Open your copy of Fitting a Model: State Demographics Starter File. If you haven’t already, Save a Copy now.
1 Which two columns will you explore? x-axis and y-axis.
2 Fill in the code to make a scatter plot exploring the relationship between those columns:
scatter-plot(states-table, "state", , )
3 Pick two states to use for your first model: and .
4 Based on these two points, define your model in Function and Pyret Notation:
| Function Notation | Pyret Notation |
|---|---|
𝑓(𝑥) = x + |
fun f(x): ( * x) + end |
5 Type this model into Pyret, and fit it to your data use fit-model. What 𝑆 value did you get?
6 What’s the best model you can build? In the table below, record your models and the 𝑆 values you got for them, then draw a star next to the one with the best 𝑆-value.
| Model (Function or Pyret Notation - whatever you prefer!) | 𝑆 |
|---|---|
★ What does this model actually mean? Try completing the sentence below:
This model predicts that a 1 percent[x-axis units] increase in [x-axis] is associated with a [slope, y-units] increaseincrease / decrease in [y-axis]. Based on the 𝑆 of S, I would say this model fits real well / not great / poorly / terribly.
These materials were developed partly through support of the National Science Foundation, (awards 1042210, 1535276, 1648684, 1738598, 2031479, and 1501927). 
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