From c0d352dd0f66b47ee91fb96eaf320f895fa78790 Mon Sep 17 00:00:00 2001
From: Prefetch
Date: Sun, 14 Nov 2021 17:54:04 +0100
Subject: Expand knowledge base

---
 content/know/concept/conditional-expectation/index.pdc | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

(limited to 'content/know/concept/conditional-expectation')

diff --git a/content/know/concept/conditional-expectation/index.pdc b/content/know/concept/conditional-expectation/index.pdc
index 5bcc152..5a8f07e 100644
--- a/content/know/concept/conditional-expectation/index.pdc
+++ b/content/know/concept/conditional-expectation/index.pdc
@@ -77,10 +77,10 @@ $$\begin{aligned}
 Recall that because $Y$ is a random variable,
 $\mathbf{E}[X|Y] = f(Y)$ is too.
 In other words, $f$ maps $Y$ to another random variable,
-which, due to the *Doob-Dynkin lemma*
-(see [$\sigma$-algebra](/know/concept/sigma-algebra/)),
-must mean that $\mathbf{E}[X|Y]$ is measurable with respect to $\sigma(Y)$.
-Intuitively, this makes some sense:
+which, thanks to the *Doob-Dynkin lemma*
+(see [random variable](/know/concept/random-variable/)),
+means that $\mathbf{E}[X|Y]$ is measurable with respect to $\sigma(Y)$.
+Intuitively, this makes sense:
 $\mathbf{E}[X|Y]$ cannot contain more information about events
 than the $Y$ it was calculated from.
 
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