For this question, use the following multiple regression output (which may differ from the output in other questions, even though the variables are the same).

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.507
R Square	0.257
Adjusted R Square	0.217
Standard Error	5319.659
Observations	100
ANOVA
	df	SS	MS	F	Significance F
Regression	5	918149733.6	183629946.7	6.489	3.175E-05
Residual	94	2660085040	28298777.02
Total	99	3578234773
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	9714.244	3289.053	2.954	0.0040	3183.751	16244.736
Annual Income ($1000)	87.421	18.063	4.840	5.082E-06	51.557	123.284
Household Size	-145.809	270.677	-0.539	0.5914	-683.244	391.627
Education	-676.427	335.456	-2.016	0.0466	-1342.483	-10.371
TV Hours	42.242	31.228	1.353	0.1794	-19.762	104.247
Age	-72.153	52.101	-1.385	0.1694	-175.601	31.295

All other things being equal, how much do you estimate the annual charges will change for a unit increase in weekly hours of TV watched? A negative number means the predicted charges will decrease, while a positive number means they will increase.

Group of answer choices

-$31.23

$42.24

-$42.24

$31.23

It depends on what the current TV watching hours are.