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The results of crafting 300 powered Alien Artifacts
admgreer
Member Posts: 0 Arc User
I dug up my spread-sheet and here are results of crafting over 300 consoles: ( No one can convince me it's random) the Purple/Blue/Green Quality results were accurate running it at %24-%51-%24
SCI: Stealth Module (27), Sensor Probes (25) , Power Insulator (20), Countermeasure System (19), Inertial Dampeners (14), Flow Capacitor (13), Graviton Generator (11), Particle Generator (8), Emitter Array (8), Field Generator (1) 147 Sci Consoles
Eng: Injector Assembly (20), Field Emitter (19), Plasma Distribution Manifold (16), Tetraburnium Hull Plating (10), Parametallic Hull Plating (8), Diburnium Hull Plating, (8) SIF Gen (9) Emergency Force Fields (9), Electroceramic Hull Plating (5), Ablative Hull Armor (5), Monotanium Alloy,(4) EPS Flow Reg (4), Neutronium Alloy (2) Consoles RCS Consoles (1) 120 Eng Consoles
Tac: Directed Energy Distribution Manifold (18), Warhead Yield Chamber (17), Prefire Chamber (11), Variable Geometry Detonators (8), Transphasic Compressor (7), Polaron Phase Modulator (6), Photon Detonation Assembly (6), Tetryon Pulse Generator (4), Ambiplasma Envelope(4), Chroniton Flux Regulator (4), TCD Subspace Infuser (3), Plasma Infuser (4), Disruptor Induction Coil (2), Antiproton Mag Regulator (2), Phaser Relay (0) 94 Tac consoles
I have done some addtional crafting since OP, I have updated the OP with my results.
SCI: Stealth Module (27), Sensor Probes (25) , Power Insulator (20), Countermeasure System (19), Inertial Dampeners (14), Flow Capacitor (13), Graviton Generator (11), Particle Generator (8), Emitter Array (8), Field Generator (1) 147 Sci Consoles
Eng: Injector Assembly (20), Field Emitter (19), Plasma Distribution Manifold (16), Tetraburnium Hull Plating (10), Parametallic Hull Plating (8), Diburnium Hull Plating, (8) SIF Gen (9) Emergency Force Fields (9), Electroceramic Hull Plating (5), Ablative Hull Armor (5), Monotanium Alloy,(4) EPS Flow Reg (4), Neutronium Alloy (2) Consoles RCS Consoles (1) 120 Eng Consoles
Tac: Directed Energy Distribution Manifold (18), Warhead Yield Chamber (17), Prefire Chamber (11), Variable Geometry Detonators (8), Transphasic Compressor (7), Polaron Phase Modulator (6), Photon Detonation Assembly (6), Tetryon Pulse Generator (4), Ambiplasma Envelope(4), Chroniton Flux Regulator (4), TCD Subspace Infuser (3), Plasma Infuser (4), Disruptor Induction Coil (2), Antiproton Mag Regulator (2), Phaser Relay (0) 94 Tac consoles
I have done some addtional crafting since OP, I have updated the OP with my results.
Post edited by admgreer on
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Comments
I'm assuming you had only purple DoFFs working on this projects correct?
def least useful to most useful
very interesting that you didnt get any phaser relays . . .
Here are my findings:
1) The quality of the reward outcome of the "Fabricate Prototype" assignment is guaranteed to match the quality of the success' display name. In other words, if your results say "Blue Quality" the console you receive cannot be anything other than Blue (Rare) quality, in all circumstances. No rare chance to upgrade to a better type, or anything like that.
2) Every console available from our random drop tables is represented. Despite the above sample showing zero Phaser Relays (e.g.), they are included in the drop table as a possible result.
3) All console rewards are equally weighted. This is the part I was unsure would be true, but it is - every item on the reward tables has an absolutely equal chance of being rewarded.
The only possible explanation I can offer at this point, is that it's just a matter of sample size. There are 42 different Mk XII consoles you can receive from this assignment (16 Eng, 10 Sci, 16 Tac) of each quality (Green, Blue, Purple) resulting in the total number of potential outcomes being 42*3=126. When you run a sample size of 300, with almost half that many possible outcomes, your odds are invariably going to be too small to create an big enough picture of the entirety.
Cryptic - Lead Systems Designer
"Play smart!"
More in the interest of curiousity, is it possible for you to data mine the game to see the results of everyone who has run the mission and see if it really does work out evenly over the larger sample size?
Nouveau riche LTS member
He's right, 300 is a very small sample size. I think a better one would be 10,000.
However I will ask you this Borticus. Why are there certain consoles still in the game, especially since they seem to be either archaic/outdated/completely unnecessary? For example, stealth modules? What use are they outside of VERY specific sets of circumstances? It seems that a lot of consoles in general are either under-used or not used at all. Wouldn't it be better to just remove them outright? That way there would be a smaller pool of possible results which would give a more desired outcome.
Would be nice if some of the worthless (i.e will only sell for under 100k on exchange) consoles can be pulled from the toys mission as powered artifacts are costing me a bomb at 1.4-1.5 mill a pop and with the results of consoles no one uses i dont see why i should be shelling out this much for them.
Sure i get some nice drops occasionally but i wouldnt mind poor drops as long as there not just for the majority of the time sensor probes or chron consoles etc.
I've been farming Children's Toys on my 12 Lvl 50 toon's twice a week now ever since the chain was introduced. That means I've run Fabricate Protoype Console 24 times a week for nearly a year now and I can tell you without a doubt that something is definitely wrong with the information you're providing. My results seem very similar to the OP. I don't think it's a coincidence for more than one person to be seeing similar results.
This would seem like a better way to gather results to me if you can do it.
Stealth modules have become the bane of my DOFFing existence. Aux power boosting consoles are not far behind.
I'm sure that the values are as you say, Borticus, but I have to say that the results do not *feel* random. It's almost as though there is a God of DOFF missions smiting me for my hubris. Barring malevolent gaming deities, is there anything else that could be skewing the results? Or am I just remarkably unfortunate?
Neat idea, but maybe the right change is to buff the scaling of science/engineering skills.
- What if 90 skill Particle generators made GW3 hit as hard as a Quantum Torpedo TS3?
- What if a 60 skill difference in (Inertial Dampeners - Graviton generators) made you shrug off tractor beams?
- What if it wasn't so easy to kill crew? What if the difference between 100% crew and 0% crew was 50% as strong as a permanent HE1?
- What if a 60 skill difference in (Stealth - Sensors) meant that you could dance around a science ship with Sensor Scan and still not be spotted?
A good first-order estimate for a sufficient sample size is always the square of the number of elements --> 42 consoles --> 1764 = N
way to go
STOWiki admin.
In general statistics though, 10,000 is usually the accepted minimum accurate sample size. It gives enough room for variance and enough room for outliers to be negated by a standard curve. Since I don't feel like thinking atm, I just shot that out since my stats professors slammed that number into me since college.
With such a number of consoles you need ~10k attempts to get a reliable sample.
FYI i must have been lucky, half of the time i get something useful. Last week, i got a purple monotanium alloy and phaser relay, and a blue shield capacity console. I also had a chroniton console. My guess is that only unlucky people will complain, happy ones don't feel the need to rant on the forums.
God, lvl 60 CW. 17k.
This statement combined with your profile picture had me laughing so hard...
Take a six-sided die. It has... six sides. If you roll it, it will result in one of those six sides facing up. Each side statistically has a 16.6666666666667% chance of landing face-up.
However, this does NOT mean that a particular side will come up one out of six times. It only means that each time you make a roll, each side has an equal 16.6666666667% chance of landing.
If you roll a "1", you will not necessarily get a "1" every six times. You're not going to roll the die six times and be guaranteed a "1". If you roll the die 36 times, you're not going to get equal results for each side. Even if you roll the die a billion times, the results will not be even across all possible results despite each side having an equal chance of landing.
Random is random. A probability statistic only matters to the individual instance, not a group of the same action being performed over and over. If you get a particular result with one instance, it does not change the probability of a different result in a different instance.
(Ex: if you get a "1" result on a six-sided die, it does not mean that you are any more or less likely to get that same or different result on successive rolls)
Raptr profile
I'd love this, if it weren't so true
Seriously though, that's funny.
There is something definitely amiss and while everyone is pointing to sample size issues and "statistically speaking" I can defiantly tell you it is not a sample size issue.
Let us forgo the rarity factor because the op stated those proportion came out the same and were find. Let?s focus on the fact that each console type is not dropping in ?equal? proportion. Is a sample size of 300 sufficient? In statistics, we have two error rates, alpha is the probability of making a type I error (incorrectly rejecting a true null hypothesis) and beta is the probability of making a type II error (failing to reject a false null hypothesis). You only worry about the type II error rate when you do not have a significant alpha (usually >0.05 in most hypothesis testing). When you reject a null hypothesis you have to check is you had enough power (beta and sample size) to ensure you did not make a false rejection.
Now with this primer behind us let us do a simple and quite easy to do statistical test. The type of test that fits this data the best is a chi-square test. For this test, we take our observed values (from the op) and derive expected values. In this case, we know the consoles should drop in equal proportion so the number of expected consoles of a particular type say for science is simply 1/10 = 0.1 * Observed value. The OP had 131science consoles so the expected values following a uniform distribution is 13.1 consoles. He should have received 13.1 of each particular console type (if they drop uniformly). Now for those of you that want to look up the chi-square test there are plenty of hits on Google. Now we have our null hypothesis that says the observed drops = the expected drops and the alternative hypothesis that says the observed drops do not equal the expected drops. I am going to go to the next step.
For the science consoles we get a chi-square value of 31.8, with 9 df, and a probability = 0.000214. Thus, we reject the null hypothesis and the observed drops do not equal the expected drops. Because our alpha is <<0.05 we do not have to worry about a beta error rate or our sample size because the effect is strong.
For the engineering consoles we get a chi-square value of 136.0, with 14 df, and a probability = 4.36x10^-22. Thus, we reject the null hypothesis and the observed drops do not equal the expected drops. Because our alpha is <<0.05 we do not have to worry about a beta error rate or our sample size because the effect is strong. By the way I could only find 15 not 16 engineering consoles.
For the tactical consoles we get a chi-square value of 72.36, with 15 df, and a probability = 1.69x10^-09. Thus, we reject the null hypothesis and the observed drops do not equal the expected drops. Because our alpha is <<0.05 we do not have to worry about a beta error rate or our sample size because the effect is strong.
Thus, sample size is not the issue here because the effect or magnitude of the difference is so strong. Our conclusions are then within each console group, a particular console type is not dropping uniformly. I have my suspicions it is the way the reward rolls and loot tables are structured. Instead of rolling for rarity, then console group, then console type the system is set to roll first for rarity then console type. All the consoles are pooled and we can now test that hypothesis. So our expected number for a particular console type is 1/41 = 0.02439 * Observed Value which means the op should have received 7.65 of each console type if again they drop uniformly.
Running our chi-square analysis again we get a chi-square value of 263.39, with 40 df, and a probability = 1.14x10^-34. Thus, we reject the null hypothesis and the observed drops do not equal the expected drops. Because our alpha is <<0.05 we do not have to worry about a beta error rate or our sample size because the effect is strong. We can say that the consoles do not drop uniformly when they are pooled.
So we can say statistically consoles from the DOFF crafting mission are not dropping uniformly within console type or within the pooled subset. We can also say that with great certainty that the sample size is not an issue because the magnitude of the effects are so great. How is the drop rate then calculated? I cannot answer that, all we can say it is not uniform based on the two scenarios above. More likely the probability of getting a specific console of a specific quality using the OP?s quality rates are:
All Consoles Pooled
Very Rare ? 0.24*0.02439 = 0.005854 = 0.59%
Rare ? 0.51*0.02439 = 0.012439 = 1.24%
Uncommon ? 0.24*0.02439 = 0.005854 = 0.59%
If the OP can provide a breakdown of the qualities we can even go so far as to test that.
I believe you may have mis-interpreted things or the last hundred years of scientific investigation is rendered null and void by that stat professor of yours. I believe what he was talking about was re-sampling statistics such as bootstrapping, jack-knifing, Markovian-chains etc... The general accepted rule for those is a minimum of 10,000 replicates/resamples but with more powerful cumputers today 100,000 replicates are easy. In addition, since we are talking about count based data here and not continuous scale data, measures of central tendency do not really apply.
I can honestly say that in all my years of teaching the people that now teach stats and all the stat work that I do, I have never heard of such a "general rule". Do you have a citation for this because I would be very interested in reading it? I have heard all sorts of things though such as having a sample size 15 times the number of variables to be estimated. Your best bet is to conduct an a priori power analysis but you would need a pre-determined effect size. Also, for the example and discussion here what you are really testing or wanting to examine is IF the data fit a pre-determined distribution. In this case, that is a uniform distribution (all have an equal probability of dropping).
At some point the sample size may even give a difference that only has a statistical meaning. This is not the case when distribution testing or fitting as the greater the sample size the better the fit or lack thereof.
The point is it is quite obvious that the console drops fit a logarithmic or inverse hyberbolic distribution whether that is intended or not.
1) You need some seriously expensive doffs to get max purple % chance. (10 to 20 mill each? I haven't looked in a while)
2) 300 powered alien artifacts represents in the 390 to 410 million EC region.
The OP would need to have gotten 8 to 12 (or more) MK XII consoles of truly high end value (read: MK XII Purple Tac Consoles) just to break even.