Here is the average annual pay of teachers in each of my groups.

\begin{array}{lccc}&\text { Elementary school } & \text {Middle school } & \text {High school }\\\hline \text { Female } & \$ 42,000 & \$ 45,000 & \$ 50,000 \\\text { Male } & \$ 40,000 & \$ 52,000 & \$ 58,000 \\\hline\end{array}

a. Create a column graph that represents these data accurately.
b. Looking at the data in the table and the column graph, do you think there is a main effect for gender?
c. Looking at the data in the table and the column graph, do you think there is a main effect for school level?
d. Looking at the data in the table and the column graph, do you think there is an interaction effect for gender X school level?
e. What is the argument against interpreting main effect when there is a statistically significant interaction effect?
f. Suppose that for the main effect of school level F₍_{2, 174)} = 5.49. Is this a statistically significant main effect?
g. "Wait a second!" someone says. "Those differences between groups may be caused by how long the teachers have been on the job. Everyone knows that the more experienced teachers get paid more. You have to control for that!" So I add "Years of teaching experience" to the model to control for its effects on teacher pay. What is this kind of variable called?

Suppose I Wanted to Know Something About How Much Teachers

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