From 92135102fae01a65657d6d36308dc85a2b6b1ec5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Nu=C3=B1o=20Sempere?= Date: Tue, 20 Nov 2018 17:12:47 +0100 Subject: [PATCH] Update Analysis.md --- rat/EA-predictions/Analysis.md | 19 +++++++++---------- 1 file changed, 9 insertions(+), 10 deletions(-) diff --git a/rat/EA-predictions/Analysis.md b/rat/EA-predictions/Analysis.md index ea39ec6..ea726b4 100644 --- a/rat/EA-predictions/Analysis.md +++ b/rat/EA-predictions/Analysis.md @@ -1,7 +1,14 @@ # Analysis of some predictions about the 2018 EA Survey ## Introduction. -A group of effective altruism community leaders made predictions about the 2018 EA Survey: a survey which aims to reach most people within the effective altruism movement. Here, I present the set up for the prediction making, the questions, and explain some judgement calls I made when judging the answers. Everything is written such that you can play along. At the end, I provide some code to replicate my analysis. The data was given to me by David Nash. +A group of effective altruism community leaders made predictions about the 2018 EA Community Survey. Here, I analyze how well calibrated they are. I present the main result first because most people just skim stuff. If readers remain interested, I then outline the set up for the prediction making, present the questions, and explain some judgement calls I made when judging the answers. Everything is written such that you can play along. At the end, I provide some code to replicate my analysis. The data was given to me by David Nash. + +## Results +For the 35 people who took part in the original prediction making, their results can be seen in the following graphics: + +![](https://nunosempere.github.io/rat/EA-predictions/Scatterplot3.jpeg) + +The average accuracy is 55.12%, that is, the average participant got 13.22 out of 24 questions right. If it had been reached, a target credence of 80% would imply an average of 19.2 correct answers. In other words, when EA Community leaders say 80%, the thing happens 55% of the time. If they bet, they'd be replacing ~1:1 bets with 1:4 bets. ## Set up For every question, try to come up with an interval such that you're 80% confident the answer lies in it. If you use a search engine, the surveys from previous years are fair game. @@ -96,20 +103,12 @@ I got this answers using R from the data released by the EA survey people, avail 1. 52.5508247 1. 26.50556195 -## Results -For the 35 people who took part in the original prediction making, their results can be seen in the following graphics: -![](https://nunosempere.github.io/rat/EA-predictions/Scatterplot3.jpeg) - - -The average accuracy is 55.12%, that is, the average participant got 13.22 out of 24 questions right. If it had been reached, a target credence of 80% would imply an average of 19.2 correct answers. In other words, in this limited domain, when these people say 80%, the thing happens 55% of the time. If they bet, they'd be replacing ~1:1 bets with 1:4 bets. - -### Other ways to break down the data: +## Other ways to break down the results: ![](https://nunosempere.github.io/rat/EA-predictions/Scatterplot2.jpeg) ![](https://nunosempere.github.io/rat/EA-predictions/histogram.jpeg) ![](https://nunosempere.github.io/rat/EA-predictions/Brier-scores.jpeg) - ## Is this an spurious result because a small number of questions were really, really hard? No. See the following scatterplot: