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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 20 Dec 2016 19:13:30 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/20/t1482261512s4qpidosp8amf1n.htm/, Retrieved Sun, 28 Apr 2024 09:56:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301782, Retrieved Sun, 28 Apr 2024 09:56:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact56
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [central tendency] [2016-12-20 18:13:30] [06fd994a2f2098873ec640c3e39346e5] [Current]
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Dataseries X:
4738.4
4687.2
5930.8
5532
5429.8
6107.4
5960.8
5541.8
5362.2
5237
4827
4781.6
4983.2
4718.4
5523.8
5286.6
5389
5810.4
5057.4
5604.4
5285
5215.2
4625.4
4270.4
4685.4
4233.8
5278.4
4978.8
5333.4
5451
5224
5790.2
5079.4
4705.8
4139.6
3720.8
4594
4638.8
4969.4
4764.4
5010.8
5267.8
5312.2
5723.2
4579.6
5015.2
4282.4
3834.2
4523.4
3884.2
3897.8
4845.6
4929
4955.4
5198.4
5122.2
4643.2
4789.8
3950.8
3824.4
4511.8
4262.4
4616.6
5139.6
4972.8
5222
5242
4979.8
4691.8
4821.6
4123.6
4027.4
4365.2
4333.6
4930
5053
5031.4
5342
5191.4
4852.2
4675.6
4689.2
3809.4
4054.2
4409.6
4210.2
4566.4
4907
5021.8
5215.2
4933.6
5197.8
4734.6
4681.8
4172
4037.8
4462.6
4282.6
4962.4
4969.2
5214.6
5416.8
4764.2
5326.2
4545.4
4797.2
4259
4117
4469.2
4203.2
5033.8
4883
5361.6
5044.6
5005.6
5382
4565.4
4825
4290.2
3933.6
4177.6
3949.4
4492.6
4894.2
5224.4
5071
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301782&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=301782&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301782&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic MeanNANANA
Geometric MeanNA
Harmonic MeanNA
Quadratic MeanNA
Winsorized Mean ( 1 / 42 )4825.1945.3687106.355
Winsorized Mean ( 2 / 42 )4824.9545.232106.671
Winsorized Mean ( 3 / 42 )4822.3244.6565107.987
Winsorized Mean ( 4 / 42 )4823.2744.2685108.955
Winsorized Mean ( 5 / 42 )4821.1543.7254110.26
Winsorized Mean ( 6 / 42 )4817.1942.5536113.203
Winsorized Mean ( 7 / 42 )4814.5941.9094114.881
Winsorized Mean ( 8 / 42 )4814.0641.8088115.145
Winsorized Mean ( 9 / 42 )4818.9540.8519117.961
Winsorized Mean ( 10 / 42 )4813.9939.9562120.482
Winsorized Mean ( 11 / 42 )4813.5739.5013121.859
Winsorized Mean ( 12 / 42 )4818.3238.4504125.313
Winsorized Mean ( 13 / 42 )4816.1337.9995126.742
Winsorized Mean ( 14 / 42 )4817.1337.6483127.951
Winsorized Mean ( 15 / 42 )4818.6336.819130.874
Winsorized Mean ( 16 / 42 )4819.2736.7103131.278
Winsorized Mean ( 17 / 42 )4820.0735.9215134.184
Winsorized Mean ( 18 / 42 )4819.8535.6422135.229
Winsorized Mean ( 19 / 42 )4822.3235.0345137.645
Winsorized Mean ( 20 / 42 )4824.134.2471140.861
Winsorized Mean ( 21 / 42 )4820.433.6927143.069
Winsorized Mean ( 22 / 42 )4821.5133.4773144.024
Winsorized Mean ( 23 / 42 )4822.533.0567145.886
Winsorized Mean ( 24 / 42 )4820.5232.8303146.831
Winsorized Mean ( 25 / 42 )4816.9132.0821150.143
Winsorized Mean ( 26 / 42 )4824.8330.8126156.586
Winsorized Mean ( 27 / 42 )4828.929.6689162.76
Winsorized Mean ( 28 / 42 )4838.6828.4467170.096
Winsorized Mean ( 29 / 42 )4850.4226.9576179.928
Winsorized Mean ( 30 / 42 )4850.3726.599182.352
Winsorized Mean ( 31 / 42 )4856.1325.9462187.161
Winsorized Mean ( 32 / 42 )4860.8525.3878191.464
Winsorized Mean ( 33 / 42 )4859.6524.5841197.674
Winsorized Mean ( 34 / 42 )4865.4223.9237203.373
Winsorized Mean ( 35 / 42 )4869.223.1367210.454
Winsorized Mean ( 36 / 42 )4854.6921.4958225.843
Winsorized Mean ( 37 / 42 )4853.4520.5428236.26
Winsorized Mean ( 38 / 42 )4844.8918.7565258.304
Winsorized Mean ( 39 / 42 )4849.2817.7555273.115
Winsorized Mean ( 40 / 42 )4847.7617.0349284.578
Winsorized Mean ( 41 / 42 )4850.6916.4415295.028
Winsorized Mean ( 42 / 42 )4849.3516.016302.782
Trimmed Mean ( 1 / 42 )4824.2244.4219108.6
Trimmed Mean ( 2 / 42 )4823.2343.3766111.194
Trimmed Mean ( 3 / 42 )4822.3242.2996114.004
Trimmed Mean ( 4 / 42 )4822.3241.3431116.641
Trimmed Mean ( 5 / 42 )4822.0640.4075119.336
Trimmed Mean ( 6 / 42 )4822.2739.5154122.035
Trimmed Mean ( 7 / 42 )4823.2238.7975124.318
Trimmed Mean ( 8 / 42 )4824.6338.1309126.528
Trimmed Mean ( 9 / 42 )4826.1737.4055129.023
Trimmed Mean ( 10 / 42 )4827.1236.765131.297
Trimmed Mean ( 11 / 42 )4828.7236.1924133.418
Trimmed Mean ( 12 / 42 )4830.4235.6187135.615
Trimmed Mean ( 13 / 42 )4831.6935.129137.541
Trimmed Mean ( 14 / 42 )4833.2234.6375139.537
Trimmed Mean ( 15 / 42 )4834.7334.1282141.664
Trimmed Mean ( 16 / 42 )4836.1733.6602143.676
Trimmed Mean ( 17 / 42 )4837.6233.1402145.974
Trimmed Mean ( 18 / 42 )4839.0632.6478148.22
Trimmed Mean ( 19 / 42 )4840.5932.1179150.713
Trimmed Mean ( 20 / 42 )484231.587153.291
Trimmed Mean ( 21 / 42 )4843.3531.0745155.862
Trimmed Mean ( 22 / 42 )4845.0230.5479158.604
Trimmed Mean ( 23 / 42 )4846.7129.9634161.754
Trimmed Mean ( 24 / 42 )4848.4129.3369165.266
Trimmed Mean ( 25 / 42 )4850.3328.6319169.403
Trimmed Mean ( 26 / 42 )4852.6127.9009173.923
Trimmed Mean ( 27 / 42 )4854.4827.2209178.337
Trimmed Mean ( 28 / 42 )4856.1926.5763182.726
Trimmed Mean ( 29 / 42 )4857.3425.9863186.919
Trimmed Mean ( 30 / 42 )4857.825.4919190.562
Trimmed Mean ( 31 / 42 )4858.2924.9456194.755
Trimmed Mean ( 32 / 42 )4858.4324.3799199.28
Trimmed Mean ( 33 / 42 )4858.2723.7746204.347
Trimmed Mean ( 34 / 42 )4858.1823.1587209.777
Trimmed Mean ( 35 / 42 )4857.722.5048215.852
Trimmed Mean ( 36 / 42 )4856.9321.8236222.554
Trimmed Mean ( 37 / 42 )4857.0821.2609228.451
Trimmed Mean ( 38 / 42 )4857.3320.7166234.466
Trimmed Mean ( 39 / 42 )4858.1920.334238.92
Trimmed Mean ( 40 / 42 )4858.8220.0135242.777
Trimmed Mean ( 41 / 42 )4859.6119.7122246.528
Trimmed Mean ( 42 / 42 )4860.2619.4136250.354
MedianNA
MidrangeNA
Midmean - Weighted Average at Xnp4852.62
Midmean - Weighted Average at X(n+1)p4863.78
Midmean - Empirical Distribution Function4863.78
Midmean - Empirical Distribution Function - Averaging4863.78
Midmean - Empirical Distribution Function - Interpolation4858.43
Midmean - Closest Observation4863.78
Midmean - True Basic - Statistics Graphics Toolkit4863.78
Midmean - MS Excel (old versions)4863.78
Number of observations144

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & NA & NA & NA \tabularnewline
Geometric Mean & NA &  &  \tabularnewline
Harmonic Mean & NA &  &  \tabularnewline
Quadratic Mean & NA &  &  \tabularnewline
Winsorized Mean ( 1 / 42 ) & 4825.19 & 45.3687 & 106.355 \tabularnewline
Winsorized Mean ( 2 / 42 ) & 4824.95 & 45.232 & 106.671 \tabularnewline
Winsorized Mean ( 3 / 42 ) & 4822.32 & 44.6565 & 107.987 \tabularnewline
Winsorized Mean ( 4 / 42 ) & 4823.27 & 44.2685 & 108.955 \tabularnewline
Winsorized Mean ( 5 / 42 ) & 4821.15 & 43.7254 & 110.26 \tabularnewline
Winsorized Mean ( 6 / 42 ) & 4817.19 & 42.5536 & 113.203 \tabularnewline
Winsorized Mean ( 7 / 42 ) & 4814.59 & 41.9094 & 114.881 \tabularnewline
Winsorized Mean ( 8 / 42 ) & 4814.06 & 41.8088 & 115.145 \tabularnewline
Winsorized Mean ( 9 / 42 ) & 4818.95 & 40.8519 & 117.961 \tabularnewline
Winsorized Mean ( 10 / 42 ) & 4813.99 & 39.9562 & 120.482 \tabularnewline
Winsorized Mean ( 11 / 42 ) & 4813.57 & 39.5013 & 121.859 \tabularnewline
Winsorized Mean ( 12 / 42 ) & 4818.32 & 38.4504 & 125.313 \tabularnewline
Winsorized Mean ( 13 / 42 ) & 4816.13 & 37.9995 & 126.742 \tabularnewline
Winsorized Mean ( 14 / 42 ) & 4817.13 & 37.6483 & 127.951 \tabularnewline
Winsorized Mean ( 15 / 42 ) & 4818.63 & 36.819 & 130.874 \tabularnewline
Winsorized Mean ( 16 / 42 ) & 4819.27 & 36.7103 & 131.278 \tabularnewline
Winsorized Mean ( 17 / 42 ) & 4820.07 & 35.9215 & 134.184 \tabularnewline
Winsorized Mean ( 18 / 42 ) & 4819.85 & 35.6422 & 135.229 \tabularnewline
Winsorized Mean ( 19 / 42 ) & 4822.32 & 35.0345 & 137.645 \tabularnewline
Winsorized Mean ( 20 / 42 ) & 4824.1 & 34.2471 & 140.861 \tabularnewline
Winsorized Mean ( 21 / 42 ) & 4820.4 & 33.6927 & 143.069 \tabularnewline
Winsorized Mean ( 22 / 42 ) & 4821.51 & 33.4773 & 144.024 \tabularnewline
Winsorized Mean ( 23 / 42 ) & 4822.5 & 33.0567 & 145.886 \tabularnewline
Winsorized Mean ( 24 / 42 ) & 4820.52 & 32.8303 & 146.831 \tabularnewline
Winsorized Mean ( 25 / 42 ) & 4816.91 & 32.0821 & 150.143 \tabularnewline
Winsorized Mean ( 26 / 42 ) & 4824.83 & 30.8126 & 156.586 \tabularnewline
Winsorized Mean ( 27 / 42 ) & 4828.9 & 29.6689 & 162.76 \tabularnewline
Winsorized Mean ( 28 / 42 ) & 4838.68 & 28.4467 & 170.096 \tabularnewline
Winsorized Mean ( 29 / 42 ) & 4850.42 & 26.9576 & 179.928 \tabularnewline
Winsorized Mean ( 30 / 42 ) & 4850.37 & 26.599 & 182.352 \tabularnewline
Winsorized Mean ( 31 / 42 ) & 4856.13 & 25.9462 & 187.161 \tabularnewline
Winsorized Mean ( 32 / 42 ) & 4860.85 & 25.3878 & 191.464 \tabularnewline
Winsorized Mean ( 33 / 42 ) & 4859.65 & 24.5841 & 197.674 \tabularnewline
Winsorized Mean ( 34 / 42 ) & 4865.42 & 23.9237 & 203.373 \tabularnewline
Winsorized Mean ( 35 / 42 ) & 4869.2 & 23.1367 & 210.454 \tabularnewline
Winsorized Mean ( 36 / 42 ) & 4854.69 & 21.4958 & 225.843 \tabularnewline
Winsorized Mean ( 37 / 42 ) & 4853.45 & 20.5428 & 236.26 \tabularnewline
Winsorized Mean ( 38 / 42 ) & 4844.89 & 18.7565 & 258.304 \tabularnewline
Winsorized Mean ( 39 / 42 ) & 4849.28 & 17.7555 & 273.115 \tabularnewline
Winsorized Mean ( 40 / 42 ) & 4847.76 & 17.0349 & 284.578 \tabularnewline
Winsorized Mean ( 41 / 42 ) & 4850.69 & 16.4415 & 295.028 \tabularnewline
Winsorized Mean ( 42 / 42 ) & 4849.35 & 16.016 & 302.782 \tabularnewline
Trimmed Mean ( 1 / 42 ) & 4824.22 & 44.4219 & 108.6 \tabularnewline
Trimmed Mean ( 2 / 42 ) & 4823.23 & 43.3766 & 111.194 \tabularnewline
Trimmed Mean ( 3 / 42 ) & 4822.32 & 42.2996 & 114.004 \tabularnewline
Trimmed Mean ( 4 / 42 ) & 4822.32 & 41.3431 & 116.641 \tabularnewline
Trimmed Mean ( 5 / 42 ) & 4822.06 & 40.4075 & 119.336 \tabularnewline
Trimmed Mean ( 6 / 42 ) & 4822.27 & 39.5154 & 122.035 \tabularnewline
Trimmed Mean ( 7 / 42 ) & 4823.22 & 38.7975 & 124.318 \tabularnewline
Trimmed Mean ( 8 / 42 ) & 4824.63 & 38.1309 & 126.528 \tabularnewline
Trimmed Mean ( 9 / 42 ) & 4826.17 & 37.4055 & 129.023 \tabularnewline
Trimmed Mean ( 10 / 42 ) & 4827.12 & 36.765 & 131.297 \tabularnewline
Trimmed Mean ( 11 / 42 ) & 4828.72 & 36.1924 & 133.418 \tabularnewline
Trimmed Mean ( 12 / 42 ) & 4830.42 & 35.6187 & 135.615 \tabularnewline
Trimmed Mean ( 13 / 42 ) & 4831.69 & 35.129 & 137.541 \tabularnewline
Trimmed Mean ( 14 / 42 ) & 4833.22 & 34.6375 & 139.537 \tabularnewline
Trimmed Mean ( 15 / 42 ) & 4834.73 & 34.1282 & 141.664 \tabularnewline
Trimmed Mean ( 16 / 42 ) & 4836.17 & 33.6602 & 143.676 \tabularnewline
Trimmed Mean ( 17 / 42 ) & 4837.62 & 33.1402 & 145.974 \tabularnewline
Trimmed Mean ( 18 / 42 ) & 4839.06 & 32.6478 & 148.22 \tabularnewline
Trimmed Mean ( 19 / 42 ) & 4840.59 & 32.1179 & 150.713 \tabularnewline
Trimmed Mean ( 20 / 42 ) & 4842 & 31.587 & 153.291 \tabularnewline
Trimmed Mean ( 21 / 42 ) & 4843.35 & 31.0745 & 155.862 \tabularnewline
Trimmed Mean ( 22 / 42 ) & 4845.02 & 30.5479 & 158.604 \tabularnewline
Trimmed Mean ( 23 / 42 ) & 4846.71 & 29.9634 & 161.754 \tabularnewline
Trimmed Mean ( 24 / 42 ) & 4848.41 & 29.3369 & 165.266 \tabularnewline
Trimmed Mean ( 25 / 42 ) & 4850.33 & 28.6319 & 169.403 \tabularnewline
Trimmed Mean ( 26 / 42 ) & 4852.61 & 27.9009 & 173.923 \tabularnewline
Trimmed Mean ( 27 / 42 ) & 4854.48 & 27.2209 & 178.337 \tabularnewline
Trimmed Mean ( 28 / 42 ) & 4856.19 & 26.5763 & 182.726 \tabularnewline
Trimmed Mean ( 29 / 42 ) & 4857.34 & 25.9863 & 186.919 \tabularnewline
Trimmed Mean ( 30 / 42 ) & 4857.8 & 25.4919 & 190.562 \tabularnewline
Trimmed Mean ( 31 / 42 ) & 4858.29 & 24.9456 & 194.755 \tabularnewline
Trimmed Mean ( 32 / 42 ) & 4858.43 & 24.3799 & 199.28 \tabularnewline
Trimmed Mean ( 33 / 42 ) & 4858.27 & 23.7746 & 204.347 \tabularnewline
Trimmed Mean ( 34 / 42 ) & 4858.18 & 23.1587 & 209.777 \tabularnewline
Trimmed Mean ( 35 / 42 ) & 4857.7 & 22.5048 & 215.852 \tabularnewline
Trimmed Mean ( 36 / 42 ) & 4856.93 & 21.8236 & 222.554 \tabularnewline
Trimmed Mean ( 37 / 42 ) & 4857.08 & 21.2609 & 228.451 \tabularnewline
Trimmed Mean ( 38 / 42 ) & 4857.33 & 20.7166 & 234.466 \tabularnewline
Trimmed Mean ( 39 / 42 ) & 4858.19 & 20.334 & 238.92 \tabularnewline
Trimmed Mean ( 40 / 42 ) & 4858.82 & 20.0135 & 242.777 \tabularnewline
Trimmed Mean ( 41 / 42 ) & 4859.61 & 19.7122 & 246.528 \tabularnewline
Trimmed Mean ( 42 / 42 ) & 4860.26 & 19.4136 & 250.354 \tabularnewline
Median & NA &  &  \tabularnewline
Midrange & NA &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 4852.62 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 4863.78 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 4863.78 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 4863.78 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 4858.43 &  &  \tabularnewline
Midmean - Closest Observation & 4863.78 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 4863.78 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 4863.78 &  &  \tabularnewline
Number of observations & 144 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301782&T=1

[TABLE]
[ROW][C]Central Tendency - Ungrouped Data[/C][/ROW]
[ROW][C]Measure[/C][C]Value[/C][C]S.E.[/C][C]Value/S.E.[/C][/ROW]
[ROW][C]Arithmetic Mean[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NA[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]NA[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]NA[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 42 )[/C][C]4825.19[/C][C]45.3687[/C][C]106.355[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 42 )[/C][C]4824.95[/C][C]45.232[/C][C]106.671[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 42 )[/C][C]4822.32[/C][C]44.6565[/C][C]107.987[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 42 )[/C][C]4823.27[/C][C]44.2685[/C][C]108.955[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 42 )[/C][C]4821.15[/C][C]43.7254[/C][C]110.26[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 42 )[/C][C]4817.19[/C][C]42.5536[/C][C]113.203[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 42 )[/C][C]4814.59[/C][C]41.9094[/C][C]114.881[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 42 )[/C][C]4814.06[/C][C]41.8088[/C][C]115.145[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 42 )[/C][C]4818.95[/C][C]40.8519[/C][C]117.961[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 42 )[/C][C]4813.99[/C][C]39.9562[/C][C]120.482[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 42 )[/C][C]4813.57[/C][C]39.5013[/C][C]121.859[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 42 )[/C][C]4818.32[/C][C]38.4504[/C][C]125.313[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 42 )[/C][C]4816.13[/C][C]37.9995[/C][C]126.742[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 42 )[/C][C]4817.13[/C][C]37.6483[/C][C]127.951[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 42 )[/C][C]4818.63[/C][C]36.819[/C][C]130.874[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 42 )[/C][C]4819.27[/C][C]36.7103[/C][C]131.278[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 42 )[/C][C]4820.07[/C][C]35.9215[/C][C]134.184[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 42 )[/C][C]4819.85[/C][C]35.6422[/C][C]135.229[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 42 )[/C][C]4822.32[/C][C]35.0345[/C][C]137.645[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 42 )[/C][C]4824.1[/C][C]34.2471[/C][C]140.861[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 42 )[/C][C]4820.4[/C][C]33.6927[/C][C]143.069[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 42 )[/C][C]4821.51[/C][C]33.4773[/C][C]144.024[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 42 )[/C][C]4822.5[/C][C]33.0567[/C][C]145.886[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 42 )[/C][C]4820.52[/C][C]32.8303[/C][C]146.831[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 42 )[/C][C]4816.91[/C][C]32.0821[/C][C]150.143[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 42 )[/C][C]4824.83[/C][C]30.8126[/C][C]156.586[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 42 )[/C][C]4828.9[/C][C]29.6689[/C][C]162.76[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 42 )[/C][C]4838.68[/C][C]28.4467[/C][C]170.096[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 42 )[/C][C]4850.42[/C][C]26.9576[/C][C]179.928[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 42 )[/C][C]4850.37[/C][C]26.599[/C][C]182.352[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 42 )[/C][C]4856.13[/C][C]25.9462[/C][C]187.161[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 42 )[/C][C]4860.85[/C][C]25.3878[/C][C]191.464[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 42 )[/C][C]4859.65[/C][C]24.5841[/C][C]197.674[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 42 )[/C][C]4865.42[/C][C]23.9237[/C][C]203.373[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 42 )[/C][C]4869.2[/C][C]23.1367[/C][C]210.454[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 42 )[/C][C]4854.69[/C][C]21.4958[/C][C]225.843[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 42 )[/C][C]4853.45[/C][C]20.5428[/C][C]236.26[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 42 )[/C][C]4844.89[/C][C]18.7565[/C][C]258.304[/C][/ROW]
[ROW][C]Winsorized Mean ( 39 / 42 )[/C][C]4849.28[/C][C]17.7555[/C][C]273.115[/C][/ROW]
[ROW][C]Winsorized Mean ( 40 / 42 )[/C][C]4847.76[/C][C]17.0349[/C][C]284.578[/C][/ROW]
[ROW][C]Winsorized Mean ( 41 / 42 )[/C][C]4850.69[/C][C]16.4415[/C][C]295.028[/C][/ROW]
[ROW][C]Winsorized Mean ( 42 / 42 )[/C][C]4849.35[/C][C]16.016[/C][C]302.782[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 42 )[/C][C]4824.22[/C][C]44.4219[/C][C]108.6[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 42 )[/C][C]4823.23[/C][C]43.3766[/C][C]111.194[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 42 )[/C][C]4822.32[/C][C]42.2996[/C][C]114.004[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 42 )[/C][C]4822.32[/C][C]41.3431[/C][C]116.641[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 42 )[/C][C]4822.06[/C][C]40.4075[/C][C]119.336[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 42 )[/C][C]4822.27[/C][C]39.5154[/C][C]122.035[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 42 )[/C][C]4823.22[/C][C]38.7975[/C][C]124.318[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 42 )[/C][C]4824.63[/C][C]38.1309[/C][C]126.528[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 42 )[/C][C]4826.17[/C][C]37.4055[/C][C]129.023[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 42 )[/C][C]4827.12[/C][C]36.765[/C][C]131.297[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 42 )[/C][C]4828.72[/C][C]36.1924[/C][C]133.418[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 42 )[/C][C]4830.42[/C][C]35.6187[/C][C]135.615[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 42 )[/C][C]4831.69[/C][C]35.129[/C][C]137.541[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 42 )[/C][C]4833.22[/C][C]34.6375[/C][C]139.537[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 42 )[/C][C]4834.73[/C][C]34.1282[/C][C]141.664[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 42 )[/C][C]4836.17[/C][C]33.6602[/C][C]143.676[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 42 )[/C][C]4837.62[/C][C]33.1402[/C][C]145.974[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 42 )[/C][C]4839.06[/C][C]32.6478[/C][C]148.22[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 42 )[/C][C]4840.59[/C][C]32.1179[/C][C]150.713[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 42 )[/C][C]4842[/C][C]31.587[/C][C]153.291[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 42 )[/C][C]4843.35[/C][C]31.0745[/C][C]155.862[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 42 )[/C][C]4845.02[/C][C]30.5479[/C][C]158.604[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 42 )[/C][C]4846.71[/C][C]29.9634[/C][C]161.754[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 42 )[/C][C]4848.41[/C][C]29.3369[/C][C]165.266[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 42 )[/C][C]4850.33[/C][C]28.6319[/C][C]169.403[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 42 )[/C][C]4852.61[/C][C]27.9009[/C][C]173.923[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 42 )[/C][C]4854.48[/C][C]27.2209[/C][C]178.337[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 42 )[/C][C]4856.19[/C][C]26.5763[/C][C]182.726[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 42 )[/C][C]4857.34[/C][C]25.9863[/C][C]186.919[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 42 )[/C][C]4857.8[/C][C]25.4919[/C][C]190.562[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 42 )[/C][C]4858.29[/C][C]24.9456[/C][C]194.755[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 42 )[/C][C]4858.43[/C][C]24.3799[/C][C]199.28[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 42 )[/C][C]4858.27[/C][C]23.7746[/C][C]204.347[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 42 )[/C][C]4858.18[/C][C]23.1587[/C][C]209.777[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 42 )[/C][C]4857.7[/C][C]22.5048[/C][C]215.852[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 42 )[/C][C]4856.93[/C][C]21.8236[/C][C]222.554[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 42 )[/C][C]4857.08[/C][C]21.2609[/C][C]228.451[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 42 )[/C][C]4857.33[/C][C]20.7166[/C][C]234.466[/C][/ROW]
[ROW][C]Trimmed Mean ( 39 / 42 )[/C][C]4858.19[/C][C]20.334[/C][C]238.92[/C][/ROW]
[ROW][C]Trimmed Mean ( 40 / 42 )[/C][C]4858.82[/C][C]20.0135[/C][C]242.777[/C][/ROW]
[ROW][C]Trimmed Mean ( 41 / 42 )[/C][C]4859.61[/C][C]19.7122[/C][C]246.528[/C][/ROW]
[ROW][C]Trimmed Mean ( 42 / 42 )[/C][C]4860.26[/C][C]19.4136[/C][C]250.354[/C][/ROW]
[ROW][C]Median[/C][C]NA[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]NA[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]4852.62[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]4863.78[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]4863.78[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]4863.78[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]4858.43[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]4863.78[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]4863.78[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]4863.78[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]144[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301782&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301782&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic MeanNANANA
Geometric MeanNA
Harmonic MeanNA
Quadratic MeanNA
Winsorized Mean ( 1 / 42 )4825.1945.3687106.355
Winsorized Mean ( 2 / 42 )4824.9545.232106.671
Winsorized Mean ( 3 / 42 )4822.3244.6565107.987
Winsorized Mean ( 4 / 42 )4823.2744.2685108.955
Winsorized Mean ( 5 / 42 )4821.1543.7254110.26
Winsorized Mean ( 6 / 42 )4817.1942.5536113.203
Winsorized Mean ( 7 / 42 )4814.5941.9094114.881
Winsorized Mean ( 8 / 42 )4814.0641.8088115.145
Winsorized Mean ( 9 / 42 )4818.9540.8519117.961
Winsorized Mean ( 10 / 42 )4813.9939.9562120.482
Winsorized Mean ( 11 / 42 )4813.5739.5013121.859
Winsorized Mean ( 12 / 42 )4818.3238.4504125.313
Winsorized Mean ( 13 / 42 )4816.1337.9995126.742
Winsorized Mean ( 14 / 42 )4817.1337.6483127.951
Winsorized Mean ( 15 / 42 )4818.6336.819130.874
Winsorized Mean ( 16 / 42 )4819.2736.7103131.278
Winsorized Mean ( 17 / 42 )4820.0735.9215134.184
Winsorized Mean ( 18 / 42 )4819.8535.6422135.229
Winsorized Mean ( 19 / 42 )4822.3235.0345137.645
Winsorized Mean ( 20 / 42 )4824.134.2471140.861
Winsorized Mean ( 21 / 42 )4820.433.6927143.069
Winsorized Mean ( 22 / 42 )4821.5133.4773144.024
Winsorized Mean ( 23 / 42 )4822.533.0567145.886
Winsorized Mean ( 24 / 42 )4820.5232.8303146.831
Winsorized Mean ( 25 / 42 )4816.9132.0821150.143
Winsorized Mean ( 26 / 42 )4824.8330.8126156.586
Winsorized Mean ( 27 / 42 )4828.929.6689162.76
Winsorized Mean ( 28 / 42 )4838.6828.4467170.096
Winsorized Mean ( 29 / 42 )4850.4226.9576179.928
Winsorized Mean ( 30 / 42 )4850.3726.599182.352
Winsorized Mean ( 31 / 42 )4856.1325.9462187.161
Winsorized Mean ( 32 / 42 )4860.8525.3878191.464
Winsorized Mean ( 33 / 42 )4859.6524.5841197.674
Winsorized Mean ( 34 / 42 )4865.4223.9237203.373
Winsorized Mean ( 35 / 42 )4869.223.1367210.454
Winsorized Mean ( 36 / 42 )4854.6921.4958225.843
Winsorized Mean ( 37 / 42 )4853.4520.5428236.26
Winsorized Mean ( 38 / 42 )4844.8918.7565258.304
Winsorized Mean ( 39 / 42 )4849.2817.7555273.115
Winsorized Mean ( 40 / 42 )4847.7617.0349284.578
Winsorized Mean ( 41 / 42 )4850.6916.4415295.028
Winsorized Mean ( 42 / 42 )4849.3516.016302.782
Trimmed Mean ( 1 / 42 )4824.2244.4219108.6
Trimmed Mean ( 2 / 42 )4823.2343.3766111.194
Trimmed Mean ( 3 / 42 )4822.3242.2996114.004
Trimmed Mean ( 4 / 42 )4822.3241.3431116.641
Trimmed Mean ( 5 / 42 )4822.0640.4075119.336
Trimmed Mean ( 6 / 42 )4822.2739.5154122.035
Trimmed Mean ( 7 / 42 )4823.2238.7975124.318
Trimmed Mean ( 8 / 42 )4824.6338.1309126.528
Trimmed Mean ( 9 / 42 )4826.1737.4055129.023
Trimmed Mean ( 10 / 42 )4827.1236.765131.297
Trimmed Mean ( 11 / 42 )4828.7236.1924133.418
Trimmed Mean ( 12 / 42 )4830.4235.6187135.615
Trimmed Mean ( 13 / 42 )4831.6935.129137.541
Trimmed Mean ( 14 / 42 )4833.2234.6375139.537
Trimmed Mean ( 15 / 42 )4834.7334.1282141.664
Trimmed Mean ( 16 / 42 )4836.1733.6602143.676
Trimmed Mean ( 17 / 42 )4837.6233.1402145.974
Trimmed Mean ( 18 / 42 )4839.0632.6478148.22
Trimmed Mean ( 19 / 42 )4840.5932.1179150.713
Trimmed Mean ( 20 / 42 )484231.587153.291
Trimmed Mean ( 21 / 42 )4843.3531.0745155.862
Trimmed Mean ( 22 / 42 )4845.0230.5479158.604
Trimmed Mean ( 23 / 42 )4846.7129.9634161.754
Trimmed Mean ( 24 / 42 )4848.4129.3369165.266
Trimmed Mean ( 25 / 42 )4850.3328.6319169.403
Trimmed Mean ( 26 / 42 )4852.6127.9009173.923
Trimmed Mean ( 27 / 42 )4854.4827.2209178.337
Trimmed Mean ( 28 / 42 )4856.1926.5763182.726
Trimmed Mean ( 29 / 42 )4857.3425.9863186.919
Trimmed Mean ( 30 / 42 )4857.825.4919190.562
Trimmed Mean ( 31 / 42 )4858.2924.9456194.755
Trimmed Mean ( 32 / 42 )4858.4324.3799199.28
Trimmed Mean ( 33 / 42 )4858.2723.7746204.347
Trimmed Mean ( 34 / 42 )4858.1823.1587209.777
Trimmed Mean ( 35 / 42 )4857.722.5048215.852
Trimmed Mean ( 36 / 42 )4856.9321.8236222.554
Trimmed Mean ( 37 / 42 )4857.0821.2609228.451
Trimmed Mean ( 38 / 42 )4857.3320.7166234.466
Trimmed Mean ( 39 / 42 )4858.1920.334238.92
Trimmed Mean ( 40 / 42 )4858.8220.0135242.777
Trimmed Mean ( 41 / 42 )4859.6119.7122246.528
Trimmed Mean ( 42 / 42 )4860.2619.4136250.354
MedianNA
MidrangeNA
Midmean - Weighted Average at Xnp4852.62
Midmean - Weighted Average at X(n+1)p4863.78
Midmean - Empirical Distribution Function4863.78
Midmean - Empirical Distribution Function - Averaging4863.78
Midmean - Empirical Distribution Function - Interpolation4858.43
Midmean - Closest Observation4863.78
Midmean - True Basic - Statistics Graphics Toolkit4863.78
Midmean - MS Excel (old versions)4863.78
Number of observations144



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
geomean <- function(x) {
return(exp(mean(log(x))))
}
harmean <- function(x) {
return(1/mean(1/x))
}
quamean <- function(x) {
return(sqrt(mean(x*x)))
}
winmean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
win <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n
win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn
}
return(win)
}
trimean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
tri <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
tri[j,1] <- mean(x,trim=j/n)
tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2)
}
return(tri)
}
midrange <- function(x) {
return((max(x)+min(x))/2)
}
q1 <- function(data,n,p,i,f) {
np <- n*p;
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q2 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q3 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
q4 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- (data[i]+data[i+1])/2
} else {
qvalue <- data[i+1]
}
}
q5 <- function(data,n,p,i,f) {
np <- (n-1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i+1]
} else {
qvalue <- data[i+1] + f*(data[i+2]-data[i+1])
}
}
q6 <- function(data,n,p,i,f) {
np <- n*p+0.5
i <<- floor(np)
f <<- np - i
qvalue <- data[i]
}
q7 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- f*data[i] + (1-f)*data[i+1]
}
}
q8 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
if (f == 0.5) {
qvalue <- (data[i]+data[i+1])/2
} else {
if (f < 0.5) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
}
}
midmean <- function(x,def) {
x <-sort(x[!is.na(x)])
n<-length(x)
if (def==1) {
qvalue1 <- q1(x,n,0.25,i,f)
qvalue3 <- q1(x,n,0.75,i,f)
}
if (def==2) {
qvalue1 <- q2(x,n,0.25,i,f)
qvalue3 <- q2(x,n,0.75,i,f)
}
if (def==3) {
qvalue1 <- q3(x,n,0.25,i,f)
qvalue3 <- q3(x,n,0.75,i,f)
}
if (def==4) {
qvalue1 <- q4(x,n,0.25,i,f)
qvalue3 <- q4(x,n,0.75,i,f)
}
if (def==5) {
qvalue1 <- q5(x,n,0.25,i,f)
qvalue3 <- q5(x,n,0.75,i,f)
}
if (def==6) {
qvalue1 <- q6(x,n,0.25,i,f)
qvalue3 <- q6(x,n,0.75,i,f)
}
if (def==7) {
qvalue1 <- q7(x,n,0.25,i,f)
qvalue3 <- q7(x,n,0.75,i,f)
}
if (def==8) {
qvalue1 <- q8(x,n,0.25,i,f)
qvalue3 <- q8(x,n,0.75,i,f)
}
midm <- 0
myn <- 0
roundno4 <- round(n/4)
round3no4 <- round(3*n/4)
for (i in 1:n) {
if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){
midm = midm + x[i]
myn = myn + 1
}
}
midm = midm / myn
return(midm)
}
(arm <- mean(x))
sqrtn <- sqrt(length(x))
(armse <- sd(x) / sqrtn)
(armose <- arm / armse)
(geo <- geomean(x))
(har <- harmean(x))
(qua <- quamean(x))
(win <- winmean(x))
(tri <- trimean(x))
(midr <- midrange(x))
midm <- array(NA,dim=8)
for (j in 1:8) midm[j] <- midmean(x,j)
midm
bitmap(file='test1.png')
lb <- win[,1] - 2*win[,2]
ub <- win[,1] + 2*win[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
bitmap(file='test2.png')
lb <- tri[,1] - 2*tri[,2]
ub <- tri[,1] + 2*tri[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Measure',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.element(a,'S.E.',header=TRUE)
a<-table.element(a,'Value/S.E.',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Arithmetic Mean',header=TRUE)
a<-table.element(a,signif(arm,6))
a<-table.element(a, signif(armse,6))
a<-table.element(a,signif(armose,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Geometric Mean',header=TRUE)
a<-table.element(a,signif(geo,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Harmonic Mean',header=TRUE)
a<-table.element(a,signif(har,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Quadratic Mean',header=TRUE)
a<-table.element(a,signif(qua,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
for (j in 1:length(win[,1])) {
a<-table.row.start(a)
mylabel <- paste('Winsorized Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(win[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a, mylabel,header=TRUE)
a<-table.element(a,signif(win[j,1],6))
a<-table.element(a,signif(win[j,2],6))
a<-table.element(a,signif(win[j,1]/win[j,2],6))
a<-table.row.end(a)
}
for (j in 1:length(tri[,1])) {
a<-table.row.start(a)
mylabel <- paste('Trimmed Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(tri[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a, mylabel,header=TRUE)
a<-table.element(a,signif(tri[j,1],6))
a<-table.element(a,signif(tri[j,2],6))
a<-table.element(a,signif(tri[j,1]/tri[j,2],6))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'Median',header=TRUE)
a<-table.element(a,signif(median(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Midrange',header=TRUE)
a<-table.element(a,signif(midr,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Weighted Average at Xnp',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[1],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Weighted Average at X(n+1)p',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[2],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[3],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Averaging',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[4],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Interpolation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[5],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Closest Observation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[6],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'True Basic - Statistics Graphics Toolkit',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[7],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'MS Excel (old versions)',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[8],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of observations',header=TRUE)
a<-table.element(a,signif(length(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')