Kayana @ Kayana @ttrpg.network Posts 1Comments 70Joined 1 yr. ago
I rationalize it as "You took some blows so now you have a better pain tolerance".
Hmm, you'd probably have to have access to something like DndBeyond's data to compile such a chart (or use one they compiled). Problem is, there doesn't seem to be anything like that. The only published data visualisations are about races, classes and names.
So I don't think you can just search for it, the only other option I see is gathering that data (if from a smaller sample) yourself, by creating a poll asking for their ability spreads if they used point buy. You could try and advertise it in appropriate communities, and once you feel like your sample size is big enough, you can calculate the percentages.
I wish there was an easier way (and maybe there is and I just didn't look far enough), but from my chair, that's the only option.
Point buy is completely deterministic, so I'm not sure what you mean by probabilities... Are you referring to statistics, like which stat is a certain value most of the time?
Well, one way to easily replicate point buy's range per stat (if not its distribution limit over all stats) would be 7 + 1d8. You could also do: Start every stat from 12, and if you want to increase one, you can do so by rolling a d4 as a bonus (rerolling on a 4). However, to do that you'll have to decrease a different one by another / the same d4. So you'll still have the same range, but like with point buy there's an element of control and choice to it.
Regarding bigger ranges, one way could be using that same method, only with bigger dice (and possibly other starting points). E.g. you could start from 11 and roll a d8, rerolling an 8 if you're adding it as a bonus. That example would give you values anywhere from 3 to 18, and it's much more swingy than 4d6dl. Of course, if the high variance is an issue, you can experiment with dropping highest or lowest on 2d8.
For example, if you're dropping lowest on bonus rolls and penalty rolls, you'll get characters with high highs and low lows, or if you're doing it the other way around, you'll get characters where each stat is fairly equal, without much variance to speak of.
There isn't much more I can say without knowing how much variance and player choice you want to include.
Possible formula: Tax for n-th house = n-th Fibonacci number + 5 * max(0, n - 2). So low numbers like three get penalized by that linear part, and high numbers grow exponentially due to the Fibonacci number.
Huh, interesting... You know, I've never really wondered about Humble Bundle specifically, but you're right, they seem to be selling your run-of-the-mill Steam keys, or at least you can activate them effortlessly in Steam. Maybe it's a case of Steam themselves handing out keys (instead of the publishers) to increase user retention? I honestly don't know, this is all just speculation.
I actually didn't click on your link at first, because I assumed it would just show other stores where you could purchase the whole game instead of a key, so I'm sorry that you had to clarify that.
As far as I know, they do - for Steam keys. If you're selling your game through other stores, not just a Steam key, there aren't any demands placed upon you. The OC might've been talking about that.
Can you even kill something that's already dead?
Gotcha, I didn't catch that on my first read-through.
This seems wrong...
10^17 milligrams
-> 10^14 grams
-> 10^11 kilograms
-> 10^8 tons
So it should actually be 553 402 322 tons, which means that we can do it only using the rice produced in 2022.
But you just completely ignored everything I said in that comment.
Mathematically, that is precisely how O notation works, only (as I've mentioned) we don't use it like that to get meaningful results. Plus, when looking at time, we can actually use O notation like normal, since computers can indeed calculate something for infinity.
Still, you're wrong saying that isn't how it works in general, which is really easy to see if you look at the actual definition of O(g(n)).
Oh, and your computer crashing is a thing that could happen, sure, but that actually isn't taken into account for runtime analysis, because it only happens with a certain chance. If it would happen after precisely three days every time, then you'd be correct and all algorithms would indeed have an upper bound for time too. However it doesn't, so we can't define that upper bound as there will always be calculations breaking it.
It's very pedantic, but he does have a point. Similar to how you could view memory usage as O(1) regardless of the algorithm used, just because a computer doesn't have infinite memory, so it's always got an upper bound on that.
Only that's not helpful at all when comparing algorithms, so we disregard that quirk and assume we're working with infinite memory.
That's a point I didn't actually think about, touché. Let's go through this then:
Before Covid (in my country at least), there was this massive push for more homes, because the interest rates were so low. Everyone was building a house, because it was so very cheap (in interest at least, not necessarily in costs). At that point, wise developers might have decided to not take on any big new projects, focusing on finishing their current ones instead of trying to ride out this bubble.
Then Covid hit and the supply chains broke down. That was sudden and couldn't be expected, I'll give you that. But now, four years later, the main reason (in my opinion) for the low occupancy is the newfound interest for WFH, also resulting from Covid. Who needs an expensive condo in a crowded city if you can have a cheap flat in a small town instead?
So in this case, I'll (partially) retract my prior opinion and instead state that while a crash could've been seen somewhere on the horizon, Covid with all its consequences certainly couldn't have been foreseen.
I'm not familiar with the housing prices in Toronto compared to smaller cities in Canada, but perhaps those developers need to bite the bullet and lower their asking prices, because I'd imagine selling for less is still better than holding onto dead weight, praying for demand to go up again.
Wow, writing the same paragraphs three times... What an abomination of an article.
On a serious note, they shouldn't have been so greedy then and waited until prices had fallen again... This looks exactly like the dotcom bubble crashing because investors just couldn't hold their horses.
That may be true for smaller cities, but in bigger cities it becomes impossible, because there just isn't enough space to house all the people near areas of interest. Cars don't factor in there at all. Give me a subway for the major areas, and perhaps a tram or bus system so you don't need that many subway stations in the residential areas, and you can have car-free city centers.
To be honest, I don't really like it either, which might surprise you considering my last sentence. I just couldn't resist making a small pun myself.
Got a laugh from me, but I did mean only the 'a', not the 'ar'. I couldn't think of any other English word with that sound unfortunately, do you have a better suggestion?
I don't really like including pedestrians in there. Like sure, you can fit a bunch of people in a small area, but another point you shouldn't ignore is the throughput over time, and pedestrians are by their nature rather slow. Obviously if you're looking at shopping in a street lined by shops left and right, then that street becomes tailor-made for pedestrian traffic (and nothing else except perhaps bicycles). But public transport is much better suited for travelling any further distances, and that should be the main focus when deciding to ditch cars.
Try pronouncing the 'a' in pan like the 'a' in large, then you'll end up with a rather well-done pun.