diff --git a/docs/1b/ece108.md b/docs/1b/ece108.md
index 779f4fd..868a5f3 100644
--- a/docs/1b/ece108.md
+++ b/docs/1b/ece108.md
@@ -911,3 +911,19 @@ $$Pr\{X^{-1}(\{x\})\}$$
 Thus the **binomial distribution** for $r$ successes of $n$ total tries, if they are independent, is:
 
 $$Pr\{X=r\}{n\choose r}p^rq^{n-r}$$
+
+### Independence
+
+Please see [SL Math - Analysis and Approaches 2#Conditional probability](/g11/mcv4u7/#conditional-probability) for more information.
+
+Two events are independent if they can be treated separately.
+
+$$\text{independent}\iff Pr\{A\cap B\}=Pr\{A\}Pr\{B\}$$
+
+Or, via the inclusion-exclusion theorem:
+
+$$\text{independent}\iff Pr\{A\cup B\}=Pr\{A\}+Pr\{B\}-Pr\{A\}Pr\{B\}$$
+
+**Bayes' theorem** provides a general formula for conditional probability:
+
+$$Pr\{A|B\}=\frac{Pr\{B|A\}}{Pr\{B\}}$$