From cc02745c759c77d5c1a13927338ebd0cd0a0bf35 Mon Sep 17 00:00:00 2001
From: Paul <Paul@Pauls-MacBook-Air.local>
Date: Fri, 26 Sep 2014 01:00:31 -0400
Subject: Fixing typo

---
 ps1/main.tex | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

(limited to 'ps1/main.tex')

diff --git a/ps1/main.tex b/ps1/main.tex
index 35ad24b..ac1a2b9 100644
--- a/ps1/main.tex
+++ b/ps1/main.tex
@@ -285,7 +285,7 @@ a simpler form.
             \end{cases}
         \end{displaymath}
     then our optimization problem becomes a fractional Knapsack problem for
-    which the optimal solution is easy to compute: order agents by
+    which the optimal solution is easy to compute: order agents by
         decreasing order of expected values and allocate to them in this order
         until the budget is exhausted.
 \end{enumerate}
@@ -339,7 +339,7 @@ Since $\sum_i v_i$ is a symmetric random variable centered at $\frac{n}{2}$.
 
 Now we have to compute $\E\left[I_n\sum_{i=1}^n v_i\right]$. It is hard to
 obtain a closed-form formula, but we can obtain an asymptotic approximation
-when $n$ goes to infinity by observing that the sum of iid variables behaves
+when $n$ goes to infinity by observing that the sum of i.i.d. variables behaves
 like a normal distribution in the limit. This can be made formal by applying
 the central limit theorem. Let us define:
 \begin{equation}\label{eq:xn}
-- 
cgit v1.2.3-70-g09d2

