Chapter 4 A First Assignment
This assignment will help you get comfortable with CODAP basics. It is designed to be conceptually super easy, so you can master some of the mechanics of doing a small project…because there will be more projects.
And it’s short. What you submit consists of a graph and a few sentences in a CODAP text box.
4.1 How do you know when you’re done?
- You have explored the dataset about Californians in 2013.
- You have found a simple relationship between two attributes.
- You have made a graph that shows that relationship.
- You have a CODAP document
- it includes the graph.
- it has a text box with a narrative
- the narrative begins with a claim about the data
- the narrative goes on to explain what you did and why the claim makes sense
- you have shared the CODAP doc and emailed the link to your instructor
4.2 A new dataset!
Time to look at some new data! You will look at data for 1000 Californians in 2013.
Here is a link to a document in a browser tab … or you can at least start in the live illustration below.`
Here are some questions to answer to make sure you understand the data set.
The people are from a specific age range. What is that range?
Why do you suppose the dataset has people from that age range?
Describe the oldest person in the dataset.
Describe the person in the dataset with the highest income.
4.3 Some elaboration
Explore. It’s essential that you mess around with the data. Here, that means make graphs. More than one. Drag different attributes to the axes to make different graphs. Try stuff in the palettes at the right edge of the graph (like the “ruler” and the “eyeball”). Select things in the graphs and see what’s selected in other graphs.
Simple relationship. For this assignment, that means it’s a relationship between only two attributes. We have already explored more complex relationships: when we filtered the height-and-gender data to show only 10-year-olds, we were looking at three attributes: age, gender, and height. For this assignment, just look at two.
For example, with the previous dataset, you might have plotted
Or you might have made a graph of
Gender and plopped
BMI in the middle.
A Narrative explains what you did. Communication is part of data science (as it is a part of everything). You need to be able to explain yourself clearly and concisely. Use complete sentences. For this assignment, you will not need very many!
This is a statement about the data that might be true or false.
It doesn’t matter which, though we generally make claims we think are true.
In the data with heights, with a graph of
you might claim: Heavier people are taller.
A claim does not have to be dramatic. A null result is still a result! Using the gender-BMI graph, you might claim: There’s no relationship between gender and BMI.
Of course, your claim will be about this new data set (1000 Californians), not the old one (800 children and teens).
“Pretty old, like, over 40” is an actual quote from a student, referring to unmarried people in a dataset.↩