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Originally Posted by diogene0
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"Incredibly unlucky" really does not come close to explaining the OP's results in the light of a uniform drop rate. Right now, the most probable event is something odd in the code chain (not necessarily the RNG). So let us go through the logical decision process so everyone can see where we currently stand. If you want to follow the hyethetico-deductive model, we can do that. We have before us five hypotheses that we have to decide on and unfortunately, they are not mutually exclusive.
1 - The OP has misrepresented his data - This is likely not the case because the OP has expressed a genuine concern and took a great deal of time and effort to collect the data.
2 - Borticus has misunderstood the table or the reward process - Again, we can say with certainty this is not the case. Borticus is familiar with DOFF system and their loot table structure.
3 - The observed results are spurious resulting purely from random chance (i.e. the sample does not reflect the population) - This cannot be denied, however the probability of such an event from the analyses provided is extremely improbable. Remember we have disproven the null hypothesis that the observed distribution and the expected distribution are the same. They are different and the results of those tests provide us the probability of that difference occurring by random chance alone.
4 - The observed results represent a sampling inadequacy (i.e. the sample size is not large enough to detect a difference) - Again, I have gone through some quite basic statistical power analyses that disprove this option. At this point whether people wish to believe it or not, the sample size issue is no longer a valid argument. We have a sufficient sample size to make a determination on the observed differences. Those still arguing a sample size issue are doing so from belief, feelings, or emotions and thus have no logical grounds anymore.
5 - Somewhere in the game code lies an issue that is skewing the observed results from the expected results (the drop rate in the loot table) - Somewhere in the chain of code from the jobs results to the draw from the loot table, the results are getting skewed. This could be anything and it does not matter if we specify it or not. We know it lies in that path because the initial roll on quality is working and we know that the values for the consoles in the loot table are equal (uniform). Something is breaking down in the process from point A----> point B.
We
CAN rule out hypotheses 1 and 2 based on the character and knowledge of the two parties in question.
We
CANNOT rule out hypothesis 3, but we can say it is highly improbable.
We
CAN rule out hypothesis 4 because we have already determined ~300 consoles is enough to make a statement on the observed difference.
We
CANNOT rule out hypothesis 5 because none of the parties know the code process.
We have two options here to decide definitively between the two:
1 - Obtain more data of similar sample sizes (replicates) to see if the observed pattern the OP has holds true or is falsified.
2 - Examine the code path for potential factors skewing the results.
If we are to make a determination, now between the last two competing hypotheses without any additional information, we have to invoke Occam's Razor. That invocation would determine hypothesis 5 as the most likely, because it is the simplest and most parsimonious. Given the evidence, your fictional sleuth would also logically deduce hypothesis 5.
Now, again just because you or anyone else is getting consoles you feel are valuable, your statement does not improve the position that the results fit hypothesis 3 or 4. Such arguments are from an emotional standpoint using a qualitative assessment as fact. Such arguments are definitely suffering from a conformational bias, as the focus is on the consoles that are deemed valuable rather than the sample of consoles as a whole. Second, such statements are purely qualitative. Those qualitative metrics are erroneously being used to afford judgment on whether consoles are being obtained in equal proportion and against the quantitative measures (which is the crux of this entire argument). Third, the qualitative statements of, "I regularly...", "I got three of...", etc... also suffer from a bias because they are only providing a partial result and cannot be used to confirm or refute the quantitative data. Our process has moved beyond the qualitative now and we must focus on the quantitative.
The best course of action we can do now is provide more data to confirm or refute hypothesis 3 and pursue an investigation to confirm or refute hypothesis 5. Both are underway.