visualization show?
Why did you pick that visualization format (as opposed to another)?
Note: If you drew your visualization, you can submit a photo of your drawing.
Step 4: Review and Comment
After sharing your work, use the “Reply” button to comment on at least two of your peers’ visualizations, and address the following:
Is the visualization clear? (Is it clear what the visualization represent?)
Is the type of visual appropriate for the data? Can you think of other types of visuals that might be useful?
Does the design and color use make the visual easy to read?
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