To bring you the best content on our sites and applications, Meredith partners with third party advertisers to serve digital ads, including personalized digital ads. Those advertisers use tracking technologies to collect information about your activity on our sites and applications and across the Internet and your other apps and devices. Evan Klitzke has a good explanation of the problem and a theoretical explanation of why Peter is correct. 15 minutes, regardless of how much time they’ve been trying to find a block. But we don’t need to rely on a theoretical argument alone. To empirically show why Peter is correct using real Bitcoin block time data, we’ll need to adapt the problem. 10 minutes until the next block is found, no matter how much time it has been since the last block was found.
Let’s find out if the data supports this. It’s an easy way to analyze Bitcoin data. One simplifying assumption: in order to analyze time between mined blocks, I sorted blocks by their timestamp. A given block’s timestamp may even be earlier than the timestamp of a prior block. Looking at data from 2016 , the mean block time is 9.
61, and the distribution looks exponential, as expected. Now, if we only look at blocks that are found more than 10 minutes since the prior block, we see that the mean time is 19. 64, about 10 minutes after our 10 minute offset. The distribution looks nearly identical, only it’s offset by 10. The same pattern can be seen for offsets up to about 65 minutes.
Beyond 65 minutes, although the expected time until the next block is still 10 minutes, we can’t show it empirically due to a small sample size. We can take this one step further by picking a set of random times and observing the mean time until the next block. It doesn’t matter what times you pick – 10 minutes since the last block was mined, totally random, every hour on the hour, your friends’ birthdays, whatever! The expected time until the next block will always be 10 minutes.