Exercise

# Factorial Experiment with NYC SAT Scores

Now we want to examine the effect of tutoring programs on the NYC schools' SAT Math score. As noted in the last exercise: the variable `Tutoring_Program`

is simply `yes`

or `no`

, depending on if a school got a tutoring program implemented. For `Percent_Black_HL`

and `Percent_Tested_HL`

, `HL`

stands for high/low. A 1 indicates less than 50% Black students or overall students tested, and a 2 indicates greater than 50% of both.

Remember that because we intend to test all of the possible combinations of factor levels, we need to write the formula like: `outcome ~ factor1 * factor2 * factor3`

.

Instructions

**100 XP**

- Use
`aov()`

to create a model to test how`Percent_Tested_HL`

,`Percent_Black_HL`

, and`Tutoring_Program`

affect the outcome`Average_Score_SAT_Math`

. - Save the outcome as a model object,
`nyc_scores_factorial`

, and examine this with`tidy()`

.