[AMR] Notes in various sections

electives/amr/parts/00_basics/00_probability.tex

@@ -20,3 +20,5 @@ e.g. $\sum_{X} \P(X) = 1$ becomes $\int \P(x) \dx = 1$
 PDF: $f(\vec{x}) = \frac{1}{\sqrt{(2\pi)^k \det(\mat{\Sigma})}} \text{exp}\left( -\frac{1}{2}(\vec{x} - \vec{\mu})^\top \mat{\Sigma}^{-1} (\vec{x} - \vec{\mu}) \right)$
 
 $\Sigma^{-1}$ for $\Sigma$ diagonal, inverse of diag els (e.g. $\sigma^{-1}$)
+
+\hl{Always Normalize (i.e. sum of all probabilities is 1)}

electives/amr/parts/00_basics/03_error-propagation.tex

@@ -1,4 +1,5 @@
 \subsection{Error Propagation}
 \label{sec:error-propagation}
 For functions $\vec{f}(\vec{x}) = \mat{A}\vec{x}$, the \bi{linear error propagation}
-is given by $\Sigma^f = A \Sigma^x A^\top$, with $\Sigma^x$ the uncertanty of $\vec{x}$ (covariance mat.)
+is given by $\Sigma^f = A \Sigma^x A^\top$, with $\Sigma^x$ the uncertanty of $\vec{x}$ (covariance mat.), typically $\texttt{diag}(\sigma^2)$,
+with $\sigma^2$ the variance of all variables involved