Fitting a straight line to a set of data yields the following prediction line. Complete (a) through (c) below.
\[
\hat{Y}_{i}=18-0.9 X_{i}
\]
a. Interpret the meaning of the \( \mathrm{Y} \)-intercept, \( \mathrm{b}_{0} \). Choose the correct answer below.
A. The \( Y \)-intercept, \( b_{0}=18 \), implies that when the value of \( X \) is 0 , the mean value of \( Y \) is 18 .
B. The \( Y \)-intercept, \( b_{0}=18 \), implies that the average value of \( Y \) is 18 .
C. The \( Y \)-intercept, \( b_{0}=-0.9 \), implies that when the value of \( X \) is 0 , the mean value of \( Y \) is -0.9 .
D. The \( Y \)-intercept, \( b_{0}=18 \), implies that for each increase of 1 unit in \( X \), the value of \( Y \) is expected to increase by 18 units.
b. Interpret the meaning of the slope, \( \mathrm{b}_{1} \). Choose the correct answer below.
A. The slope, \( b_{1}=0.9 \), implies that for each increase of 1 unit in \( X \), the value of \( Y \) is expected to increase by 0.9 units.
B. The slope, \( b_{1}=18 \), implies that for each increase of 1 unit in \( X \), the value of \( Y \) is expected to increase by 18 units.
C. The slope, \( b_{1}=-0.9 \), implies that for each increase of 1 unit in \( X \), the value of \( Y \) is estimated to decrease by 0.9 units.
D. The slope, \( \mathrm{b}_{1}=-0.9 \), implies that the average value of \( \mathrm{Y} \) is -0.9 .
c. Predict the mean value of \( Y \) for \( X=5 \).
\( \hat{Y}_{i}= \) \( \square \) (Type an integer or a decimal.)