From 575deb180bc026314d53e4237dd7cd08a465e3c4 Mon Sep 17 00:00:00 2001
From: jwarren-scottlogic <jwarren@scottlogic.com>
Date: Tue, 29 Oct 2024 15:30:49 +0000
Subject: [PATCH] Adjusting styling again

---
 ...-21-building-an-assignment-algorithm-2.markdown | 14 +++++++++-----
 1 file changed, 9 insertions(+), 5 deletions(-)

diff --git a/_posts/2024-10-21-building-an-assignment-algorithm-2.markdown b/_posts/2024-10-21-building-an-assignment-algorithm-2.markdown
index 800d074c1f..b2fbb023bb 100644
--- a/_posts/2024-10-21-building-an-assignment-algorithm-2.markdown
+++ b/_posts/2024-10-21-building-an-assignment-algorithm-2.markdown
@@ -156,10 +156,11 @@ Finally, we landed on using the Z-score for aggregate compromise. The Z-score is
 <details class="no-italic"><summary>Click the 'more' button for to see how we compared compromise and surplus difference exactly, along with the rationale.</summary>
 <br>
 <br>
+The value which we use to score attendees can be calculated as:
 \[
 \begin{align}
-\text{sorting score} &= \text{standardisedSurplusScore} \\
-&- \text{standardisedCompromiseScore}
+\text{sorting score} =& \text{standardisedSurplusScore} \\
+&\; - \text{standardisedCompromiseScore}
 \end{align}
 \]
 <br>
@@ -168,9 +169,12 @@ Finally, we landed on using the Z-score for aggregate compromise. The Z-score is
     Where the \(\text{standardisedCompromiseScore}\) is: 
 </p>
 
-\[standardisedCompromiseScore = 
-\left( \frac{\text{mean surplus difference}}{\text{max surplus}} \right) \times 
-\left( \frac{\text{attendee Z score}}{2.72} \right)^3
+\[
+\begin{align}
+standardisedCompromiseScore =& 
+\left( \frac{\text{mean surplus difference}}{\text{max surplus}} \right)
+&\; \times \left( \frac{\text{attendee Z score}}{2.72} \right)^3
+\end{align}
 \]
 
 <div style="display: flex; justify-content: flex-end;">