Articles like this really bother me because its really unclear what data here is significant (if any) since all of the data is just quoted as a % without standa

Articles like this really bother me because its really unclear what data here is significant (if any) since all of the data is just quoted as a % without standard error and the sample sizes are very small: e.g. on comparing companies that do better. You could have a data set of 150 companies whose exit performance (or current value) looks something like this (numbers in millions): 5000,1000,500,400,200,200,100,50,50,30,30,20,20,20,15,15,15,15,0,0,0,0,0,0,0 (repeated 6x to get 150 data points) Now compare that against a data set that is those exact numbers divided in half: 2500,500,250,200,100,100,50,25,25,15,15,10,10,10,7.5,7.5,7.5,7.5,0,0,0,0,0,0,0 (repeated 6x to get 150 data points) If you compare these data sets with a Two Sample T-Test you have to go down to 91% confidence to get a significant result (http://www.evanmiller.org/ab-testing/t-test.html#!307.2/986.137554/150;153.6/493.068777/150@91 http://www.evanmiller.org/ab-testing/t-test.html#!307.2/986....) That may not sound that bad, but now add a super-unicorn to each one of those data sets, a $20B exit. Now the differences aren't even significant at 80% confidence. e.g. in Item 7 about technical co-founders: "consumer companies with at least one technical co-founder underperform completely non-technical teams by 31%" Lets say that First Round has 150 consumer businesses and we're just going to look at a binary outcome of something like "valued over $50m". Now lets say that 100 of these consumer companies have technical co-founders and 50 are completely non-technical. Say 40% of the non-technical teams are "successful" by the $50m metric. That means that 30.5% of the technical teams are successful (if they are doing 31% worse by the numbers in the article since 40%/1.31 = 30.5%). That's not a significant result at 80% confidence (http://www.evanmiller.org/ab-testing/chi-squared.html#!31/100;20/50@80 http://www.evanmiller.org/ab-testing/chi-squared.html#!31/10...) I understand why they published the piece and think it will get a lot of reads, but really wish I could read a version with statistically relevant insights instead.