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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 computationWed, 30 Nov 2016 16:08:08 +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/Nov/30/t1480518545tfuqiurnhwwck9n.htm/, Retrieved Sun, 19 May 2024 00:26:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=297458, Retrieved Sun, 19 May 2024 00:26:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact41
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Central tendency ...] [2016-11-30 15:08:08] [c3c00422a8efeb721f46880d0369ae73] [Current]
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Dataseries X:
2700
3900
3850
3800
3800
3700
3950
3950
4150
4050
4200
3850
2950
4050
4200
4050
4100
4000
4100
4100
4300
4250
4300
3700
2900
4150
4300
4000
4100
4050
4100
4150
4200
4350
4450
3900
3100
4500
4450
4300
4350
4200
4250
4350
4550
4600
4700
4000
3200
4550
4700
4500
4550
4450
4550
4600
4850
4950
5050
4250
3550
5000
5000
4750
4750
4800
4900
4950
5100
5150
5150
4550
3700
5350
5200
5100
5050
4950
4950
4900
5200
5300
5500
4750
3950
5400
5300
5200
5100
5250
5200
5250
5500
5550
5600
4800
3700
4800
5400
5200
5250
5150
5100
5300
5650
5700
5800
5150
4100
5700
5900
5500
5800
5450
5950
6100
6400
6100
6150
5500
4500
6400
6150
5800
6150
6050




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=297458&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=297458&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297458&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 Mean4712.768.847568.4513
Geometric Mean4647.74
Harmonic Mean4580.1
Quadratic Mean4775.15
Winsorized Mean ( 1 / 42 )4714.2968.493768.828
Winsorized Mean ( 2 / 42 )4711.1167.59869.6931
Winsorized Mean ( 3 / 42 )4714.6866.880870.4938
Winsorized Mean ( 4 / 42 )4717.8666.283371.1771
Winsorized Mean ( 5 / 42 )4729.7663.633874.3278
Winsorized Mean ( 6 / 42 )4736.962.630675.6324
Winsorized Mean ( 7 / 42 )4734.1362.153576.1682
Winsorized Mean ( 8 / 42 )4727.7861.107677.368
Winsorized Mean ( 9 / 42 )4724.2160.544478.0287
Winsorized Mean ( 10 / 42 )4724.2158.300681.0318
Winsorized Mean ( 11 / 42 )4724.2158.300681.0318
Winsorized Mean ( 12 / 42 )4728.9757.708581.9458
Winsorized Mean ( 13 / 42 )4718.6556.221683.9295
Winsorized Mean ( 14 / 42 )4724.2155.548485.0466
Winsorized Mean ( 15 / 42 )4718.2554.724786.218
Winsorized Mean ( 16 / 42 )4718.2553.123488.8169
Winsorized Mean ( 17 / 42 )4711.5152.242390.1857
Winsorized Mean ( 18 / 42 )4704.3751.340891.6301
Winsorized Mean ( 19 / 42 )4711.950.472193.3565
Winsorized Mean ( 20 / 42 )4711.950.472193.3565
Winsorized Mean ( 21 / 42 )4711.950.472193.3565
Winsorized Mean ( 22 / 42 )4711.948.424197.3049
Winsorized Mean ( 23 / 42 )4702.7847.329799.3622
Winsorized Mean ( 24 / 42 )4702.7847.329799.3622
Winsorized Mean ( 25 / 42 )4692.8646.1802101.621
Winsorized Mean ( 26 / 42 )4692.8643.8892106.925
Winsorized Mean ( 27 / 42 )4692.8643.8892106.925
Winsorized Mean ( 28 / 42 )4692.8643.8892106.925
Winsorized Mean ( 29 / 42 )4681.3542.6381109.793
Winsorized Mean ( 30 / 42 )4681.3542.6381109.793
Winsorized Mean ( 31 / 42 )4681.3542.6381109.793
Winsorized Mean ( 32 / 42 )4681.3539.9314117.235
Winsorized Mean ( 33 / 42 )4681.3539.9314117.235
Winsorized Mean ( 34 / 42 )4681.3539.9314117.235
Winsorized Mean ( 35 / 42 )4695.2438.4767122.028
Winsorized Mean ( 36 / 42 )4695.2438.4767122.028
Winsorized Mean ( 37 / 42 )4680.5636.9597126.639
Winsorized Mean ( 38 / 42 )4680.5636.9597126.639
Winsorized Mean ( 39 / 42 )4696.0335.3738132.755
Winsorized Mean ( 40 / 42 )4696.0335.3738132.755
Winsorized Mean ( 41 / 42 )4679.7633.7271138.754
Winsorized Mean ( 42 / 42 )4696.4332.0524146.523
Trimmed Mean ( 1 / 42 )4715.3266.651570.7459
Trimmed Mean ( 2 / 42 )4716.3964.609572.9985
Trimmed Mean ( 3 / 42 )4719.1762.871375.0608
Trimmed Mean ( 4 / 42 )4720.7661.239777.0867
Trimmed Mean ( 5 / 42 )4721.5559.622279.1912
Trimmed Mean ( 6 / 42 )4719.7458.541680.622
Trimmed Mean ( 7 / 42 )4716.5257.56981.9281
Trimmed Mean ( 8 / 42 )4713.6456.584483.3027
Trimmed Mean ( 9 / 42 )4711.5755.68584.6112
Trimmed Mean ( 10 / 42 )4709.9154.778185.9816
Trimmed Mean ( 11 / 42 )4708.1754.124686.9876
Trimmed Mean ( 12 / 42 )4706.3753.387888.1544
Trimmed Mean ( 13 / 42 )470452.640889.3604
Trimmed Mean ( 14 / 42 )4702.5552.007790.4202
Trimmed Mean ( 15 / 42 )4700.5251.376391.492
Trimmed Mean ( 16 / 42 )4698.9450.766192.5604
Trimmed Mean ( 17 / 42 )4697.2850.270293.4407
Trimmed Mean ( 18 / 42 )4696.1149.807594.2851
Trimmed Mean ( 19 / 42 )4695.4549.379995.0884
Trimmed Mean ( 20 / 42 )4694.1948.980295.8385
Trimmed Mean ( 21 / 42 )4692.8648.508696.7428
Trimmed Mean ( 22 / 42 )4691.4647.954397.832
Trimmed Mean ( 23 / 42 )469047.545898.6418
Trimmed Mean ( 24 / 42 )4689.147.187499.372
Trimmed Mean ( 25 / 42 )4688.1646.7531100.275
Trimmed Mean ( 26 / 42 )4687.8446.3676101.102
Trimmed Mean ( 27 / 42 )4687.546.1629101.543
Trimmed Mean ( 28 / 42 )4687.1445.8944102.129
Trimmed Mean ( 29 / 42 )4686.7645.5507102.891
Trimmed Mean ( 30 / 42 )4687.1245.2693103.539
Trimmed Mean ( 31 / 42 )4687.544.904104.389
Trimmed Mean ( 32 / 42 )4687.944.4379105.493
Trimmed Mean ( 33 / 42 )4688.3344.203106.064
Trimmed Mean ( 34 / 42 )4688.7943.8788106.858
Trimmed Mean ( 35 / 42 )4689.2943.4456107.935
Trimmed Mean ( 36 / 42 )4688.8943.0872108.823
Trimmed Mean ( 37 / 42 )4688.4642.6015110.054
Trimmed Mean ( 38 / 42 )468942.1922111.134
Trimmed Mean ( 39 / 42 )4689.5841.6301112.649
Trimmed Mean ( 40 / 42 )4689.1341.1464113.962
Trimmed Mean ( 41 / 42 )4688.6440.4737115.844
Trimmed Mean ( 42 / 42 )4689.2939.8726117.607
Median4700
Midrange4550
Midmean - Weighted Average at Xnp4636.03
Midmean - Weighted Average at X(n+1)p4661.97
Midmean - Empirical Distribution Function4661.97
Midmean - Empirical Distribution Function - Averaging4661.97
Midmean - Empirical Distribution Function - Interpolation4687.9
Midmean - Closest Observation4661.97
Midmean - True Basic - Statistics Graphics Toolkit4661.97
Midmean - MS Excel (old versions)4661.97
Number of observations126

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 4712.7 & 68.8475 & 68.4513 \tabularnewline
Geometric Mean & 4647.74 &  &  \tabularnewline
Harmonic Mean & 4580.1 &  &  \tabularnewline
Quadratic Mean & 4775.15 &  &  \tabularnewline
Winsorized Mean ( 1 / 42 ) & 4714.29 & 68.4937 & 68.828 \tabularnewline
Winsorized Mean ( 2 / 42 ) & 4711.11 & 67.598 & 69.6931 \tabularnewline
Winsorized Mean ( 3 / 42 ) & 4714.68 & 66.8808 & 70.4938 \tabularnewline
Winsorized Mean ( 4 / 42 ) & 4717.86 & 66.2833 & 71.1771 \tabularnewline
Winsorized Mean ( 5 / 42 ) & 4729.76 & 63.6338 & 74.3278 \tabularnewline
Winsorized Mean ( 6 / 42 ) & 4736.9 & 62.6306 & 75.6324 \tabularnewline
Winsorized Mean ( 7 / 42 ) & 4734.13 & 62.1535 & 76.1682 \tabularnewline
Winsorized Mean ( 8 / 42 ) & 4727.78 & 61.1076 & 77.368 \tabularnewline
Winsorized Mean ( 9 / 42 ) & 4724.21 & 60.5444 & 78.0287 \tabularnewline
Winsorized Mean ( 10 / 42 ) & 4724.21 & 58.3006 & 81.0318 \tabularnewline
Winsorized Mean ( 11 / 42 ) & 4724.21 & 58.3006 & 81.0318 \tabularnewline
Winsorized Mean ( 12 / 42 ) & 4728.97 & 57.7085 & 81.9458 \tabularnewline
Winsorized Mean ( 13 / 42 ) & 4718.65 & 56.2216 & 83.9295 \tabularnewline
Winsorized Mean ( 14 / 42 ) & 4724.21 & 55.5484 & 85.0466 \tabularnewline
Winsorized Mean ( 15 / 42 ) & 4718.25 & 54.7247 & 86.218 \tabularnewline
Winsorized Mean ( 16 / 42 ) & 4718.25 & 53.1234 & 88.8169 \tabularnewline
Winsorized Mean ( 17 / 42 ) & 4711.51 & 52.2423 & 90.1857 \tabularnewline
Winsorized Mean ( 18 / 42 ) & 4704.37 & 51.3408 & 91.6301 \tabularnewline
Winsorized Mean ( 19 / 42 ) & 4711.9 & 50.4721 & 93.3565 \tabularnewline
Winsorized Mean ( 20 / 42 ) & 4711.9 & 50.4721 & 93.3565 \tabularnewline
Winsorized Mean ( 21 / 42 ) & 4711.9 & 50.4721 & 93.3565 \tabularnewline
Winsorized Mean ( 22 / 42 ) & 4711.9 & 48.4241 & 97.3049 \tabularnewline
Winsorized Mean ( 23 / 42 ) & 4702.78 & 47.3297 & 99.3622 \tabularnewline
Winsorized Mean ( 24 / 42 ) & 4702.78 & 47.3297 & 99.3622 \tabularnewline
Winsorized Mean ( 25 / 42 ) & 4692.86 & 46.1802 & 101.621 \tabularnewline
Winsorized Mean ( 26 / 42 ) & 4692.86 & 43.8892 & 106.925 \tabularnewline
Winsorized Mean ( 27 / 42 ) & 4692.86 & 43.8892 & 106.925 \tabularnewline
Winsorized Mean ( 28 / 42 ) & 4692.86 & 43.8892 & 106.925 \tabularnewline
Winsorized Mean ( 29 / 42 ) & 4681.35 & 42.6381 & 109.793 \tabularnewline
Winsorized Mean ( 30 / 42 ) & 4681.35 & 42.6381 & 109.793 \tabularnewline
Winsorized Mean ( 31 / 42 ) & 4681.35 & 42.6381 & 109.793 \tabularnewline
Winsorized Mean ( 32 / 42 ) & 4681.35 & 39.9314 & 117.235 \tabularnewline
Winsorized Mean ( 33 / 42 ) & 4681.35 & 39.9314 & 117.235 \tabularnewline
Winsorized Mean ( 34 / 42 ) & 4681.35 & 39.9314 & 117.235 \tabularnewline
Winsorized Mean ( 35 / 42 ) & 4695.24 & 38.4767 & 122.028 \tabularnewline
Winsorized Mean ( 36 / 42 ) & 4695.24 & 38.4767 & 122.028 \tabularnewline
Winsorized Mean ( 37 / 42 ) & 4680.56 & 36.9597 & 126.639 \tabularnewline
Winsorized Mean ( 38 / 42 ) & 4680.56 & 36.9597 & 126.639 \tabularnewline
Winsorized Mean ( 39 / 42 ) & 4696.03 & 35.3738 & 132.755 \tabularnewline
Winsorized Mean ( 40 / 42 ) & 4696.03 & 35.3738 & 132.755 \tabularnewline
Winsorized Mean ( 41 / 42 ) & 4679.76 & 33.7271 & 138.754 \tabularnewline
Winsorized Mean ( 42 / 42 ) & 4696.43 & 32.0524 & 146.523 \tabularnewline
Trimmed Mean ( 1 / 42 ) & 4715.32 & 66.6515 & 70.7459 \tabularnewline
Trimmed Mean ( 2 / 42 ) & 4716.39 & 64.6095 & 72.9985 \tabularnewline
Trimmed Mean ( 3 / 42 ) & 4719.17 & 62.8713 & 75.0608 \tabularnewline
Trimmed Mean ( 4 / 42 ) & 4720.76 & 61.2397 & 77.0867 \tabularnewline
Trimmed Mean ( 5 / 42 ) & 4721.55 & 59.6222 & 79.1912 \tabularnewline
Trimmed Mean ( 6 / 42 ) & 4719.74 & 58.5416 & 80.622 \tabularnewline
Trimmed Mean ( 7 / 42 ) & 4716.52 & 57.569 & 81.9281 \tabularnewline
Trimmed Mean ( 8 / 42 ) & 4713.64 & 56.5844 & 83.3027 \tabularnewline
Trimmed Mean ( 9 / 42 ) & 4711.57 & 55.685 & 84.6112 \tabularnewline
Trimmed Mean ( 10 / 42 ) & 4709.91 & 54.7781 & 85.9816 \tabularnewline
Trimmed Mean ( 11 / 42 ) & 4708.17 & 54.1246 & 86.9876 \tabularnewline
Trimmed Mean ( 12 / 42 ) & 4706.37 & 53.3878 & 88.1544 \tabularnewline
Trimmed Mean ( 13 / 42 ) & 4704 & 52.6408 & 89.3604 \tabularnewline
Trimmed Mean ( 14 / 42 ) & 4702.55 & 52.0077 & 90.4202 \tabularnewline
Trimmed Mean ( 15 / 42 ) & 4700.52 & 51.3763 & 91.492 \tabularnewline
Trimmed Mean ( 16 / 42 ) & 4698.94 & 50.7661 & 92.5604 \tabularnewline
Trimmed Mean ( 17 / 42 ) & 4697.28 & 50.2702 & 93.4407 \tabularnewline
Trimmed Mean ( 18 / 42 ) & 4696.11 & 49.8075 & 94.2851 \tabularnewline
Trimmed Mean ( 19 / 42 ) & 4695.45 & 49.3799 & 95.0884 \tabularnewline
Trimmed Mean ( 20 / 42 ) & 4694.19 & 48.9802 & 95.8385 \tabularnewline
Trimmed Mean ( 21 / 42 ) & 4692.86 & 48.5086 & 96.7428 \tabularnewline
Trimmed Mean ( 22 / 42 ) & 4691.46 & 47.9543 & 97.832 \tabularnewline
Trimmed Mean ( 23 / 42 ) & 4690 & 47.5458 & 98.6418 \tabularnewline
Trimmed Mean ( 24 / 42 ) & 4689.1 & 47.1874 & 99.372 \tabularnewline
Trimmed Mean ( 25 / 42 ) & 4688.16 & 46.7531 & 100.275 \tabularnewline
Trimmed Mean ( 26 / 42 ) & 4687.84 & 46.3676 & 101.102 \tabularnewline
Trimmed Mean ( 27 / 42 ) & 4687.5 & 46.1629 & 101.543 \tabularnewline
Trimmed Mean ( 28 / 42 ) & 4687.14 & 45.8944 & 102.129 \tabularnewline
Trimmed Mean ( 29 / 42 ) & 4686.76 & 45.5507 & 102.891 \tabularnewline
Trimmed Mean ( 30 / 42 ) & 4687.12 & 45.2693 & 103.539 \tabularnewline
Trimmed Mean ( 31 / 42 ) & 4687.5 & 44.904 & 104.389 \tabularnewline
Trimmed Mean ( 32 / 42 ) & 4687.9 & 44.4379 & 105.493 \tabularnewline
Trimmed Mean ( 33 / 42 ) & 4688.33 & 44.203 & 106.064 \tabularnewline
Trimmed Mean ( 34 / 42 ) & 4688.79 & 43.8788 & 106.858 \tabularnewline
Trimmed Mean ( 35 / 42 ) & 4689.29 & 43.4456 & 107.935 \tabularnewline
Trimmed Mean ( 36 / 42 ) & 4688.89 & 43.0872 & 108.823 \tabularnewline
Trimmed Mean ( 37 / 42 ) & 4688.46 & 42.6015 & 110.054 \tabularnewline
Trimmed Mean ( 38 / 42 ) & 4689 & 42.1922 & 111.134 \tabularnewline
Trimmed Mean ( 39 / 42 ) & 4689.58 & 41.6301 & 112.649 \tabularnewline
Trimmed Mean ( 40 / 42 ) & 4689.13 & 41.1464 & 113.962 \tabularnewline
Trimmed Mean ( 41 / 42 ) & 4688.64 & 40.4737 & 115.844 \tabularnewline
Trimmed Mean ( 42 / 42 ) & 4689.29 & 39.8726 & 117.607 \tabularnewline
Median & 4700 &  &  \tabularnewline
Midrange & 4550 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 4636.03 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 4661.97 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 4661.97 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 4661.97 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 4687.9 &  &  \tabularnewline
Midmean - Closest Observation & 4661.97 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 4661.97 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 4661.97 &  &  \tabularnewline
Number of observations & 126 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297458&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]4712.7[/C][C]68.8475[/C][C]68.4513[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]4647.74[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]4580.1[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]4775.15[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 42 )[/C][C]4714.29[/C][C]68.4937[/C][C]68.828[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 42 )[/C][C]4711.11[/C][C]67.598[/C][C]69.6931[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 42 )[/C][C]4714.68[/C][C]66.8808[/C][C]70.4938[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 42 )[/C][C]4717.86[/C][C]66.2833[/C][C]71.1771[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 42 )[/C][C]4729.76[/C][C]63.6338[/C][C]74.3278[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 42 )[/C][C]4736.9[/C][C]62.6306[/C][C]75.6324[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 42 )[/C][C]4734.13[/C][C]62.1535[/C][C]76.1682[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 42 )[/C][C]4727.78[/C][C]61.1076[/C][C]77.368[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 42 )[/C][C]4724.21[/C][C]60.5444[/C][C]78.0287[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 42 )[/C][C]4724.21[/C][C]58.3006[/C][C]81.0318[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 42 )[/C][C]4724.21[/C][C]58.3006[/C][C]81.0318[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 42 )[/C][C]4728.97[/C][C]57.7085[/C][C]81.9458[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 42 )[/C][C]4718.65[/C][C]56.2216[/C][C]83.9295[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 42 )[/C][C]4724.21[/C][C]55.5484[/C][C]85.0466[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 42 )[/C][C]4718.25[/C][C]54.7247[/C][C]86.218[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 42 )[/C][C]4718.25[/C][C]53.1234[/C][C]88.8169[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 42 )[/C][C]4711.51[/C][C]52.2423[/C][C]90.1857[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 42 )[/C][C]4704.37[/C][C]51.3408[/C][C]91.6301[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 42 )[/C][C]4711.9[/C][C]50.4721[/C][C]93.3565[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 42 )[/C][C]4711.9[/C][C]50.4721[/C][C]93.3565[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 42 )[/C][C]4711.9[/C][C]50.4721[/C][C]93.3565[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 42 )[/C][C]4711.9[/C][C]48.4241[/C][C]97.3049[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 42 )[/C][C]4702.78[/C][C]47.3297[/C][C]99.3622[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 42 )[/C][C]4702.78[/C][C]47.3297[/C][C]99.3622[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 42 )[/C][C]4692.86[/C][C]46.1802[/C][C]101.621[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 42 )[/C][C]4692.86[/C][C]43.8892[/C][C]106.925[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 42 )[/C][C]4692.86[/C][C]43.8892[/C][C]106.925[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 42 )[/C][C]4692.86[/C][C]43.8892[/C][C]106.925[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 42 )[/C][C]4681.35[/C][C]42.6381[/C][C]109.793[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 42 )[/C][C]4681.35[/C][C]42.6381[/C][C]109.793[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 42 )[/C][C]4681.35[/C][C]42.6381[/C][C]109.793[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 42 )[/C][C]4681.35[/C][C]39.9314[/C][C]117.235[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 42 )[/C][C]4681.35[/C][C]39.9314[/C][C]117.235[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 42 )[/C][C]4681.35[/C][C]39.9314[/C][C]117.235[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 42 )[/C][C]4695.24[/C][C]38.4767[/C][C]122.028[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 42 )[/C][C]4695.24[/C][C]38.4767[/C][C]122.028[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 42 )[/C][C]4680.56[/C][C]36.9597[/C][C]126.639[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 42 )[/C][C]4680.56[/C][C]36.9597[/C][C]126.639[/C][/ROW]
[ROW][C]Winsorized Mean ( 39 / 42 )[/C][C]4696.03[/C][C]35.3738[/C][C]132.755[/C][/ROW]
[ROW][C]Winsorized Mean ( 40 / 42 )[/C][C]4696.03[/C][C]35.3738[/C][C]132.755[/C][/ROW]
[ROW][C]Winsorized Mean ( 41 / 42 )[/C][C]4679.76[/C][C]33.7271[/C][C]138.754[/C][/ROW]
[ROW][C]Winsorized Mean ( 42 / 42 )[/C][C]4696.43[/C][C]32.0524[/C][C]146.523[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 42 )[/C][C]4715.32[/C][C]66.6515[/C][C]70.7459[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 42 )[/C][C]4716.39[/C][C]64.6095[/C][C]72.9985[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 42 )[/C][C]4719.17[/C][C]62.8713[/C][C]75.0608[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 42 )[/C][C]4720.76[/C][C]61.2397[/C][C]77.0867[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 42 )[/C][C]4721.55[/C][C]59.6222[/C][C]79.1912[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 42 )[/C][C]4719.74[/C][C]58.5416[/C][C]80.622[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 42 )[/C][C]4716.52[/C][C]57.569[/C][C]81.9281[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 42 )[/C][C]4713.64[/C][C]56.5844[/C][C]83.3027[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 42 )[/C][C]4711.57[/C][C]55.685[/C][C]84.6112[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 42 )[/C][C]4709.91[/C][C]54.7781[/C][C]85.9816[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 42 )[/C][C]4708.17[/C][C]54.1246[/C][C]86.9876[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 42 )[/C][C]4706.37[/C][C]53.3878[/C][C]88.1544[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 42 )[/C][C]4704[/C][C]52.6408[/C][C]89.3604[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 42 )[/C][C]4702.55[/C][C]52.0077[/C][C]90.4202[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 42 )[/C][C]4700.52[/C][C]51.3763[/C][C]91.492[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 42 )[/C][C]4698.94[/C][C]50.7661[/C][C]92.5604[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 42 )[/C][C]4697.28[/C][C]50.2702[/C][C]93.4407[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 42 )[/C][C]4696.11[/C][C]49.8075[/C][C]94.2851[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 42 )[/C][C]4695.45[/C][C]49.3799[/C][C]95.0884[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 42 )[/C][C]4694.19[/C][C]48.9802[/C][C]95.8385[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 42 )[/C][C]4692.86[/C][C]48.5086[/C][C]96.7428[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 42 )[/C][C]4691.46[/C][C]47.9543[/C][C]97.832[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 42 )[/C][C]4690[/C][C]47.5458[/C][C]98.6418[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 42 )[/C][C]4689.1[/C][C]47.1874[/C][C]99.372[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 42 )[/C][C]4688.16[/C][C]46.7531[/C][C]100.275[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 42 )[/C][C]4687.84[/C][C]46.3676[/C][C]101.102[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 42 )[/C][C]4687.5[/C][C]46.1629[/C][C]101.543[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 42 )[/C][C]4687.14[/C][C]45.8944[/C][C]102.129[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 42 )[/C][C]4686.76[/C][C]45.5507[/C][C]102.891[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 42 )[/C][C]4687.12[/C][C]45.2693[/C][C]103.539[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 42 )[/C][C]4687.5[/C][C]44.904[/C][C]104.389[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 42 )[/C][C]4687.9[/C][C]44.4379[/C][C]105.493[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 42 )[/C][C]4688.33[/C][C]44.203[/C][C]106.064[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 42 )[/C][C]4688.79[/C][C]43.8788[/C][C]106.858[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 42 )[/C][C]4689.29[/C][C]43.4456[/C][C]107.935[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 42 )[/C][C]4688.89[/C][C]43.0872[/C][C]108.823[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 42 )[/C][C]4688.46[/C][C]42.6015[/C][C]110.054[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 42 )[/C][C]4689[/C][C]42.1922[/C][C]111.134[/C][/ROW]
[ROW][C]Trimmed Mean ( 39 / 42 )[/C][C]4689.58[/C][C]41.6301[/C][C]112.649[/C][/ROW]
[ROW][C]Trimmed Mean ( 40 / 42 )[/C][C]4689.13[/C][C]41.1464[/C][C]113.962[/C][/ROW]
[ROW][C]Trimmed Mean ( 41 / 42 )[/C][C]4688.64[/C][C]40.4737[/C][C]115.844[/C][/ROW]
[ROW][C]Trimmed Mean ( 42 / 42 )[/C][C]4689.29[/C][C]39.8726[/C][C]117.607[/C][/ROW]
[ROW][C]Median[/C][C]4700[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]4550[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]4636.03[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]4661.97[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]4661.97[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]4661.97[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]4687.9[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]4661.97[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]4661.97[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]4661.97[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]126[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=297458&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297458&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 Mean4712.768.847568.4513
Geometric Mean4647.74
Harmonic Mean4580.1
Quadratic Mean4775.15
Winsorized Mean ( 1 / 42 )4714.2968.493768.828
Winsorized Mean ( 2 / 42 )4711.1167.59869.6931
Winsorized Mean ( 3 / 42 )4714.6866.880870.4938
Winsorized Mean ( 4 / 42 )4717.8666.283371.1771
Winsorized Mean ( 5 / 42 )4729.7663.633874.3278
Winsorized Mean ( 6 / 42 )4736.962.630675.6324
Winsorized Mean ( 7 / 42 )4734.1362.153576.1682
Winsorized Mean ( 8 / 42 )4727.7861.107677.368
Winsorized Mean ( 9 / 42 )4724.2160.544478.0287
Winsorized Mean ( 10 / 42 )4724.2158.300681.0318
Winsorized Mean ( 11 / 42 )4724.2158.300681.0318
Winsorized Mean ( 12 / 42 )4728.9757.708581.9458
Winsorized Mean ( 13 / 42 )4718.6556.221683.9295
Winsorized Mean ( 14 / 42 )4724.2155.548485.0466
Winsorized Mean ( 15 / 42 )4718.2554.724786.218
Winsorized Mean ( 16 / 42 )4718.2553.123488.8169
Winsorized Mean ( 17 / 42 )4711.5152.242390.1857
Winsorized Mean ( 18 / 42 )4704.3751.340891.6301
Winsorized Mean ( 19 / 42 )4711.950.472193.3565
Winsorized Mean ( 20 / 42 )4711.950.472193.3565
Winsorized Mean ( 21 / 42 )4711.950.472193.3565
Winsorized Mean ( 22 / 42 )4711.948.424197.3049
Winsorized Mean ( 23 / 42 )4702.7847.329799.3622
Winsorized Mean ( 24 / 42 )4702.7847.329799.3622
Winsorized Mean ( 25 / 42 )4692.8646.1802101.621
Winsorized Mean ( 26 / 42 )4692.8643.8892106.925
Winsorized Mean ( 27 / 42 )4692.8643.8892106.925
Winsorized Mean ( 28 / 42 )4692.8643.8892106.925
Winsorized Mean ( 29 / 42 )4681.3542.6381109.793
Winsorized Mean ( 30 / 42 )4681.3542.6381109.793
Winsorized Mean ( 31 / 42 )4681.3542.6381109.793
Winsorized Mean ( 32 / 42 )4681.3539.9314117.235
Winsorized Mean ( 33 / 42 )4681.3539.9314117.235
Winsorized Mean ( 34 / 42 )4681.3539.9314117.235
Winsorized Mean ( 35 / 42 )4695.2438.4767122.028
Winsorized Mean ( 36 / 42 )4695.2438.4767122.028
Winsorized Mean ( 37 / 42 )4680.5636.9597126.639
Winsorized Mean ( 38 / 42 )4680.5636.9597126.639
Winsorized Mean ( 39 / 42 )4696.0335.3738132.755
Winsorized Mean ( 40 / 42 )4696.0335.3738132.755
Winsorized Mean ( 41 / 42 )4679.7633.7271138.754
Winsorized Mean ( 42 / 42 )4696.4332.0524146.523
Trimmed Mean ( 1 / 42 )4715.3266.651570.7459
Trimmed Mean ( 2 / 42 )4716.3964.609572.9985
Trimmed Mean ( 3 / 42 )4719.1762.871375.0608
Trimmed Mean ( 4 / 42 )4720.7661.239777.0867
Trimmed Mean ( 5 / 42 )4721.5559.622279.1912
Trimmed Mean ( 6 / 42 )4719.7458.541680.622
Trimmed Mean ( 7 / 42 )4716.5257.56981.9281
Trimmed Mean ( 8 / 42 )4713.6456.584483.3027
Trimmed Mean ( 9 / 42 )4711.5755.68584.6112
Trimmed Mean ( 10 / 42 )4709.9154.778185.9816
Trimmed Mean ( 11 / 42 )4708.1754.124686.9876
Trimmed Mean ( 12 / 42 )4706.3753.387888.1544
Trimmed Mean ( 13 / 42 )470452.640889.3604
Trimmed Mean ( 14 / 42 )4702.5552.007790.4202
Trimmed Mean ( 15 / 42 )4700.5251.376391.492
Trimmed Mean ( 16 / 42 )4698.9450.766192.5604
Trimmed Mean ( 17 / 42 )4697.2850.270293.4407
Trimmed Mean ( 18 / 42 )4696.1149.807594.2851
Trimmed Mean ( 19 / 42 )4695.4549.379995.0884
Trimmed Mean ( 20 / 42 )4694.1948.980295.8385
Trimmed Mean ( 21 / 42 )4692.8648.508696.7428
Trimmed Mean ( 22 / 42 )4691.4647.954397.832
Trimmed Mean ( 23 / 42 )469047.545898.6418
Trimmed Mean ( 24 / 42 )4689.147.187499.372
Trimmed Mean ( 25 / 42 )4688.1646.7531100.275
Trimmed Mean ( 26 / 42 )4687.8446.3676101.102
Trimmed Mean ( 27 / 42 )4687.546.1629101.543
Trimmed Mean ( 28 / 42 )4687.1445.8944102.129
Trimmed Mean ( 29 / 42 )4686.7645.5507102.891
Trimmed Mean ( 30 / 42 )4687.1245.2693103.539
Trimmed Mean ( 31 / 42 )4687.544.904104.389
Trimmed Mean ( 32 / 42 )4687.944.4379105.493
Trimmed Mean ( 33 / 42 )4688.3344.203106.064
Trimmed Mean ( 34 / 42 )4688.7943.8788106.858
Trimmed Mean ( 35 / 42 )4689.2943.4456107.935
Trimmed Mean ( 36 / 42 )4688.8943.0872108.823
Trimmed Mean ( 37 / 42 )4688.4642.6015110.054
Trimmed Mean ( 38 / 42 )468942.1922111.134
Trimmed Mean ( 39 / 42 )4689.5841.6301112.649
Trimmed Mean ( 40 / 42 )4689.1341.1464113.962
Trimmed Mean ( 41 / 42 )4688.6440.4737115.844
Trimmed Mean ( 42 / 42 )4689.2939.8726117.607
Median4700
Midrange4550
Midmean - Weighted Average at Xnp4636.03
Midmean - Weighted Average at X(n+1)p4661.97
Midmean - Empirical Distribution Function4661.97
Midmean - Empirical Distribution Function - Averaging4661.97
Midmean - Empirical Distribution Function - Interpolation4687.9
Midmean - Closest Observation4661.97
Midmean - True Basic - Statistics Graphics Toolkit4661.97
Midmean - MS Excel (old versions)4661.97
Number of observations126



Parameters (Session):
par1 = 200 ; par2 = 5 ; par3 = 0 ; par4 = P1 P5 Q1 Q3 P95 P99 ;
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')