Other players mining before you affects your hit rate

kingofaces

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Tony KingofAces Hans
We just wrapped up the testing described here. Thanks to Leroy Casper Hunter and Leeloo Leeloo Mountain for helping out. There have been competing ideas out there on how other miners affect your hit rate, so I figured we'd try to some formal science on it.

To sum it up, this was designed like I would any scientific experiment at work to give this data a bit more rigor to have actual testable data. The three of us each dropped en/ore at the exact same coordinates with about a 5 minute buffer between us. Leeloo went first, then Casper, then myself. If someone caught up to the person ahead of them, we typically gave at least a minute or two buffer if not closer to 5 minutes. These were all done with F-101's with no attachments, etc. so everything was standardized for depth, search radius, etc. There were 30 drops for each type, or 60 total drops per person.

Hit rate

The first miner had 26.7% HR, second was 6.7%, and third was 5.0%:

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As you increase the number of miners (primarily having more than one miner dropping on recently mined areas), hit rate significantly decreases. For the formal research statistics end of things, I used a logistic regression with hit rate as a response, and miner number as the independent variable. One way to look the above graph is if the confidence intervals overlap, you cannot say those average hit rates are significantly different (i.e., they are only numerically different due to randomness). The confidence intervals basically mean that if you repeated this study 100s of times or had a much higher sample size (maybe 10k PED worth), we can say with 95% confidence that the "true average" falls within those limits without needing to actually do that much sampling.

Likewise, the logistic regression line had a negative slope (-1.2), and was also statistically significant p = 0.000982, also confirming that as you add more miners, hit rate goes down. P-values under 0.05 are generally the threshold for significance, so there's next to no question that we ruled out randomness in this experiment and the differences we saw are due to the number of miners.

Hit rate however, was not zero for the 2nd or 3rd miners. Some claims could have been missed by the previous person because they found a claim closer where they dropped even though both were within their search radius. Another reason is claims "respawning". As the third person in the chain, I did have one claim appear right next to me and not on the edge of the radius as you'd expect with the former example.

TT returns

I also analyzed the TT returns from these runs since it was possible claim size might be different depending on your hit rate. This gets a little trickier to analyze because that data doesn't fit a normal distribution and are instead bimodal (a bunch of zeros for the NRFs, and another peak for actual claims). I won't get into the nuts and bolts of that one, but in order from miner 1 to 3's total TT: Leeloo 33.48, Casper 12.42, and myself 16.55 PED. There would be issues trying to graph that up due to the non-normal data, but I analyzed the total PEC with a zero-inflated poisson regression to take care of those. The short of it was that Leeloo's average TT per drop was significantly higher than Casper (p = 0.04155) or myself (p = 0.00342). Casper's and my TT per drop were not significantly different (p = 0.1988).

Conclusions

Essentially, TT returns declined with declining hit rate as more than one person mined an area. This go a good ways towards settling the question of whether other miners affect your hit rate or TT.

There are a few followups mentioned in previous threads now that we found there is a difference due to other miners:

  1. Does the first miner only deplete claims at the depth they hit at, or at any depth within the radius (i.e., due claims exist in a disc, or cylinder)? This could be done in quick succession with at least two people at the same coordinates again. It would need to have enough range in depth treatments to not overlap much, so maybe like 200, 500, and 800m.

  2. What is the rough respawn rate? This could be done by repeating this again, but instead of 5 minute intervals, spread it out by increasing wait time of 30 minutes, 1 hour, 2 hours, etc. for each person to see when it's "safe" to mine the area again.

  3. Do others in the same zone affect your mining if you don't overlap drops? No need for staggering here again, just do 30+ drops in the same general vicinity and compare HR again.

I would like to take another weekend to test either 1 or 2 now that we have this wrapped up. I'm thinking March 9, but I'll see what people think about what we have so far before setting up the next round of testing.
 
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Nice bit of testing. I have always had a feeling that was the case.
 
Thank you very much King :) hope we get plenty more testing to do !!!

I'll link this thread also to my mining guide

Still some questions

What if different finders (read different depths)

Do deeper finders give the same results

Longer waiting times (I mostly work with 2 hour timers)

Different spawn times for different ores/enmatter?

As MA stated that skills do matter, we might do the same tests with higher (deeper) finders to compare, cause with that F-101 my HR was way of lol Maybe its because it's the F-101 ...
 
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Was that a 16.55 PED or 165500 ped test because its late and I can't read properly.
I hope its not the first case.I've been educated that a test should be conducted for a period of at least 6 months + with a very large sample of ped spent so you can remove any variation possible.
Anyway good luck :)
 
Was that a 16.55 PED or 165500 ped test because its late and I can't read properly.
I hope its not the first case.I've been educated that a test should be conducted for a period of at least 6 months + with a very large sample of ped spent so you can remove any variation possible.
Anyway good luck :)

there are different kinds of tests

like when you wanne see if you can find stuff on the same coordinates with autodropping without moving and you see that after the first hit the next 30 drops are all NRF then you dont need to do this test for 2 weeks and drop a million times. you can see the result after 2 minutes with a certain degree of certainty thats upwards of 95%.

if you wanne test the refresh rate you would have to do this for maybe few hours, depending on when you start getting hits again.
 
interestingly the second and third miner have roughly a fourth of the hitrate but have about half of the TT

you could also test this with doing ore once and enmatter once, with a few days inbetween. i assume the higher TT in regards to hitrate is due to more ore hits. could be luck but could also be a statistically significant difference
 
The sample looks a little small.

Repeat it 100 times, if the numbers are still the same I buy it.
 
The sample looks a little small.

Repeat it 100 times, if the numbers are still the same I buy it.

I'm pretty sure even if we did this 1K times, results would be the same, but I'm willing to go for it.

EDIT : that's also the reason why I almost never mine during weekends
 
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Thank you very much King :) hope we get plenty more testing to do !!!

I'll link this thread also to my mining guide

Still some questions

What if different finders (read different depths)

Do deeper finders give the same results

Longer waiting times (I mostly work with 2 hour timers)

Different spawn times for different ores/enmatter?

As MA stated that skills do matter, we might do the same tests with higher (deeper) finders to compare, cause with that F-101 my HR was way of lol Maybe its because it's the F-101 ...

Ty for doing this testing and surply the data. Yes its only small sample and there is other variables to consider. I would help, but on diffrent planet. I had some say its no point minging this area i alreay done. I did mine it and found gold and run was ok. The diffrence was his 105 522m depth and my milf 900m depth. Also i dont know if skill level has factor or just what tool you can use. Are all 3 of you simlier level?
 
As a hypothesis test I buy it 100%. The server/s keeps track of areas. But is this unique to mining or also true for hunting in same area or even crafting? I wonder how large the respawn areas are, if set to predetermined area sizes or dynamically determined. Is the return also a combo of 1. Local activity in the area + 2. Global activity on the planet? But I guess its not so easy to just say "More miners in an area = Less finds" if more acitivity in an area also means that players spend more in that area. Does that also mean that our spending in an area also determines how much there is to find there? Or is the entire spending on a planet spread out evenly on that said planet or even universe wide?

I have experienced fantastic hit rates and back to back globals and multis in more or less abandonded areas.

Maybe one way of do some further testing is to get in contact with some land owners. Don't they have access to stats regarding mining activity in their areas? That way you could correlate activity vs returns maybe.
 
with same setup cycle even 10k ped and results would be intresting to see.

Good data thank you.
 
The sample looks a little small.

Repeat it 100 times, if the numbers are still the same I buy it.


When you're using these statistical tests, they're designed to use these sample sizes to make predictions of the "true average" you'd get if you did 1000+ drops instead. Those confidence intervals basically mean that if you repeated the study again, 95% of the time the averages would fall within that range. The higher the sample size, the more that confidence intervals shrinks, but the averages generally only bounce around within those limits as you increase sample size.

Something we never do in science is sample so much that we can get a near direct estimate of the true population size through sheer force. It's expensive and time consuming. If the samples we pull come from a random distribution though (i.e., a random number generator with some set average), 30+ samples is typically enough as long as your comparisons are properly designed and you're using the right statistical tests.

with same setup cycle even 10k ped and results would be intresting to see.

Good data thank you.

Likewise, those p-values I give already address that. There's only a 0.0982% chance that 10k ped drops that the negative trend in the graph wouldn't hold true. Similar for the TT test, Leeloo's and my TT would still be expected to be different at that high of a sample size with about 99.7% confidence in that difference. That's the fun thing about research statistics. You can determine what would happen at high sample sizes with much less.
 
interestingly the second and third miner have roughly a fourth of the hitrate but have about half of the TT

you could also test this with doing ore once and enmatter once, with a few days inbetween. i assume the higher TT in regards to hitrate is due to more ore hits. could be luck but could also be a statistically significant difference

I'm really cautious about directly comparing the actual numbers from TT because of the need for that zero-inflated model I mention. With that statistical tests, I can definitely say miner 1 had more than miner 2 or 3, but the way the model quantifies that doesn't boil it down into simple math we can directly compare to hit rate. Those total TTs I gave pretty much can only give a general idea, but they have the same problem as averages not being "correct" because of all the zero data.

As for type affecting TT (just happening to get more ores with higher TT than enmatter claims), I forgot to mention I did look at that. I can actually account for that in the model as a covariate. That effect doesn't change the model at (p = 0.1911), so the results pretty much stay the same.
 
Thank you (all three of you) for this interesting experiment. At the very least, it now satisfies my nagging query as to why I can sometimes get up to 20 NRFs in a row while mining planetside. :laugh:

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Going off on a tangent now though
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After reading this, two additional questions now pop up.
  1. Is it safe to conclude (from this) that there is at least a 2D (x,y) spatial distribution to the mining claims? If yes, it would then lead me to wonder if there isn't a 3rd dimension (z) to its distribution. Would going through with this again with everything done the same way but using three different avg. search depth finders, but with the same search radius, result in any difference in the hit rates?
  2. How much time in between (the drops) do you think it would require before there is no longer any interference (in hit rates) between the three miners? 5 minutes and 10 minutes is definitely out right? So maybe 30 minutes, or perhaps even 1 hour?

Lastly, it might probably just be smoke and mirrors, but I can't help associating your hit rates in this particular manner/pattern.
  • 1st Miner (Hit Rate): 26.7%
  • 2nd Miner (Hit Rate): 26.7% * 26.7% = 7.1289% (in comparison to the 6.7%)
  • 3rd Miner (Hit Rate): 26.7% * 26.7% * 26.7% = 1.9034% (in comparison to the 5%)
Its almost like having the probability of hitting a claim to be around 26.7% and then the 2nd/3rd Miners' to be analogous to trying to hit 2/3 consecutive (in a row) claims in the exact same spot. And any discrepancy (in hit rates) can be explained off due to "luck" and "server's regeneration of claims". :scratch2:

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As for the TT part
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Would it be possible to separate the tally for number of claims and TT of enmatter and ores? Then do an average to see if there's a difference in TT values (of the enmatt and ore claims) between the three miners.

It would be interesting to see if MA does any "compensation" to the 2nd and 3rd miners for their "reduced hit rates".

;)
 
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Thank you (all three of you) for this interesting experiment. At the very least, it now satisfies my nagging query as to why I can sometimes get up to 20 NRFs in a row while mining planetside. :laugh:

----------------------------------
Going off on a tangent now though
----------------------------------
After reading this, two additional questions now pop up.
  1. Is it safe to conclude (from this) that there is at least a 2D (x,y) spatial distribution to the mining claims? If yes, it would then lead me to wonder if there isn't a 3rd dimension (z) to its distribution. Would going through with this again with everything done the same way but using three different avg. search depth finders, but with the same search radius, result in any difference in the hit rates?
  2. How much time in between (the drops) do you think it would require before there is no longer any interference (in hit rates) between the three miners? 5 minutes and 10 minutes is definitely out right? So maybe 30 minutes, or perhaps even 1 hour?

Lastly, it might probably just be smoke and mirrors, but I can't help associating your hit rates in this particular manner/pattern.
  • 1st Miner (Hit Rate): 26.7%
  • 2nd Miner (Hit Rate): 26.7% * 26.7% = 7.1289% (in comparison to the 6.7%)
  • 3rd Miner (Hit Rate): 26.7% * 26.7% * 26.7% = 1.9034% (in comparison to the 5%)
Its almost like having the probability of hitting a claim to be around 26.7% and then the 2nd/3rd Miners' to be analogous to trying to hit 2/3 consecutive (in a row) claims in the exact same spot. And any discrepancy (in hit rates) can be explained off due to "luck" and "server's regeneration of claims". :scratch2:

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As for the TT part
------------------
Would it be possible to separate the tally for number of claims and TT of enmatter and ores? Then do an average to see if there's a difference in TT values (of the enmatt and ore claims) between the three miners.

It would be interesting to see if MA does any "compensation" to the 2nd and 3rd miners for their "reduced hit rates".

;)

As King already mentioned we are going to do a lot more testing, the more questions, the more testing :)

About the repop or respawn for claims, and now I speak from my own experience only, I wait 2 hours before redoing the same zone over and over again. I tried shorter times, but then my HR/TT return was less, a lot less.
If this is the same on any server or for other resources I never tested them all.
Those I know who mine the same way, try already after 1,30 hours but they go for specific ores most of the time.

Another thing that is worth mentioning is that you never can say that you didn't find anything. Either you will find a claim some 1 has missed, most likely because he/she didn't drop a 2nd bomb at the same place (rebombing) or there is a safety barrier that you will get a minimum if you keep mining in that zone.
Then I'm thinking of around 10-20% HR or even 25%
Either way if you get a HR of 25-30% you should consider stop mining there or keep a very close eye on your TT return so it doesn't go under 90-80% (IMO)
These % are all for mining without amps/enhancers
 
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Thank you (all three of you) for this interesting experiment. At the very least, it now satisfies my nagging query as to why I can sometimes get up to 20 NRFs in a row while mining planetside. :laugh:

----------------------------------
Going off on a tangent now though
----------------------------------
After reading this, two additional questions now pop up.

------------------
As for the TT part
------------------
Would it be possible to separate the tally for number of claims and TT of enmatter and ores? Then do an average to see if there's a difference in TT values (of the enmatt and ore claims) between the three miners.

It would be interesting to see if MA does any "compensation" to the 2nd and 3rd miners for their "reduced hit rates".

;)

Leeloo covered the rest pretty well. For the question of TT, I addressed this same question in my reply before yours. When you add resource type (ore vs. enmatter) as a covariate in the model, you can account for the fact that each type has a different base TT claim size. Accounting for that difference doesn't change the results (p = 0.1911) on TT. So basically, no compensation.

I mentioned it in another thread, but when you pull random samples, you are going to get "streaks" as a part of that randomness (10 heads in a row in a coin flip). I'm pretty convinced that this is what is going on when people see "compensation" happening for a bad run. It's a well known problem that people looking at raw data without appropriate statistical tests will see such trends in the randomness and think they truly exist. If someone repeated the exact same study a bunch of times or with a single higher sample size, they could test the "compensation" question further and rule out that randomess, but I'm planning to focus on the other things you mentioned that are also cheaper to test. I'll probably draw up a new thread in a few days on the next round.
 
Thank you very much for doing this experiment and for sharing the results.

Regarding this part:

Something we never do in science is sample so much that we can get a near direct estimate of the true population size through sheer force. It's expensive and time consuming. If the samples we pull come from a random distribution though (i.e., a random number generator with some set average), 30+ samples is typically enough as long as your comparisons are properly designed and you're using the right statistical tests.

That is only valid with some strong assumptions: independence of the observations, low variance and some sort of stationarity (i.e. that results do not depend on time and location). I am not sure any of these assumptions hold in this case, so I would not claim that the p-value for example is very accurate. Of course, the effect size is very convincing and would likely result in a high significance with a more elaborate model.

I find your analysis and conclusion quite convincing but I think it can be strengthened if this test repeated in different setting: different locations/times, wider time intervals and more avatars (easy to say, as I have barely time to play and cannot offer any help).

Again, thanks and keep up the good work.
 
Thank you very much for doing this experiment and for sharing the results.

Regarding this part:



That is only valid with some strong assumptions: independence of the observations, low variance and some sort of stationarity (i.e. that results do not depend on time and location). I am not sure any of these assumptions hold in this case, so I would not claim that the p-value for example is very accurate. Of course, the effect size is very convincing and would likely result in a high significance with a more elaborate model.

I find your analysis and conclusion quite convincing but I think it can be strengthened if this test repeated in different setting: different locations/times, wider time intervals and more avatars (easy to say, as I have barely time to play and cannot offer any help).

Again, thanks and keep up the good work.

Thanks for reply and those test will be coming up in the next weeks when everybody can :wtg:
 
Thank you very much for doing this experiment and for sharing the results.

That is only valid with some strong assumptions: independence of the observations, low variance and some sort of stationarity (i.e. that results do not depend on time and location). I am not sure any of these assumptions hold in this case, so I would not claim that the p-value for example is very accurate. Of course, the effect size is very convincing and would likely result in a high significance with a more elaborate model.

I find your analysis and conclusion quite convincing but I think it can be strengthened if this test repeated in different setting: different locations/times, wider time intervals and more avatars (easy to say, as I have barely time to play and cannot offer any help).

Again, thanks and keep up the good work.


Some of that is addressed in my next round of testing thread, but the model assumptions are a big one (and I was the oddball who actually liked research statistics in grad school, so I love to talk them).


  1. Independence of observations shouldn't really be an issue unless someone is going to claim what you found in previous drops affects your later hit rate (or some form of autocorrelation). I didn't find any evidence that something like that was going on when looking at the model data.

  2. Low variance isn't a requirement, but maybe you meant homogeneity of variance is (i.e., not having highly variable variances)? The logistic regression is already tailored to dealing with this to a degree, and I didn't find any evidence of overdispersion either as another check on that.

  3. The time factor would largely be minimized by us all testing in a fairly short window. For a location ( x% higher or lower hit rates for all of us), that would really matter for the purposed of this experiment. That or an interaction effect (miner 1 stays the same, but miner 2 and 3 have even lower hit rates), would get more into fine tuning if you wanted to really model exactly when and where someone should mine. If this were a full blown field study where I'd be putting out recommendations like that, I'd definitely want more locations. Just for showing that such an effect can happen though, this design did the trick, and it'll be validated to some degree in the next round of testing.

I'm glad people are having fun poking around on this subject, so I'll keep things going for a bit.
 
the thing is that this test has some medium sized faulty factors in it.
for example it seems that they dropped directly after each other. given the size of the planet and the amount of players id argue, that realistically nobody drops a few seconds after someone else. a more ralistic approach would be to drop like 2 minutes later. best would be to do the same test with 1 minute break, then 2 minutes, then 5 minutes, 10 minutes and then 15 minutes.
next thing id argue is what happens if the finders have a different search depth and not overlap by 100% like everyone using the same finder. id say the chance that the miner before you used the exact same finder with exact same enhancers is medium to low. so there should be above test done with different finders as well. maybe even with same finders but different enhancers.

the problem is we dont know how the system determines if you get a hit or not. and as we dont know it yet we need to test out which of the possible factors reduces the hitrate. in this example many of them havent been tested. so the only thing this test shows if if you have the exact same finder as the person before you and you drop just seconds later than him then the hitrate will most likely be pretty bad.

on top of that 30 or 50 drops is not really enough. e.g. the it could be more like condition crafting where you probably get a lot higher claims and probably have a higher chance for a big payout. but this would have need to be done over thousands of drops, that probably nobody will ever make. one hint that this might be true is that person A gets a 26% hitrate with 33 ped TT while the other miners have about a fifth of that hitrate but only have about half to a third of the TT value while it should be a fifth as well so there is definitely something different. sadly this hasnt been tested out further.
 
the thing is that this test has some medium sized faulty factors in it. . .

Most of these incorrect assumptions have already been addressed in this thread or the followup that we planned to do after this. To reiterate a few though:

on top of that 30 or 50 drops is not really enough

This has been an extremely common mistake in these threads, which is why I bring it up first (more details on why this in incorrect is in other replies) You don't directly compare averages with just 10s of whatever sample size you're working with. No one did that here though. Most people know that, but most don't know you don't literally go and do thousands of samples. Most any intro research statistics course goes over these details, but the statistical tests used here for those averages are designed to approximate what that true average would be at say 10,000 samples based on a smaller sample size and determine how likely a legitimate difference is between treatments as opposed to random chance.

That's why us scientists use them in almost any peer-reviewed articles. 30-50 drops per treatment is already much higher than many published studies that would only use 10-15 as a sample size for a simple experimental design like this one. ~30 is generally considered pretty good with data that has variation like this. Being binomial (hit or miss) helps a lot since those distributions need smaller sample sizes than something closer to 100-300 samples to detect small differences in TT for things like claim size vs. finder decay. There's also not really any evidence that we have power issues since that deals more with false negatives as opposed to false positive. Since we detected a difference, that would instead be a question of false positive or not, and that's built into the tests already where increasing sample size doesn't really change that at this point. That both miners 2 and 3 had lower hit rates just makes the case that a false positive there is even less likely.

tl;dr statistical significance is what tells the story here, not so much sample size or raw averages even though they play in to those tests.

for example it seems that they dropped directly after each other.

I suggest rereading the first posts of this thread. The intent of this was to determine if other miners can affect your hit rate at all. Of course testing was going to occur at the smallest interval where an effect was most likely. People were claiming this didn't happen at all, so the first step was to try to force the effect with a narrow interval. After that, the second round of testing was looking at how long that effect last for, which looks to at least be < 15 minutes. That means the effect generally only is going to be seen "in the wild" at places like Ashi or other small high volume areas (maybe right around TPs).

next thing id argue is what happens if the finders have a different search depth and not overlap by 100%

I have some later testing between and F-106 w/ 7 enhancers vs. no enhancers, and claims are practically nonexistent on the second drop if you drop once shallow then drop deeper the second time anyways, so it's not really a depth overlap issue. If depth overlap mattered, the results in the graph in this thread would have looked different than just the initial decrease, and that depth testing I just mentioned more or less replicated the graph in this thread. It basically looks like the z-plane (depth) doesn't affect hit rate in general, but rather the x-y plane. Depth is more about resources type (and generally better MU).

That didn't matter here though since we were looking at what the rough respawn rate was if you were dealing with the situation in this round 1 thread. At the time, that was before my later testing, so testing at the same depth would have accounted for the same scenario if depth overlap mattered just to be on the safe side. If we had varied depth in this or round 2, that would have been a confounded experiment, and someone could have said the hit rates differences or lack thereof could have just been due to an untested depth effect. This design instead accounted for depth.

the problem is we dont know how the system determines if you get a hit or not.

For the purposes of these two rounds of testing, that doesn't matter. All the mattered is what you do in any basic experimental design. Standardize what you can, and account for uncontrolled variability in the rest of your experimental design. We deal with "black boxes" all the time in science, so this was just testing what happened to average hit rate as you changed time between drops. If the baseline hit rate of that area changed over time, that would have been accounted for with everyone mining roughly sequentially (i.e., blocking by time). That also applies to round 2 to a degree.
 
did you do the f106 with and without enhancers drops urself or over 2 persons, one with enhancers and one without? otherwise that test is also flawed/ needs to be repeated with the other at least

and yes, i know what you wanted to show and thats fine. but reading through some replies here it seems that many think that this is now over and they know everything. thing is, this test just shows a tiny part without countertesting different variables. but this needs to be done or the whole hypothesis could fall over.

i dont mean to discredit your testing, i just wanne show that there is tons of stuff missing to understand this mechanic. i mean sure, one step at a time but when those steps arent taken at all then we cant really say much.
for example what if the hitrate is completely normal, when dropping just 1m apart from the first miners drop. or what if one minute later, or 5 minutes later the hitrate is completely normal? then your test is nice to see that there is some connection but in reality it wouldnt have any impact at all. and important to test is how it affects the reality of a miner as well
 
did you do the f106 with and without enhancers drops urself or over 2 persons, one with enhancers and one without? otherwise that test is also flawed/ needs to be repeated with the other at least

That was just by myself. There's no indication in either set of data that the results change whether you have multiple people dropping like we did here or if you do it yourself. You still get a statistically significant lower hit rate on the second shortly-after drop regardless, so that's more replication on this that I've been doing while testing other things. It's possible to still get a claim on the second drop, but that's the point between when the radius has been cleared and when whatever the respawn rate is has brought claims back to whatever "full" density is, hence the reduced by non-zero hit rate.

or what if one minute later, or 5 minutes later the hitrate is completely normal?

I linked to it earlier, but we tested exactly that in round 2. You generally don't see reduced hit rate in that area after 15 minutes. It's possible the respawn rate varies either by location (respawn of specific resources is a slightly different topic), but that's up to individuals to test at this point.

Basically, a lot of your questions are things we already accounted for when designing these tests.
 
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That didn't matter here though since we were looking at what the rough respawn rate was if you were dealing with the situation in this round 1 thread.

so did only the first droper get claims while everyone else who droped in the same location right after him did get nothing at all?

If no, then i highly doubt that spawns/respawns is a thing...
 
so did only the first droper get claims while everyone else who droped in the same location right after him did get nothing at all?

If no, then i highly doubt that spawns/respawns is a thing...

Just to be clear on which is being discussed, that's in this thread (round 1), and all in the original graph:

attachment.php


Those are non-zero hit rates, but still significantly reduced even after the first person dropped until the entire radius was empty. Miner 2 was 5 minutes after miner 1, and miner 3 was 10 minutes after miner 1.

In round 2, we basically repeated this, but extended the wait time between drops. With the second miner being 15 minutes after the first "clearing" miner, there was no difference in hit rate:

attachment.php


Edit: grabbed the wrong graph before, should have been hit rate, not TT

Basically, something fairly consistently was happening between 10 and 15 minutes where the respawn rate or whatever you want to call it was adding a few claims early on, but didn't return it to normal hit rate until about 15 minutes without any mining there prior to the last drop. Regardless of what it's called, hit rate drops after a spot is initially mined, and "something" replenishes it over time at whatever rate that is.
 
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but why is the tt from second and third dropper not a fifth of first dropper, while the hitrate is a fifth for both (approx)? it seems the hitrate is lowered by 75ish % but the tt return just by 50ish%. so theres some correlation there. would be interesting to test this further
 
but why is the tt from second and third dropper not a fifth of first dropper, while the hitrate is a fifth for both (approx)? it seems the hitrate is lowered by 75ish % but the tt return just by 50ish%. so theres some correlation there. would be interesting to test this further


TT/drop pretty much tracked hit rate here. Remember you can't be talking about fifths, etc. here, just statistical significance. Miner 1 (Leeloo) had both significantly higher hit rate and TT / drop than both miner 2 and 3 (Casper and myself), while both 2 and 3 had significantly lower hit rates and TT / drop than miner 1, but there were no differences in either measure between 2 and 3.

I did mention this:

but in order from miner 1 to 3's total TT: Leeloo 33.48, Casper 12.42, and myself 16.55 PED

Those are just totals and not comparable. I also mention those totals are from non-normal distributions (e.g., skewing), so those shouldn't be used in any comparisons. That's why I used the zero-inflated poisson regression where those averages don't really apply, but gave those numbers with that caution anyways just for a reference point. When I did run those models, I didn't get any evidence contradicting that TT/drop proportionally changed with lower hit rate, but as I mentioned in the OP, presenting those zero-inflated models gets a little trickier compared to the simpler statistics, so I didn't get that far into the nuts and bolts for the purposes of this post.

That said, I went back into the data, and the back-transformed averages of TT/drop were:
Leeloo: 0.344
Casper: 0.120
myself: 0.080


If you plot those against hit rate, it's basically a linear decrease in TT as hit rate decreases. Keep in mind that's also accounting for an average across ore and enmatter (i.e., 60 drops per person). Basically, TT doesn't increase or stay flat as hit rate decreases.
 
what i'm curious about, did you get some multiplier shortly after the testing?
 
hmmm... so don't mine where someone else has? Wonder if mining on different planets and 'indoor' might get you different results... Seems like the less popular planets might actually have some use since the population is lower?
 
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