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

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

$\begin{array}{lllll}\text { VARIABLE } & \begin{array}{llll}\text { PARAMETER } \\\text { ESTIMATE }\end{array} & \begin{array}{l}\text { STANDARD } \\\text { ERROR }\end{array} & \text { T-RATIO } & \text { P-VALUE } \\\text { INTERCEPT } & 15.48 & 5.09 & 3.04 & 0.0008\\X&-21.36&8.03&-2.66&0.0171\end{array}$
-The parameter estimate of b indicates

A) X increases by 8.03 units when Y increases by one unit.
B) X decreases by 21.36 units when Y increases by one unit.
C) Y decreases by 2.66 units when X increases by one unit.
D) a 10-unit decrease in X results in a 213.6 unit increase in Y.