Small fixes for typos in lectures 2 (found by Naman) and 4

50008 - Probability and Statistics/Lecture 2 - (Random Variables)/Lecture 2.tex

@@ -290,7 +290,7 @@
             \begin{center}
                 \begin{tabular}{c | c | c | c}
                     \keyword{PMF} & \keyword{Expected} & \keyword{Variance} & \keyword{Skewness} \\
-                    $p_X(x) = {n \choose x}p^^x(1-p)^{n-x}$ & $\mu = E(X) = np$ & $\sigma^2 = Var(X) = np(1-p)$ & $\gamma_1 = \cfrac{1 - 2p}{\sqrt{np(1-p)}}$ \\
+                    $p_X(x) = {n \choose x}p^x(1-p)^{n-x}$ & $\mu = E(X) = np$ & $\sigma^2 = Var(X) = np(1-p)$ & $\gamma_1 = \cfrac{1 - 2p}{\sqrt{np(1-p)}}$ \\
                 \end{tabular}
             \end{center}
 

50008 - Probability and Statistics/Lecture 4 - (Joint random distributions)/Lecture 4.tex

@@ -80,7 +80,7 @@
                 \[f_Y(y) = \cfrac{d}{dy} \int_{x = -\infty}^{\infty} \int_{s = -\infty}^y f(x,s) \ ds \ dx\]
                 Hence by applying the fundamental theorem of calculus:
                 \[f_X(x) = \int_{y=-\infty}^{\infty} f(x,y) \ dy\]
-                \[f_X(y) = \int_{x=-\infty}^{\infty} f(x,y) \ dx\]
+                \[f_Y(y) = \int_{x=-\infty}^{\infty} f(x,y) \ dx\]
             }
             \example{Marginal pdf}{
                 Given continuous variables $(X, Y) \in \mathbb{R}^2$: