CountE(r)σ^2
010.9119.17
113.6318.68
215.8425.51
38.6911.29
48.356.69
00.0
17.227685504501818E-4
20.648888180366443
30.9840881771783161
40.036235538813243075
5-0.020323715991559167
total:289.72363216872805
651.27 ; 24.59813041451064

num
Count Asset 1  Asset 2  Asset 3  Asset 4  Asset 5 E(r) σ^2 σ CAL Slope CAL line utility  Er Utility
00.03330.0-0.00560.00.97238.3944.046.630.369.446.859.46
10.02670.00.01650.00.95668.5442.846.540.389.407.059.42
20.02020.00.03870.00.94098.6942.186.490.419.377.229.40
30.01370.00.06100.00.92528.8442.046.480.439.367.379.39
40.00720.00.08320.00.90958.9942.456.510.469.387.519.40
57.22760.00.10540.00.89389.1443.386.580.479.427.639.44
60.00.00.12570.00.87429.2944.946.700.499.487.729.49
70.00.00.14570.00.85429.4446.986.850.509.567.809.56
80.00.00.16570.00.83429.5949.587.040.519.657.869.65
90.00.00.18570.00.81429.7452.737.260.519.777.909.76
100.00.00.20570.00.79429.8956.437.510.519.907.929.89
110.00.00900.21930.00.771510.0460.687.780.5110.047.9210.04
120.00.02680.22670.00.746310.1965.398.080.5110.207.9010.21
130.00.04460.23420.00.721010.3470.558.390.5110.367.8710.39
140.00.06240.24170.00.695810.4976.168.720.5110.537.8310.58
150.00.08010.24920.00.670510.6482.229.060.5110.717.7610.80
160.00.09790.25660.00.645310.7988.739.420.5010.897.6911.03
170.00.11570.26410.00.620010.9495.709.780.5011.087.5911.27
180.00.13340.27160.00.594811.09103.1210.150.5011.277.4811.53
190.00.15120.27910.00.569511.24110.9810.530.4911.477.3611.80
200.00.16900.28660.00.544311.39119.3010.920.4911.677.2212.09
210.00.18680.29400.00.519111.54128.0711.310.4911.887.0612.40
220.00.20450.30150.00.493811.69137.2911.710.4812.086.8912.72
230.00.22230.30900.00.468611.84146.9612.120.4812.296.7013.06
240.00.24010.31650.00.443311.99157.0812.530.4712.516.4913.42
250.00.25790.32390.00.418112.14167.6512.940.4712.726.2713.79
260.00.27560.33140.00.392812.29178.6813.360.4712.946.0414.17
270.00.29340.33890.00.367612.44190.1513.780.4613.165.7814.57
280.00.31120.34640.00.342312.59202.0814.210.4613.385.5214.99
290.00.32890.35390.00.317112.74214.4614.640.4613.615.2315.43
300.00.34670.36130.00.291812.89227.2815.070.4513.834.9315.87
310.00.36450.36880.00.266613.04240.5615.510.4514.064.6216.34
320.00.38230.37630.00.241313.19254.2915.940.4514.284.2916.82
330.00.40000.38380.00.216113.34268.4716.380.4414.513.9417.32
340.00.41780.39120.00.190813.49283.1116.820.4414.743.5817.83
350.00.43560.39870.00.165613.64298.1917.260.4414.973.2018.36
360.00.45330.40620.00.140313.79313.7217.710.4415.202.8118.90
370.00.47110.41370.00.115113.94329.7118.150.4315.432.4019.46
380.00.48890.42120.00.089814.09346.1518.600.4315.661.9720.03
390.00.50670.42860.00.064614.24363.0319.050.4315.901.5320.63
400.00.52440.43610.00.039314.39380.3719.500.4316.131.0821.23
410.00.54220.44360.00.014114.54398.1619.950.4216.360.6021.86
420.00.56000.45110.0-0.011114.69416.4020.400.4216.600.1122.49
430.00.57770.45850.0-0.036314.84435.0920.850.4216.83-0.3823.15
440.00.59550.46600.0-0.061614.99454.2421.310.4217.07-0.9023.82
450.00.61330.47350.0-0.086815.14473.8321.760.4217.31-1.4424.50
460.00.63110.48100.0-0.112115.29493.8722.220.4117.54-1.9925.20
470.00.64880.48840.0-0.137315.44514.3722.670.4117.78-2.5625.92
480.00.00.96490.01750.017415.59651.2725.510.3719.26-7.2030.71
490.00.00.98400.0362-0.020315.74651.2725.510.3819.26-7.0530.71


sNum : Max Slope : 0.5196584924373893

sNum : -1.1508175492812711 PC : -3.126388037344441E-13

pivit Row : 4 PC : 3 pivit numer multip :
Expected Loss (Y) vs. Avg. Dist. To Fault (X1) and Avg. Year Built (X2)
   
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.842556136
R Square 0.709900843
Adjusted R Square 0.657155542
Standard Error 11979119.67
Observations 14
ANOVA
  df SS MS F Significance F
Regression 2 3.86272E+15 1.93136E+15 13.45903475 0.001106638
Residual 11 1.57849E+15 1.43499E+14
Total 13 5.44122E+15      
  Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 467155050.9 704020356.5 0.663553329 0.520640454 -1082384090 2016694192
Avg. Dist. to Fault -6073477.78 9062571.569 -0.670171566 0.516570837 -26020073.4 13873117.84
Text Box: These standard errors measure the variability of the regression estimates.  If is very large, then we should have little confidence in the associated estimate.  This is also reflected in the confidence interval for the parameter.
Avg. Year Built
1126087.577 507975.0103 2.216816879 0.048635417 8041.552134 2244133.602
 
RESIDUAL OUTPUT
Observation Predicted Expected Loss Residuals Leverage Stud. Residuals Cook's D
1 6718499.851 -5740785.174 0.523285815 -0.694092505 0.176276469
2 4908005.459 834739.6251 0.249585505 0.08044064 0.000717378
3 17900934.01 -2249565.569 0.121228447 -0.20032528 0.00184535
4 19211542.61 -4637027.773 0.243126527 -0.444941743 0.021197962
5 16872246.09 -4063440.91 0.150231886 -0.367975437 0.007979544
6 29509513.45 -1664739.231 0.147501986 -0.150513212 0.001306569
7 22234933.42 18852830.43 0.105113535 1.663671926 0.10836894
8 43399275.23 5005801.474 0.254720066 0.48404864 0.02669319
9 30612796.75 -11576667.58 0.130082673 -1.036142932 0.053513031
10 33095983.51 -1102734.15 0.246170885 -0.10602529 0.001223662
11 47155418.79 -14805325.47 0.159545288 -1.348142802 0.115005923
12 40512761.79 20135424.2 0.108335103 1.780061655 0.128326505
13 52608304.44 13887196.03 0.215108025 1.308533115 0.156420945
14 63080824.28 -12875705.89 0.345964259 -1.329062498 0.311457868   Bin Frequency
    -1.35 1
-0.31 5
0.74 5
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