Difference between revisions of "User:Hakazumi/Test Chamber"

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*Dodges/targeted hits count while {{Status|Awakening}} is active:<br />[https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.60%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D+-%3E%220.05%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 260 samples needed to confirm if it's 60% like GW says]<br /><code>147/260 = ~56,5%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.565%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%22260%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 5.05% margin of error with 90% conf. level = either 50%, 55% or 60%], with 85% it becomes something between 50.58% and 59.42%<br />presumed to be 55%, [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.55%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D+-%3E%220.05%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 268 samples needed]<br /><code>155/268 = ~57,8%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.578%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%22268%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 summed up results (4,96% margin of error / 52,84%; 62,76%)]<br /><code>310/536 = ~57,8%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.578%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%22536%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (3,51% margin of error / 54,29%; 61,31%)]<br /><s>(aiming for 804)</s> <code>388/671 = (see below)</code><hr /><code>388/671</code> combined with previous <code>147/260</code> results: <code>535/931 = ~57,5%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.575%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%22931%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (2,67% MoE / 54,83%; 60,17%)]<br /><code>584/1021 = ~57,2%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.572%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%221021%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (2,55% MoE / 54,65%; 59,75%)]<br />Confirmed 55% dodge rate.
 
*Dodges/targeted hits count while {{Status|Awakening}} is active:<br />[https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.60%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D+-%3E%220.05%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 260 samples needed to confirm if it's 60% like GW says]<br /><code>147/260 = ~56,5%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.565%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%22260%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 5.05% margin of error with 90% conf. level = either 50%, 55% or 60%], with 85% it becomes something between 50.58% and 59.42%<br />presumed to be 55%, [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.55%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D+-%3E%220.05%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 268 samples needed]<br /><code>155/268 = ~57,8%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.578%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%22268%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 summed up results (4,96% margin of error / 52,84%; 62,76%)]<br /><code>310/536 = ~57,8%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.578%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%22536%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (3,51% margin of error / 54,29%; 61,31%)]<br /><s>(aiming for 804)</s> <code>388/671 = (see below)</code><hr /><code>388/671</code> combined with previous <code>147/260</code> results: <code>535/931 = ~57,5%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.575%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%22931%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (2,67% MoE / 54,83%; 60,17%)]<br /><code>584/1021 = ~57,2%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.572%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%221021%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (2,55% MoE / 54,65%; 59,75%)]<br />Confirmed 55% dodge rate.
 
*Dodges/targeted hits count with Ougi {{Status|Dodge Rate Boosted}} buff:<br />[https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.10%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D+-%3E%220.05%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 97 samples needed assuming it's 10% boost]<br/><code>18/97 = ~18,6%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.186%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%2297%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (6,5% MoE / 12,1%; 25,1%)]<br />[https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.15%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D+-%3E%220.05%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 138 samples if it's 15%]<br/><code>13/138 = ~9,4%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.094%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%22138%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (4,1% MoE / 5,3%; 13,5%)]<br />[https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.20%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D+-%3E%220.05%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 173 if it's 20%]<br/><code>14/173 = ~8,1%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.081%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%22173%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (3,4% MoE / 4,7%; 11,5%)]<br />[https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.05%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D+-%3E%220.05%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 51 if it's 5%]<br /><code>8/51 = ~15,7%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.157%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%2251%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (8,4% MoE / 7,3%; 24,1%)]<br />our friend 180<br /><code>22/180 = 12,2%~</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.122%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%22180%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (4% MoE / 8,2%; 16,2%)]<br />assumed to be either 10% or 15%<br/>all results combined: <code>75/639 = ~11,7%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.117%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%22639%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (2,1% MoE) / 9,6%; 13,8%)] = 10%
 
*Dodges/targeted hits count with Ougi {{Status|Dodge Rate Boosted}} buff:<br />[https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.10%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D+-%3E%220.05%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 97 samples needed assuming it's 10% boost]<br/><code>18/97 = ~18,6%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.186%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%2297%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (6,5% MoE / 12,1%; 25,1%)]<br />[https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.15%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D+-%3E%220.05%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 138 samples if it's 15%]<br/><code>13/138 = ~9,4%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.094%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%22138%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (4,1% MoE / 5,3%; 13,5%)]<br />[https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.20%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D+-%3E%220.05%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 173 if it's 20%]<br/><code>14/173 = ~8,1%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.081%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%22173%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (3,4% MoE / 4,7%; 11,5%)]<br />[https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.05%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D+-%3E%220.05%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 51 if it's 5%]<br /><code>8/51 = ~15,7%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.157%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%2251%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (8,4% MoE / 7,3%; 24,1%)]<br />our friend 180<br /><code>22/180 = 12,2%~</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.122%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%22180%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (4% MoE / 8,2%; 16,2%)]<br />assumed to be either 10% or 15%<br/>all results combined: <code>75/639 = ~11,7%</code> [https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.117%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D+-%3E%22639%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 (2,1% MoE) / 9,6%; 13,8%)] = 10%
 +
*{{Status|Dodge Rate Boosted}} from Ougi combined with {{Status|Awakening}}:<br />[https://www.wolframalpha.com/input/?i=sample+size+binomial+distribution&assumption=%7B%22FS%22%7D+-%3E+%7B%7B%22SampleSizeForBinomialParameter%22%2C+%22n%22%7D%7D&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22phat%22%7D+-%3E%220.65%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22moebp%22%7D+-%3E%220.05%22&assumption=%7B%22F%22%2C+%22SampleSizeForBinomialParameter%22%2C+%22c%22%7D+-%3E%220.90%22 246 samples needed if it's 65% (aka if values are additive)]
  
 
==Misc==
 
==Misc==
 
Local def down has sides as well.
 
Local def down has sides as well.
 
==References==
 
==References==

Revision as of 22:48, 15 February 2020

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Would you lick store-bought oreo cupcake and leave it in plain view, hoping for someone to eat it? Whatever is your answer, welcome.

Actual Page Content

Some Info I've Gathered

The Debuff Success rate formula is as follows:[1]

[math]\text{Debuff Success %} = \frac{\text{(Base Accuracy + Accuracy Boost)} \times \text{[100 - (Debuff Resistance + Debuff Res. Modifiers)]}}{\text{100}}[/math]


Debuff 180 times (0.95^180*100 = 0.01%) as debuff accuracy is divided per 5%.


Samples-needed calculating-thing nya sample proportion is the est. value; margin of error is the increment.
Can be used for multi attack rate, blind, proc chances—basically, anything, that can be summarized as "it will either do X or not"


Buffs are said to be generally in multiples of 5, so 0.05 margin of error for ^.


Margin of error based on samples.


Continue gathering samples until the margin of error shows only one possibility in the range. Example: Notes: Confirmed TA Rate is 5% assuming the da/ta rates are in multiples of 0.5% (5.06% ±0.39% is [4.67%, 5.45%] and 5% is the only multiple of 0.5% within it.)

Weapons

Debuff accuracy is estimated based on numbers from 180 attacks against non-elemental Old Lignoid. For Sword Master attack skills single attacks aren't differenced from double and triple attacks.

Swordfish icon.jpg
Swordfish

  • Accuracy of Sword Master DEF Down on attack = 10%
    Hit rate = 27/180
    MC had 6% debuff success rate bonus so base should be around 10%.
    10% from 180 = 18, (6% rounded down) 5% = 9, 18+9=27

Characters

Npc m 3040094000 01.jpg
Veight

Tested against Light ele test turret beta. No dodge buffs from ring.

Misc

Local def down has sides as well.

References