From cfa9b2f005c4b8e0ebe939abdbf523ad97ba211b Mon Sep 17 00:00:00 2001
From: Greg Ashton <gregory.ashton@ligo.org>
Date: Tue, 15 Sep 2020 16:05:35 +0100
Subject: [PATCH] Fix typo

---
 docs/basics-of-parameter-estimation.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/basics-of-parameter-estimation.txt b/docs/basics-of-parameter-estimation.txt
index 7cf00eeec..37b97d59b 100644
--- a/docs/basics-of-parameter-estimation.txt
+++ b/docs/basics-of-parameter-estimation.txt
@@ -6,7 +6,7 @@ In this example, we'll go into some of the basics of parameter estimation and
 how they are implemented in :code:`bilby`.
 
 Firstly, consider a situation where you have discrete data :math:`\{y_0,
-y_1,\ldots, y_n\}` taken at a set of times :math:`\{t_0, t_1, \ldots, y_n\}`.
+y_1,\ldots, y_n\}` taken at a set of times :math:`\{t_0, t_1, \ldots, t_n\}`.
 Further, we know that this data is generated by a process which can be modelled
 by a linear function of the form :math:`y(t) = m t + c`. We will refer to
 this model as :math:`H`. Given a set of data,
-- 
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