Fixed multivariate notation

tex/chapters/kde.tex

@@ -13,7 +13,7 @@
 %In contrast, 
 The KDE is often the preferred tool to estimate a density function from discrete data samples because of its ability to produce a continuous estimate and its flexibility.
 %
-Given a univariate random sample $X=\{X_1, \dots, X_n\}$, where $X$ has the density function $f$ and let $w_1, \dots w_n$ be associated weights.
+Given a univariate random sample set $X=\{X_1, \dots, X_n\}$, where $X$ has the density function $f$ and let $w_1, \dots w_n$ be associated weights.
 The kernel estimator $\hat{f}$ which estimates $f$ at the point $x$ is given as
 \begin{equation}
 \label{eq:kde}