Exercise

# From experimental results to a prediction

In the previous exercise, you were directed to follow a common strategy: establish a baseline, then change one input at a time to estimate the effect of that input on the output.

In this exercise, you'll be working with a new (and different) `test_scores()`

mathematical model. You'll follow the same procedure as before to estimate the effect of each variable.

Instructions

**100 XP**

- Make a baseline of a
`"public"`

school with academic and religious motivation both set to zero. - Make the following changes one at a time, leaving the other inputs at their baseline values:
- Change school to
`"private"`

. - Change academic motivation to 1.
- Change religious motivation to 1.
- Using just the results you get from these four model runs (be honest now!), make a prediction of what the model output will be for a
`"private"`

school where the student has religious motivation of 2 and academic motivation of 2. Save your prediction in the variable`my_prediction`

. Use this very common linear strategy for making your prediction: - If the change in output going from 0 to 1 is X, then the change in output going from 1 to 2 will also be X.
- Find the change in output for each of the inputs in turn. Add up the individual changes to get the anticipated change when more than one input is changed.
- Once you have made your prediction, test it out by making a new run of
`test_scores()`

with those new inputs.