From 85552266076ba61aefc50833bb101e14dd88e62a Mon Sep 17 00:00:00 2001
From: Liam Toney <38269494+liamtoney@users.noreply.github.com>
Date: Tue, 28 Sep 2021 16:37:27 -0800
Subject: [PATCH 1/2] Use correct confidence interval

See table here: https://journals.plos.org/plosone/article/figure?id=10.1371/journal.pone.0118537.t001
---
 examples/statistics/confidence_ellipse.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/statistics/confidence_ellipse.py b/examples/statistics/confidence_ellipse.py
index 9ba8758999d2..0c6229881605 100644
--- a/examples/statistics/confidence_ellipse.py
+++ b/examples/statistics/confidence_ellipse.py
@@ -36,7 +36,7 @@
 # of standard deviations. The default value is 3 which makes the ellipse
 # enclose 99.4% of the points if the data is normally distributed
 # like in these examples (3 standard deviations in 1-D contain 99.7%
-# of the data, which is 99.4% of the data in 2-D).
+# of the data, which is 98.9% of the data in 2-D).
 
 
 def confidence_ellipse(x, y, ax, n_std=3.0, facecolor='none', **kwargs):

From 82850375b1a8de2b1882cdec97ac1eda9d28ef9d Mon Sep 17 00:00:00 2001
From: Liam Toney <38269494+liamtoney@users.noreply.github.com>
Date: Tue, 28 Sep 2021 20:53:17 -0800
Subject: [PATCH 2/2] Change other place where incorrect value appears

Missed this one somehow...
---
 examples/statistics/confidence_ellipse.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/statistics/confidence_ellipse.py b/examples/statistics/confidence_ellipse.py
index 0c6229881605..b5d3b4793c79 100644
--- a/examples/statistics/confidence_ellipse.py
+++ b/examples/statistics/confidence_ellipse.py
@@ -34,7 +34,7 @@
 #
 # The radiuses of the ellipse can be controlled by n_std which is the number
 # of standard deviations. The default value is 3 which makes the ellipse
-# enclose 99.4% of the points if the data is normally distributed
+# enclose 98.9% of the points if the data is normally distributed
 # like in these examples (3 standard deviations in 1-D contain 99.7%
 # of the data, which is 98.9% of the data in 2-D).