squiggle.c

commit 08908f9da56268747822f13122a0a61dbd0ae515
parent 8547347ac628a94da82d66dfa97c294100e38f57
Author: NunoSempere <nuno.sempere@protonmail.com>
Date:   Thu,  2 Nov 2023 21:49:35 +0000

add more digits to 90% normal constant

Diffstat:
A
examples/15_plotting-scratchpad/.Rhistory
 | 
7
+++++++
M
squiggle.c
 | 
1
+

2 files changed, 8 insertions(+), 0 deletions(-)
diff --git a/examples/15_plotting-scratchpad/.Rhistory b/examples/15_plotting-scratchpad/.Rhistory
@@ -0,0 +1,7 @@
+library(ggplot2)
+data <- read.csv("samples.txt", header = FALSE)
+data <- as.data.frame(data)
+ggplot(data = data, aes(x = V1)) +
+geom_bar()
+ggplot(data = data, aes(x = V1)) +
+geom_freqpoly()
diff --git a/squiggle.c b/squiggle.c
@@ -85,6 +85,7 @@ inline double sample_normal_from_90_confidence_interval(double low, double high,
     // 1. We know that the 90% confidence interval of the unit normal is
     // [-1.6448536269514722, 1.6448536269514722]
     // see e.g.: https://stackoverflow.com/questions/20626994/how-to-calculate-the-inverse-of-the-normal-cumulative-distribution-function-in-p
+    // or https://www.wolframalpha.com/input?i=N%5BInverseCDF%28normal%280%2C1%29%2C+0.05%29%2C%7B%E2%88%9E%2C100%7D%5D
     // 2. So if we take a unit normal and multiply it by
     // L / 1.6448536269514722, its new 90% confidence interval will be
     // [-L, L], i.e., length 2 * L