The Linear Regression Equation, Y = a + BX, Was

Multiple Choice

The linear regression equation, Y = a + bX, was estimated. The following computer printout was
obtained:
$\begin{array}{rllll}\text { DEPENDENT VARIABLE: } & \text { Y } & \text { R-SQUARE } & \text { F-RATIO } & \text { P-VALUE ON F } \\\text { OBSERVATIONS: } &18 & 0.3066 & 7.076 & 0.0171\end{array}$

$\begin{array}{lllll}\text { VARIABLE } & \begin{array}{llll}\text { PARAMETER } \\\text { ESTIMATE }\end{array} & \begin{array}{l}\text { STANDARD } \\\text { ERROR }\end{array} & \text { T-RATIO } & \text { P-VALUE } \\\text { INTERCEPT } & 15.48 & 5.09 & 3.04 & 0.0008\\X&-21.36&8.03&-2.66&0.0171\end{array}$
-Which of the following statements is correct at the 1% level of significance?

A) Both $\hat { a }$ and
$\hat { b }$ are statistically significant.
B) Neither $\hat { a }$ nor
$\hat { b }$ is statistically significant.
C) $\hat { a }$ is statistically significant, but
$\hat { b }$ is not.
D) $\hat { b }$ is statistically significant, but
$\hat { a }$ is not.