3 ms·
Sorry to be another typical HN nitpicker, but one problem I see with many of these approaches is that the significance level (95% in this case) is picked out of
by tedsanders 13y ago
Sorry to be another typical HN nitpicker, but one problem I see with many of these approaches is that the significance level (95% in this case) is picked out of thin air. The reality is that even with a single data point, you have information. The information may not be reliable, but it's information nonetheless. The only reason that people don't redesign based on unreliable information is that redesigns have costs: costs for the developer and costs for the users. Given that different sites have different cost functions, they should also have different significance thresholds.
One size does not fit all.
- jessicaraygun 13y agoThe recommendation of 95% significance level is quite common across A/B testing resources. The main goal here is to be able to say which variant will consistently perform best (in this case, 95% of the time). I agree that it would be useful to be able to change the confidence level based on a site's specific needs - this is a feature I am looking to implement in Confidence.js soon.