Adjust Big-O Notation slide

lectures/complexity/slides.qmd

@@ -20,7 +20,18 @@ Investigation of resources needed for algorithms working on data structures
  - Memory required to run an algorithm
 
 
-## big-$\mathcal{O}$ notation
+## Big-$\mathcal{O}$ Notation
+
+ - With enough data, usually only the order in relation to input data $n$ is important
+ - Therefore the big-$\mathcal{O}$ notation describes the asymptotic behaviour of running an algorithm
+
+| Order        | Notation               |
+| ------------ | ---------------------- |
+| constant     | $\mathcal{O}(1)$       |
+| logarithmic  | $\mathcal{O}(\log{n})$ |
+| linear       | $\mathcal{O}(n)$       |
+| quadratic    | $\mathcal{O}(n^2)$     |
+
 
 # specific algorithms