That is very cool. Rich asking directly for support is straight forward, and I like it. This reminds me of Zed's post on why he switched to using the AGPL license - also straight forward.
I have never really gotten into Clojure, but I did take Halloway's book "Programming Clojure" to the dentist this morning and I may give the language another look.
3 out of 4 corporate sponsors are on the east coast (MA, MA, NY, CA).
EDIT: apparently thats uninteresting? I find it interesting considering the balance of funding in the industry. Not only do I expect more west coast companies, I expect far more of them. This could be due to (a) clojure is more popular there, (b) east coast companies have fewer opportunities for getting their name out, or (c) they are more likely to donate money. Maybe someone has some insight here.
EDIT 2: now, 4 out of 5 sponsors are on the east coast (NC, MA, MA, NY, CA) This may be biased by the time zone, as the day is just starting on the west coast.
Confidence intervals are based on both the sample size and the standard deviation. Given the 100 mile radius of 3 out of 4, you can have some confidence that this is not random. It is quite likely to change with new samples, but it is not meaningless.
> Confidence intervals are based on both the sample size and the standard deviation.
And since we don't know the standard deviation, we need to estimate it from the sample. So we need a lot of samples for that.
> Given the 100 mile radius of 3 out of 4, you can have some confidence that this is not random.
All the "100 mile radius" tells you is that its concentrated in areas with programming companies. It's not surprising that there are no contributions from Nebraska.
> It is quite likely to change with new samples, but it is not meaningless.
If the (unknown) probability of a corporate donation coming from the east coast is p, and we have N samples, then the chance that at least N-1 come from the east coast is p^N + choose(N, 1) (1-p) p^N. When N=5, if p = 0.5 then there's an 18.75% chance that we'd see 4 out of 5 donations from the east coast, just by chance.
For it to be significant at the 1% level, you need p = 0.28. So even if the west coast were 3 times as likely to donate as the east coast, you would still have 4 / 5 corporate donations from the east coast 1% of the time.
Thats a simple way to look at it (binary East vs West), but it does simplify the math. Your conclusion is true but rarely applicable. A better conclusion is that there is only a 5% chance of a more than 25% west coast bias, and there is most likely a 30% east coast bias. Which brings us back to the original question of why that might be. The best hypothesis so far is physical proximity to Rich.
That would make the most sense. He probably does more presentations in the area, and I bet people are more likely to donate money to someone that they have met.
Your expectation that more donations would come from well-funded regions relies on the assumption that well-funded companies are more likely to donate. The opposite may be true, since the founders of bootstrapped startups can make such decisions without concern about what their financers think about it. The first corporate sponsor on that list, Snowtide, is bootstrapped. I don't know about the others.
This sample-size too small thing is becoming ridiculous. You do realize that although something might not be significant, in a hundreds of situations in real life, you are perfectly willing to draw real conclusions from a sample-size of 1?
Stupid example: You are with a group of people, and wonder if it is safe to swim in this river. The first person that walks in gets grabbed by a crocodile. Do you ridicule the rest of the group for not going for a swim? Especially since the only crocodile you observed will not be needing another meal.
Of course not—the potential downside from getting that wrong is getting eaten by a crocodile, and the potential upside is that I get to swim. I demand much more confidence from my decision making process because the risk-reward is so different. Further if I update my priors in a Bayesian manner the fact that of the sample size of 1 person going into the river, 1 person got eaten is somewhat worrying. But because you're not giving me any information, my prior is impossible to calculate. If this is a river in California I would be rather surprised to see a crocodile. If this was the Nile delta I would not. Etc.
Here the downside to getting things wrong is much smaller, so it's much easier to hold out for more precise data before making any claims.
158 individual contributors so far. I'm impressed, although it's just 8% of the target number. Many people must be finding Clojure more usable than I do. (I like to get a backtrace with the location of the error, when errors happen, at least like in Python)
What is the target number, and where did you find it? Your 8% estimate seems very low, and does not agree with the graphic progress meter in the upper right which is at around 55%.
The graphic represents the goal in dollars. nearestneighbor said 8% of the target number of individual contributors. It appears that each corporate sponsorship is worth about 200 individual donations (10% of the targeted 2000 individuals).
I contributed, even though I don't use Clojure on a daily basis. However, I do think it's something that I'd like to see a version 2 of, so it was a worthwhile donation for me.
I have never really gotten into Clojure, but I did take Halloway's book "Programming Clojure" to the dentist this morning and I may give the language another look.