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Encounter lethality
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<blockquote data-quote="clearstream" data-source="post: 7525096" data-attributes="member: 71699"><p>Ah, right. I agree that the chance will fluctuate. For example, I believe from experience that the average rate per encounter declines with tier and have considered incorporating that as a factor.</p><p></p><p>Say we have 12 different values for <strong><em>c</em></strong> - 0.1, 0.1, 0.025, 0.05, 0.01, 0.003, etc - modelling your differing rates. The question is whether that mathematically differs from using an average of those rates? In some instances it is obvious that it does not, e.g. the sum of 1 then 2 then 3, each times 97, is the same as 2 then 2 then 2, each times 97. The estimate is based on using (1-<em><strong>c</strong></em>)^<em><strong>f</strong></em> to get a survival chance over <em><strong>f</strong></em> encounters. Perhaps you're saying that there will exist a mathematical difference between using that simple formula with a constant for <em><strong>c</strong></em>, versus using a summation. Is that right?</p><p></p><p>I can prove that one way or another, by inserting random numbers for <em><strong>c</strong></em> on a per encounter basis, creating a summation and comparing. I'll do that and come back to you.</p><p></p><p>Perhaps you are instead or also saying that our second DM always uses fewer rests per encounter, so all their encounters are more lethal, and that is your main concern? That amounts to saying second DM is using a higher value for <strong><em>c</em></strong>, and does not challenge the argument. It only says pick a larger value for <strong><em>c</em></strong>, for that DM.</p><p></p><p></p><p>[EDIT: Intuitively, a summation shouldn't differ from exponentiation using the average. In the end, they're both a series of multiplications. But I was thinking of creating a Monte Carlo sim for it, and generating an array of <em><strong>c</strong></em>'s can tie into that.)</p></blockquote><p></p>
[QUOTE="clearstream, post: 7525096, member: 71699"] Ah, right. I agree that the chance will fluctuate. For example, I believe from experience that the average rate per encounter declines with tier and have considered incorporating that as a factor. Say we have 12 different values for [B][I]c[/I][/B] - 0.1, 0.1, 0.025, 0.05, 0.01, 0.003, etc - modelling your differing rates. The question is whether that mathematically differs from using an average of those rates? In some instances it is obvious that it does not, e.g. the sum of 1 then 2 then 3, each times 97, is the same as 2 then 2 then 2, each times 97. The estimate is based on using (1-[I][B]c[/B][/I])^[I][B]f[/B][/I] to get a survival chance over [I][B]f[/B][/I] encounters. Perhaps you're saying that there will exist a mathematical difference between using that simple formula with a constant for [I][B]c[/B][/I], versus using a summation. Is that right? I can prove that one way or another, by inserting random numbers for [I][B]c[/B][/I] on a per encounter basis, creating a summation and comparing. I'll do that and come back to you. Perhaps you are instead or also saying that our second DM always uses fewer rests per encounter, so all their encounters are more lethal, and that is your main concern? That amounts to saying second DM is using a higher value for [B][I]c[/I][/B], and does not challenge the argument. It only says pick a larger value for [B][I]c[/I][/B], for that DM. [EDIT: Intuitively, a summation shouldn't differ from exponentiation using the average. In the end, they're both a series of multiplications. But I was thinking of creating a Monte Carlo sim for it, and generating an array of [I][B]c[/B][/I]'s can tie into that.) [/QUOTE]
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