Copernicus has September as hottest on record. It holds the record by 0.05 C, the same as May.

Compare to this range question, where the community gives an 87% chance that any of the top 25 will file by Mar 2024.

Note that fires 6, 7, and 8 were very similarly destructive and this is most likely due to chance, not some magic of that number of buildings being destroyed. Hence a new fire is quite unlikely to stop at places 7 or 8. Quantitatively, fire 7 was only 1.8% more destructive than fire 8, while fire 5 was 18% more destructive than fire 6.

The same goes for fires 3 and 4.

Looks like I can't collect tachyons (yes, I'm below 50).

Taking @RyanBeck 's sheet and filling in the last 2 months of data, I get a mean of 4411 and sd of 77.

@(Sylvain) The resolution criteria say "date when the first credible article is published", notably *not* the date when the event actually occurred. I assume a live-updating page would count, so OWID or Bloomberg from around March 20 would count. Here's my thinking * OWID's page from March 20 is [ourworldindata.org/covid-vaccinations](https://web.archive.org/web/20210320003827/https://ourworldindata.org/covid-vaccinations) and lists the world total as 101.61 million fully vaccinated. * The only trouble is that this includes a bunch of Chinese or Russian...

35% is far, far too high - try 1%

  • The current PM isn't actually stepping down until November
  • It takes time to fail 4 votes and is quite unlikely
  • It will definitely take time to schedule the new election, probably the full 3 months allowed (November + 3 months = 2022)
  • Politicians will lose a lot of approval if they cause an extra election so close to the normal election

I just input the cdf for the 20 historical maxima, adjusted for inflation.

@ethulin @admins This can probably resolve quite a while ago. The US alone hit the target a few days ago.

— edited by PepeS

In 2017 solar was about 9% of all renewable power, according to wikipedia. https://en.wikipedia.org/wiki/Renewable_energy

https://en.wikipedia.org/wiki/Solar_power

However, solar grows by about 40% per year - much faster than the 2.5-3% growth of renewable on a whole. That means we can expect 17% of renewable to be solar in 2019 and 28% in 2021. I expect this to push renewable growth way over 3%.

— edited by PepeS

@WPR Well, looks like 6.9% of children had antibodies between April 16 to July 3. That totals to 72.6% of the population so far.

Edit: Misread 68 children as 68%.

— edited by PepeS

Edit: It's not this simple. See comments. > And splitting behavior is even more incalculable than the allocation of second votes. That sounds pretty bad, but I got curious about this question and it's actually pretty simple. 1. The party that's pushing up the Bundestag size is the Christian Social Union (CSU) 2. To a first approximation, the size will be 46/(CSU vote share) 3. This year they're polling at about 5.8% (vs [6.5% in 2017](https://en.wikipedia.org/wiki/2017_German_federal_election#Results)) # Way more details for the curious: 1. There are...

@AlyssaStevens Since the link in the resolution criteria lists the stocks every week, will this be averaged for all 4-5 weeks of September?

If you think there's a 17% chance of Trump winning and you think 538 is calibrated, then by Markov's inequality they can only give more than 96 at any time in 17+4 = 21% of outcomes. Realistically, they will probably only give 96 in 17+epsilon% of outcomes. So why is the community cdf at 66% for an outcome of 96 on this question?

Ok I see that a lot of this was wrong. Actually this calculation happens for each state, and then a few extra seats are allocated at the national level to balance things. You can see from the 2017 election that in most states the CDU wins most regions with under 50% of the vote so extra seats are allocated.

This makes the calculation difficult, but I think outcomes over 900 are super unlikely.

@(WPR) This is a good point but again, 'testing positive for antibodies' doesn't perfectly cover 'been infected by the virus'. It seems like an almost mathematical fact to me that age groups get infected at similar rates. More concretely, most people of all ages are in local contact networks with mixed age, health status, and proclivity for partying. The rate of infection for an individual is 1 - 1/R_t for their local network. Children have very low R_0 individually but their parents have pretty average R_0 values and any other adults the child or their...