Reply to thread

Message

<blockquote data-quote="Mokona" data-source="post: 3409746" data-attributes="member: 24891">Using simulation software I ran these two tests for you.&nbsp; Depending on the most likely values for X and Y you'd want to simulate those combinations but I guessed.&nbsp;&nbsp; <img src="https://cdn.jsdelivr.net/joypixels/assets/8.0/png/unicode/64/1f609.png" class="smilie smilie--emoji" loading="lazy" width="64" height="64" alt=";)" title="Wink&nbsp; &nbsp; ;)"&nbsp; data-smilie="2"data-shortname=";)" />[The labels are formated as Xd vs Y.]Forecast: 5d_vs_5&nbsp; &nbsp;&nbsp; Statistic&nbsp; &nbsp; Forecast valuesTrials&nbsp; &nbsp; 10,000Mean&nbsp; &nbsp; 7.5Median&nbsp; &nbsp; 7Mode&nbsp; &nbsp; 8Standard Deviation&nbsp; &nbsp; 4.03Variance&nbsp; &nbsp; 16.22Skewness&nbsp; &nbsp; 0.3541Kurtosis&nbsp; &nbsp; 2.83Coeff. of Variability&nbsp; &nbsp; 0.537Minimum&nbsp; &nbsp; 0Maximum&nbsp; &nbsp; 23Mean Std. Error&nbsp; &nbsp; 0.04Forecast: 5d_vs_7&nbsp; &nbsp;&nbsp; Statistic&nbsp; &nbsp; Forecast valuesTrials&nbsp; &nbsp; 10,000Mean&nbsp; &nbsp; 14Median&nbsp; &nbsp; 14Mode&nbsp; &nbsp; 14Standard Deviation&nbsp; &nbsp; 5.61Variance&nbsp; &nbsp; 31.52Skewness&nbsp; &nbsp; 0.1363Kurtosis&nbsp; &nbsp; 2.7Coeff. of Variability&nbsp; &nbsp; 0.401Minimum&nbsp; &nbsp; 0Maximum&nbsp; &nbsp; 33Mean Std. Error&nbsp; &nbsp; 0.06-----Forecast: 2d_vs_5&nbsp; &nbsp;&nbsp; Statistic&nbsp; &nbsp; Forecast valuesTrials&nbsp; &nbsp; 10,000Mean&nbsp; &nbsp; 3Median&nbsp; &nbsp; 3Mode&nbsp; &nbsp; 0Standard Deviation&nbsp; &nbsp; 2.55Variance&nbsp; &nbsp; 6.51Skewness&nbsp; &nbsp; 0.5355Kurtosis&nbsp; &nbsp; 2.53Coeff. of Variability&nbsp; &nbsp; 0.8506Minimum&nbsp; &nbsp; 0Maximum&nbsp; &nbsp; 10Mean Std. Error&nbsp; &nbsp; 0.03Forecast: 2d_vs_7&nbsp; &nbsp;&nbsp; Statistic&nbsp; &nbsp; Forecast valuesTrials&nbsp; &nbsp; 10,000Mean&nbsp; &nbsp; 5.6Median&nbsp; &nbsp; 6Mode&nbsp; &nbsp; 7Standard Deviation&nbsp; &nbsp; 3.52Variance&nbsp; &nbsp; 12.42Skewness&nbsp; &nbsp; 0.2156Kurtosis&nbsp; &nbsp; 2.33Coeff. of Variability&nbsp; &nbsp; 0.6294Minimum&nbsp; &nbsp; 0Maximum&nbsp; &nbsp; 14Mean Std. Error&nbsp; &nbsp; 0.04-----I ran the same test for Fireball damage (sum of Xd6) for comparison.Forecast: 2d6&nbsp; &nbsp;&nbsp; Statistic&nbsp; &nbsp; Forecast valuesTrials&nbsp; &nbsp; 10,000Mean&nbsp; &nbsp; 7Median&nbsp; &nbsp; 7Mode&nbsp; &nbsp; 7Standard Deviation&nbsp; &nbsp; 2.41Variance&nbsp; &nbsp; 5.83Skewness&nbsp; &nbsp; 0.0352Kurtosis&nbsp; &nbsp; 2.36Coeff. of Variability&nbsp; &nbsp; 0.3448Minimum&nbsp; &nbsp; 2Maximum&nbsp; &nbsp; 12Mean Std. Error&nbsp; &nbsp; 0.02Forecast: 3d6&nbsp; &nbsp;&nbsp; Statistic&nbsp; &nbsp; Forecast valuesTrials&nbsp; &nbsp; 10,000Mean&nbsp; &nbsp; 10.5Median&nbsp; &nbsp; 11Mode&nbsp; &nbsp; 10Standard Deviation&nbsp; &nbsp; 2.98Variance&nbsp; &nbsp; 8.91Skewness&nbsp; &nbsp; -0.002Kurtosis&nbsp; &nbsp; 2.54Coeff. of Variability&nbsp; &nbsp; 0.2843Minimum&nbsp; &nbsp; 3Maximum&nbsp; &nbsp; 18Mean Std. Error&nbsp; &nbsp; 0.03Forecast: 5d6&nbsp; &nbsp;&nbsp; Statistic&nbsp; &nbsp; Forecast valuesTrials&nbsp; &nbsp; 10,000Mean&nbsp; &nbsp; 17.5Median&nbsp; &nbsp; 18Mode&nbsp; &nbsp; 18Standard Deviation&nbsp; &nbsp; 3.81Variance&nbsp; &nbsp; 14.52Skewness&nbsp; &nbsp; -0.0241Kurtosis&nbsp; &nbsp; 2.72Coeff. of Variability&nbsp; &nbsp; 0.2178Minimum&nbsp; &nbsp; 5Maximum&nbsp; &nbsp; 30Mean Std. Error&nbsp; &nbsp; 0.04Forecast: 10d6&nbsp; &nbsp;&nbsp; Statistic&nbsp; &nbsp; Forecast valuesTrials&nbsp; &nbsp; 10,000Mean&nbsp; &nbsp; 35Median&nbsp; &nbsp; 35Mode&nbsp; &nbsp; 37Standard Deviation&nbsp; &nbsp; 5.45Variance&nbsp; &nbsp; 29.72Skewness&nbsp; &nbsp; 0.0019Kurtosis&nbsp; &nbsp; 2.86Coeff. of Variability&nbsp; &nbsp; 0.1558Minimum&nbsp; &nbsp; 14Maximum&nbsp; &nbsp; 55Mean Std. Error&nbsp; &nbsp; 0.05</blockquote>

[QUOTE="Mokona, post: 3409746, member: 24891"] Using simulation software I ran these two tests for you. Depending on the most likely values for X and Y you'd want to simulate those combinations but I guessed. ;) [The labels are formated as Xd vs Y.] Forecast: 5d_vs_5 Statistic Forecast values Trials 10,000 Mean 7.5 Median 7 Mode 8 Standard Deviation 4.03 Variance 16.22 Skewness 0.3541 Kurtosis 2.83 Coeff. of Variability 0.537 Minimum 0 Maximum 23 Mean Std. Error 0.04 Forecast: 5d_vs_7 Statistic Forecast values Trials 10,000 Mean 14 Median 14 Mode 14 Standard Deviation 5.61 Variance 31.52 Skewness 0.1363 Kurtosis 2.7 Coeff. of Variability 0.401 Minimum 0 Maximum 33 Mean Std. Error 0.06 ----- Forecast: 2d_vs_5 Statistic Forecast values Trials 10,000 Mean 3 Median 3 Mode 0 Standard Deviation 2.55 Variance 6.51 Skewness 0.5355 Kurtosis 2.53 Coeff. of Variability 0.8506 Minimum 0 Maximum 10 Mean Std. Error 0.03 Forecast: 2d_vs_7 Statistic Forecast values Trials 10,000 Mean 5.6 Median 6 Mode 7 Standard Deviation 3.52 Variance 12.42 Skewness 0.2156 Kurtosis 2.33 Coeff. of Variability 0.6294 Minimum 0 Maximum 14 Mean Std. Error 0.04 ----- I ran the same test for Fireball damage (sum of Xd6) for comparison. Forecast: 2d6 Statistic Forecast values Trials 10,000 Mean 7 Median 7 Mode 7 Standard Deviation 2.41 Variance 5.83 Skewness 0.0352 Kurtosis 2.36 Coeff. of Variability 0.3448 Minimum 2 Maximum 12 Mean Std. Error 0.02 Forecast: 3d6 Statistic Forecast values Trials 10,000 Mean 10.5 Median 11 Mode 10 Standard Deviation 2.98 Variance 8.91 Skewness -0.002 Kurtosis 2.54 Coeff. of Variability 0.2843 Minimum 3 Maximum 18 Mean Std. Error 0.03 Forecast: 5d6 Statistic Forecast values Trials 10,000 Mean 17.5 Median 18 Mode 18 Standard Deviation 3.81 Variance 14.52 Skewness -0.0241 Kurtosis 2.72 Coeff. of Variability 0.2178 Minimum 5 Maximum 30 Mean Std. Error 0.04 Forecast: 10d6 Statistic Forecast values Trials 10,000 Mean 35 Median 35 Mode 37 Standard Deviation 5.45 Variance 29.72 Skewness 0.0019 Kurtosis 2.86 Coeff. of Variability 0.1558 Minimum 14 Maximum 55 Mean Std. Error 0.05 [/QUOTE]

Verification