From 574e1f7e48f238efada8bff73ba26fd6dd50aaac Mon Sep 17 00:00:00 2001
From: Stratis Ioannidis <stratis@stratis-Latitude-E6320.(none)>
Date: Mon, 11 Feb 2013 16:36:11 -0800
Subject: related

---
 problem.tex | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'problem.tex')

diff --git a/problem.tex b/problem.tex
index d505280..3bdbb94 100644
--- a/problem.tex
+++ b/problem.tex
@@ -1,5 +1,5 @@
 \label{sec:prel}
-\subsection{Linear Regression and Experimental Design}
+\subsection{Linear Regression and Experimental Design}\label{sec:edprelim}
 
 The theory of experimental design \cite{pukelsheim2006optimal,atkinson2007optimum,chaloner1995bayesian} considers the following formal setting. %  studies how an experimenter \E\  should select the parameters of a set of experiments she is about to conduct. In general, the optimality of a particular design depends on the purpose of the experiment, \emph{i.e.}, the quantity \E\  is trying to learn or the hypothesis she is trying to validate. Due to their ubiquity in statistical analysis, a large literature on the subject focuses on learning \emph{linear models}, where \E\ wishes to  fit  a linear function to the data she has collected.
 %Putting cost considerations aside
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