To interpret the effect of $X_4$ on the dependent variable in this multiple regression analysis:

• $X_4$ is a qualitative (dummy) variable, which means it can take only the values of 0 or 1.
• The coefficient for $X_4$ is $-9.976$, indicating the effect of $X_4 = 1$ on the dependent variable.

When $X_4$ changes from 0 to 1, the dependent variable is expected to decrease by 9.976 units, all else being equal. This is because a coefficient of $-9.976$ implies a reduction of that amount when $X_4$ takes the value 1.

Thus, the correct answer is:

The dependent variable will decrease by 9.976 units.

Would you like further details or explanations? Here are 5 related questions:

1. What is the significance of the p-value for $X_4$ in this analysis?
2. How does a dummy variable like $X_4$ affect the regression model?
3. How should we interpret the coefficient of $X_3$ despite its large standard error?
4. What impact does the intercept have in this regression model?
5. How do we assess the overall goodness-of-fit for this regression model?

Tip: The p-value helps assess whether the effect of a variable is statistically significant. If it's less than a threshold (commonly 0.05), the variable is considered to have a significant effect on the dependent variable.