gatekeeper13 wrote: »
e.g CoA. 14 drops, 8 Sunderflame, 6 Embershield, 0 BSW armor. How is this "random"?
But that is random. A low chance of happening, sure. But its random.
Random doesnt mean evenly spread out or fair. And the previous drop has no bearing on the next. Randomness is clumpy.
MrBrownstone wrote: »But why are you trying so hard to get a medium one? You got a heavy already, go get a medium helm and you're set.
Random means that on a sample big enough you should get evenly spread results. So... let's see trials, SunSpire, very popular. 12 people, chests, etc. tons of loot, like 100+ per run. I'd say pretty much statistically relevant with each run, but ok, let's take multiple runs.But that is random. A low chance of happening, sure. But its random.gatekeeper13 wrote: »e.g CoA. 14 drops, 8 Sunderflame, 6 Embershield, 0 BSW armor. How is this "random"?
Random doesnt mean evenly spread out or fair. And the previous drop has no bearing on the next. Randomness is clumpy.
Fully random 1-key is better only if you need other sets too. If you already have other sets and need just the one then 5-key is mathematically better.But to change the topic a bit, after this experience I am starting to think that maybe in the long run, buying those fully random 1-key coffer is better approach. Especially if one has multiple toons, and experimenting with builds, etc. in this scenario you will end up with 5x more shoulders, basically building your own stockpile ready to be used when needed. You just need lots of storage space to keep themWhat do you think?
The thing is player is not expected to make a statistically relevant number of draws in this case. That is not a case when one player will make thousands or tens of thousands draws. Using RNG outside of cases with statistically relevant number of draws for one player is bad game design.18 tries. <snip> Sorry for your bad luck, but nowhere near a statistically relevant sample size.
nafensoriel wrote: »You want them to fix RANDOM by making it less random?
It's not random by any means, it's pseudo-random, meaning the implementation tries to simulate randomness, but obviously it has it's flaws, as in most other games.
It baffles me when people actually do think that luck/unluck in a software program is really random.
it aint broke if it's doing its job innit
(that job being psuedo random and unpredictable)
Part of the issue is sample size as someone said above. In order for data to be at least approximately normal in distribution, we need:n*p*(1-p) >= 10
In this case n, the sample size, is 18. The probability of success, p, could be calculated as 1/6 or about 0.167. (2 monster sets and 3 armor weights gives 6 total options of which 1 is desired) Thus,n*p*(1-p) = 18*0.167*0.833 = 2.5
which is way less than 10. In fact, we'd need the sample size to be about 4 times as large (72 statistical, not ESO, trials) in order to assume some degree of normality, which is to say a reasonable expectation of a somewhat even distribution of results.
So that's unfortunate, but we can still look at the binomial distribution just to see what that tells us.
Ex: What is the probability of receiving 0 medium ilambris shoulders out of 18 coffers? Without going into too much of the formula or calculation detail, the result comes out to be 0.0373 or just under 4% chance of this occurring. So relatively unlikely but not outside the realm of possibility unfortunately.
So now, just for fun, let's try a hypothesis test. This is really spurious because we'd be making the claim that the proportion of drops that is theoretically 0.167 was observed to be 0 in a sample of 18. But what the heck, I'm just sitting in my office right now before class.
Null hypothesis: p = 0.167
Alternative hypothesis: p < 0.167
I'm going to use the P-value approach here, this gives us a test statistic of z0 = -1.89 Calculating the P-value, the probability that z < -1.89, we get P=0.0294. Basically what we can conclude here is that if we repeat this process of buying 18 coffers we anticipate getting less than 3 ilambris medium shoulders in about 3 of 100 repetitions. And unless we were using an extremely low level of significance (0.01 or 0.02 for example) then we can be reasonably confident that we should reject the null hypothesis and conclude that the data tells us the drop rate is in fact lower than 1 out of 6.
TL;DR
- Results are not assumed to be normally distributed with less than 72 coffers.
- The outcome of 0 medium Ilambris shoulders out of 18 is expected about 4% of the time.
- Hypothesis testing tells us the drop rate is actually less than 1 out of 6 for medium Ilambris, but it's hard to get behind this idea at this sample size.
Edit: Lol, just realized I should use a T-distribution not Z for the hypothesis test. Ah well, not reliable results anyway
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