Open your copy of the State Demographics Starter File.
The al-ak Model
Type fit-model(states-table, "state", "pct-college-or-higher", "median-income", al-ak) in the Interactions Area, then find the points representing AL and AK along the predictor line. Hint: You know their coordinates and they will help you know where to look!
1 What do you Notice?
2 What do you Wonder?
3 Find S in the upper left corner. What is the S value (the number after S)?
4 With median income ranging from
lowest median income to
highest median income, what does the S-value of the al-ak model tell us?
Comparing Models
5 Use fit-model to find the S-value for the mi-ca model.
6 Is the mi-ca model better or worse than the al-ak model?
7 How much
more / less
error do we expect in predictions made with the mi-ca model than predictions made with the al-ak model?
Percent Change =
$$\displaystyle \frac{ \text{Difference} \text{between} \text{the} \text{S-values} } {\text{S-value} \text{for} \text{al-ak} \text{model}} \times 100 = $$$$\displaystyle \frac{\qquad}{\qquad}$$
mi-ca model predictions are expected to have
percent
more / less
error than al-ak model predictions!
A Model of Your Own
8 Identify two other states that you think would make a better model: and .
Add two new definitions for these states to your State Demographics Starter File.
9 Record the college-or-higher and median-income values for these states, as (x,y) pairs below:
(college-or-higher, median-income) (college-or-higher, median-income)
10 Derive your model and write it below (in both Function and Pyret notation), then fit the model and record the S-value:
other(x) = slope (m)x + y-intercept / vertical shift
fun other(x): ( * x) + end S:
11 Adjust the slope and y-intercept of your model to get the smallest S possible. Write the best model you find (and corresponding S) below:
fun best(x): ( * x) + end S:
12 How much
more / less
error do we expect in predictions made with your model than predictions made with the mi-ca model? %
These materials were developed partly through support of the National Science Foundation, (awards 1042210, 1535276, 1648684, 1738598, 2031479, and 1501927). 
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