After a Transformation of the Y-Variable Values into Log Y

After a transformation of the y-variable values into log y, and performing a regression analysis produced the following tables. $$\begin{array} { | c | c | c | c | c | } \hline & \text { Coefficients } & \text { Stardard Error } & t \text { Statistic } & p \text {-value } \\\hline \text { Iritercept } & 2.005349 & 0.097351 & 20.59923 & 4.81 \mathrm { E } - 18 \\\hline \boldsymbol { x } & 0.027126 & 0.009518 & \mathbf { 2 . 8 4 9 8 4 3 } & \mathbf { 0 . 0 0 8 2 7 5 } \\\hline\end{array}$$ $$\begin{array} { | c | c | c | c | c | c | } \hline & \mathrm { df } & \text { SS } & \text { MS } & F & p \text {-value } \\\hline \text { Regression } & 1 & 0.196642 & 0.196642 & 8.121607 & 0.008447 \\\hline \text { Residual } & 26 & 0.629517 & 0.024212 & & \\\hline \text { Total } & 27 & 0.826159 & & & \\\hline\end{array}$$ For x₁= 10, the predicted value of y is ____________.

A) 155.79
B) 1.25
C) 2.42
D) 189.06
E) 18.90