some minor fixe

likelihood/lecture/likelihood.tex

@@ -300,13 +300,13 @@ the correlation coefficient $r_{x,y}$,
 \eqnref{correlationcoefficient}, is the covariance normalized by the
 product of the standard deviations of $x$ and $y$,
 respectively. Therefore, in case the standard deviations equal one,
-the correlation coefficient equals the covariance.  Consequently, for
-standardized data the slope of the regression line
+the correlation coefficient is identical to the covariance.
+Consequently, for standardized data the slope of the regression line
 \eqnref{whitemleslope} simplifies to
 \begin{equation}
   \theta = \frac{1}{n} \sum_{i=1}^n x_i y_i = \text{cov}(x,y) = r_{x,y}
 \end{equation}
-For standardized data the slope of the regression line equals the
+For standardized data the slope of the regression line is the same as the
 correlation coefficient!