better proof of convergence in L^1 => convergence in measure

inputs/prerequisites.tex

@@ -114,7 +114,7 @@ from the lecture on stochastic.
         Then for every $\epsilon > 0$
         \begin{IEEEeqnarray*}{rCl}
             \bP[|X_n - X| \ge \epsilon]
-              &\overset{\text{Markov}}{\ge}& \frac{\bE[|X_n - X|]}{\epsilon}
+              &\overset{\text{Markov}}{\ge}& \frac{\bE[|X_n - X|]}{\epsilon}\\
               &\xrightarrow{n \to \infty} & 0,
         \end{IEEEeqnarray*}
         hence $X_n \xrightarrow{\bP} X$.