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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, 06 Dec 2016 13:14:27 +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/06/t14810264937rpchguqszoogv6.htm/, Retrieved Fri, 01 Nov 2024 03:38:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=297808, Retrieved Fri, 01 Nov 2024 03:38:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [F1 Competitie Cen...] [2016-12-06 12:14:27] [15b172d40fa89b8c3dac8ac54fed18ba] [Current]
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Dataseries X:
4861
3665
6683
6824
7811
7242
7458
7856
6477
7577
5999
4628
4144
3778
4320
4948
5132
5460
5598
5583
5917
6458
5079
4486
3763
3531
5014
5162
4880
4720
4631
4315
4268
4172
3432
2705
2359
2729
4043
4301
4576
4984
4854
4847
5038
4950
4566
3943
3328
3106
4821
4876
5691
6576
5850
6499
6244
5855
5304
4035
4167
4791
5215
5949
6459
6680
6413
6626
6642
6529
5691
4743
3535
3314
5564
6287
6738
6355
6745
7005
6575
6719
5196
4304
4967
4175
5579
7009
6997
7062
7214
6918
6874
7175
5375
4675
4422
4567
5971
6560
6415
6727
7077
6589
6800
6982
6118
4500
3195
4482
6619
6237
6520
7043
6188
6774
6118
6308
5230
4587
4976
4561
5456
5691
6163
6133




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=297808&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=297808&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297808&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 Mean5470.02109.84249.799
Geometric Mean5318.51
Harmonic Mean5151.37
Quadratic Mean5606.19
Winsorized Mean ( 1 / 42 )5472.41109.19150.1179
Winsorized Mean ( 2 / 42 )5469.08108.50750.4031
Winsorized Mean ( 3 / 42 )5475.22106.36851.4745
Winsorized Mean ( 4 / 42 )5471.19104.89652.1582
Winsorized Mean ( 5 / 42 )5474.8103.94452.6707
Winsorized Mean ( 6 / 42 )5473.61103.58752.8407
Winsorized Mean ( 7 / 42 )5473.94101.94553.6951
Winsorized Mean ( 8 / 42 )5479.28100.83654.3386
Winsorized Mean ( 9 / 42 )5478.21100.62254.4434
Winsorized Mean ( 10 / 42 )5485.8398.729255.5644
Winsorized Mean ( 11 / 42 )5494.0397.446756.3798
Winsorized Mean ( 12 / 42 )5494.797.149956.559
Winsorized Mean ( 13 / 42 )5510.1794.625858.2312
Winsorized Mean ( 14 / 42 )5513.2992.419459.6551
Winsorized Mean ( 15 / 42 )550991.667160.0979
Winsorized Mean ( 16 / 42 )5515.4889.30861.7579
Winsorized Mean ( 17 / 42 )5515.3488.550762.2846
Winsorized Mean ( 18 / 42 )5512.3488.035262.6152
Winsorized Mean ( 19 / 42 )5508.4287.482162.9662
Winsorized Mean ( 20 / 42 )5522.0785.590664.5173
Winsorized Mean ( 21 / 42 )5525.7484.742265.2065
Winsorized Mean ( 22 / 42 )5524.8784.523565.3649
Winsorized Mean ( 23 / 42 )5520.383.554466.0683
Winsorized Mean ( 24 / 42 )5520.6883.38166.2103
Winsorized Mean ( 25 / 42 )5533.3880.257568.9453
Winsorized Mean ( 26 / 42 )5542.4678.538270.5702
Winsorized Mean ( 27 / 42 )5541.8278.280370.7945
Winsorized Mean ( 28 / 42 )5538.2677.215371.7249
Winsorized Mean ( 29 / 42 )5549.3175.39873.6002
Winsorized Mean ( 30 / 42 )5550.2675.247373.7602
Winsorized Mean ( 31 / 42 )5546.8274.820674.1349
Winsorized Mean ( 32 / 42 )5541.2373.732975.1528
Winsorized Mean ( 33 / 42 )5541.7573.179375.7284
Winsorized Mean ( 34 / 42 )5547.1571.427377.6615
Winsorized Mean ( 35 / 42 )5541.8770.692378.3943
Winsorized Mean ( 36 / 42 )5549.368.861980.5859
Winsorized Mean ( 37 / 42 )5562.2267.500182.4032
Winsorized Mean ( 38 / 42 )5556.1965.439884.9054
Winsorized Mean ( 39 / 42 )5570.4363.911387.1588
Winsorized Mean ( 40 / 42 )5561.5461.056191.089
Winsorized Mean ( 41 / 42 )5554.7158.656594.6989
Winsorized Mean ( 42 / 42 )5550.0457.714296.1642
Trimmed Mean ( 1 / 42 )5475.87107.0151.1717
Trimmed Mean ( 2 / 42 )5479.44104.60252.3837
Trimmed Mean ( 3 / 42 )5484.88102.33753.5964
Trimmed Mean ( 4 / 42 )5488.32100.69954.502
Trimmed Mean ( 5 / 42 )5492.9799.34655.2913
Trimmed Mean ( 6 / 42 )5496.9998.091256.0396
Trimmed Mean ( 7 / 42 )5501.3896.773456.848
Trimmed Mean ( 8 / 42 )5505.8695.634357.572
Trimmed Mean ( 9 / 42 )5509.7494.563458.2651
Trimmed Mean ( 10 / 42 )5513.9193.395659.0382
Trimmed Mean ( 11 / 42 )5517.3192.386259.7201
Trimmed Mean ( 12 / 42 )5519.9291.439960.3667
Trimmed Mean ( 13 / 42 )5522.5790.409261.0842
Trimmed Mean ( 14 / 42 )5523.889.588361.6576
Trimmed Mean ( 15 / 42 )5524.7888.935862.121
Trimmed Mean ( 16 / 42 )5526.1988.273262.6033
Trimmed Mean ( 17 / 42 )5527.1187.790462.958
Trimmed Mean ( 18 / 42 )5528.0887.305363.3189
Trimmed Mean ( 19 / 42 )5529.3386.785363.7128
Trimmed Mean ( 20 / 42 )5530.9486.226864.1441
Trimmed Mean ( 21 / 42 )5531.6185.777364.488
Trimmed Mean ( 22 / 42 )5532.0485.323964.8357
Trimmed Mean ( 23 / 42 )5532.5584.791265.2491
Trimmed Mean ( 24 / 42 )5533.4184.250965.6778
Trimmed Mean ( 25 / 42 )5534.2983.608166.1932
Trimmed Mean ( 26 / 42 )5534.3583.185166.5305
Trimmed Mean ( 27 / 42 )5533.8182.840666.8007
Trimmed Mean ( 28 / 42 )5533.2782.414267.1398
Trimmed Mean ( 29 / 42 )5532.9481.985467.4869
Trimmed Mean ( 30 / 42 )5531.8681.636767.762
Trimmed Mean ( 31 / 42 )5530.6681.177268.1307
Trimmed Mean ( 32 / 42 )5529.680.620268.5882
Trimmed Mean ( 33 / 42 )5528.8380.030669.084
Trimmed Mean ( 34 / 42 )5527.9879.326969.6861
Trimmed Mean ( 35 / 42 )5526.7178.647170.2723
Trimmed Mean ( 36 / 42 )5525.777.8570.9788
Trimmed Mean ( 37 / 42 )5524.1277.065971.6804
Trimmed Mean ( 38 / 42 )5521.5276.215572.4462
Trimmed Mean ( 39 / 42 )5519.1275.403473.1946
Trimmed Mean ( 40 / 42 )5515.5274.526374.0078
Trimmed Mean ( 41 / 42 )5512.2373.817574.6737
Trimmed Mean ( 42 / 42 )5509.1273.225775.2348
Median5512
Midrange5107.5
Midmean - Weighted Average at Xnp5514.32
Midmean - Weighted Average at X(n+1)p5530.66
Midmean - Empirical Distribution Function5530.66
Midmean - Empirical Distribution Function - Averaging5530.66
Midmean - Empirical Distribution Function - Interpolation5529.6
Midmean - Closest Observation5530.66
Midmean - True Basic - Statistics Graphics Toolkit5530.66
Midmean - MS Excel (old versions)5530.66
Number of observations126

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 5470.02 & 109.842 & 49.799 \tabularnewline
Geometric Mean & 5318.51 &  &  \tabularnewline
Harmonic Mean & 5151.37 &  &  \tabularnewline
Quadratic Mean & 5606.19 &  &  \tabularnewline
Winsorized Mean ( 1 / 42 ) & 5472.41 & 109.191 & 50.1179 \tabularnewline
Winsorized Mean ( 2 / 42 ) & 5469.08 & 108.507 & 50.4031 \tabularnewline
Winsorized Mean ( 3 / 42 ) & 5475.22 & 106.368 & 51.4745 \tabularnewline
Winsorized Mean ( 4 / 42 ) & 5471.19 & 104.896 & 52.1582 \tabularnewline
Winsorized Mean ( 5 / 42 ) & 5474.8 & 103.944 & 52.6707 \tabularnewline
Winsorized Mean ( 6 / 42 ) & 5473.61 & 103.587 & 52.8407 \tabularnewline
Winsorized Mean ( 7 / 42 ) & 5473.94 & 101.945 & 53.6951 \tabularnewline
Winsorized Mean ( 8 / 42 ) & 5479.28 & 100.836 & 54.3386 \tabularnewline
Winsorized Mean ( 9 / 42 ) & 5478.21 & 100.622 & 54.4434 \tabularnewline
Winsorized Mean ( 10 / 42 ) & 5485.83 & 98.7292 & 55.5644 \tabularnewline
Winsorized Mean ( 11 / 42 ) & 5494.03 & 97.4467 & 56.3798 \tabularnewline
Winsorized Mean ( 12 / 42 ) & 5494.7 & 97.1499 & 56.559 \tabularnewline
Winsorized Mean ( 13 / 42 ) & 5510.17 & 94.6258 & 58.2312 \tabularnewline
Winsorized Mean ( 14 / 42 ) & 5513.29 & 92.4194 & 59.6551 \tabularnewline
Winsorized Mean ( 15 / 42 ) & 5509 & 91.6671 & 60.0979 \tabularnewline
Winsorized Mean ( 16 / 42 ) & 5515.48 & 89.308 & 61.7579 \tabularnewline
Winsorized Mean ( 17 / 42 ) & 5515.34 & 88.5507 & 62.2846 \tabularnewline
Winsorized Mean ( 18 / 42 ) & 5512.34 & 88.0352 & 62.6152 \tabularnewline
Winsorized Mean ( 19 / 42 ) & 5508.42 & 87.4821 & 62.9662 \tabularnewline
Winsorized Mean ( 20 / 42 ) & 5522.07 & 85.5906 & 64.5173 \tabularnewline
Winsorized Mean ( 21 / 42 ) & 5525.74 & 84.7422 & 65.2065 \tabularnewline
Winsorized Mean ( 22 / 42 ) & 5524.87 & 84.5235 & 65.3649 \tabularnewline
Winsorized Mean ( 23 / 42 ) & 5520.3 & 83.5544 & 66.0683 \tabularnewline
Winsorized Mean ( 24 / 42 ) & 5520.68 & 83.381 & 66.2103 \tabularnewline
Winsorized Mean ( 25 / 42 ) & 5533.38 & 80.2575 & 68.9453 \tabularnewline
Winsorized Mean ( 26 / 42 ) & 5542.46 & 78.5382 & 70.5702 \tabularnewline
Winsorized Mean ( 27 / 42 ) & 5541.82 & 78.2803 & 70.7945 \tabularnewline
Winsorized Mean ( 28 / 42 ) & 5538.26 & 77.2153 & 71.7249 \tabularnewline
Winsorized Mean ( 29 / 42 ) & 5549.31 & 75.398 & 73.6002 \tabularnewline
Winsorized Mean ( 30 / 42 ) & 5550.26 & 75.2473 & 73.7602 \tabularnewline
Winsorized Mean ( 31 / 42 ) & 5546.82 & 74.8206 & 74.1349 \tabularnewline
Winsorized Mean ( 32 / 42 ) & 5541.23 & 73.7329 & 75.1528 \tabularnewline
Winsorized Mean ( 33 / 42 ) & 5541.75 & 73.1793 & 75.7284 \tabularnewline
Winsorized Mean ( 34 / 42 ) & 5547.15 & 71.4273 & 77.6615 \tabularnewline
Winsorized Mean ( 35 / 42 ) & 5541.87 & 70.6923 & 78.3943 \tabularnewline
Winsorized Mean ( 36 / 42 ) & 5549.3 & 68.8619 & 80.5859 \tabularnewline
Winsorized Mean ( 37 / 42 ) & 5562.22 & 67.5001 & 82.4032 \tabularnewline
Winsorized Mean ( 38 / 42 ) & 5556.19 & 65.4398 & 84.9054 \tabularnewline
Winsorized Mean ( 39 / 42 ) & 5570.43 & 63.9113 & 87.1588 \tabularnewline
Winsorized Mean ( 40 / 42 ) & 5561.54 & 61.0561 & 91.089 \tabularnewline
Winsorized Mean ( 41 / 42 ) & 5554.71 & 58.6565 & 94.6989 \tabularnewline
Winsorized Mean ( 42 / 42 ) & 5550.04 & 57.7142 & 96.1642 \tabularnewline
Trimmed Mean ( 1 / 42 ) & 5475.87 & 107.01 & 51.1717 \tabularnewline
Trimmed Mean ( 2 / 42 ) & 5479.44 & 104.602 & 52.3837 \tabularnewline
Trimmed Mean ( 3 / 42 ) & 5484.88 & 102.337 & 53.5964 \tabularnewline
Trimmed Mean ( 4 / 42 ) & 5488.32 & 100.699 & 54.502 \tabularnewline
Trimmed Mean ( 5 / 42 ) & 5492.97 & 99.346 & 55.2913 \tabularnewline
Trimmed Mean ( 6 / 42 ) & 5496.99 & 98.0912 & 56.0396 \tabularnewline
Trimmed Mean ( 7 / 42 ) & 5501.38 & 96.7734 & 56.848 \tabularnewline
Trimmed Mean ( 8 / 42 ) & 5505.86 & 95.6343 & 57.572 \tabularnewline
Trimmed Mean ( 9 / 42 ) & 5509.74 & 94.5634 & 58.2651 \tabularnewline
Trimmed Mean ( 10 / 42 ) & 5513.91 & 93.3956 & 59.0382 \tabularnewline
Trimmed Mean ( 11 / 42 ) & 5517.31 & 92.3862 & 59.7201 \tabularnewline
Trimmed Mean ( 12 / 42 ) & 5519.92 & 91.4399 & 60.3667 \tabularnewline
Trimmed Mean ( 13 / 42 ) & 5522.57 & 90.4092 & 61.0842 \tabularnewline
Trimmed Mean ( 14 / 42 ) & 5523.8 & 89.5883 & 61.6576 \tabularnewline
Trimmed Mean ( 15 / 42 ) & 5524.78 & 88.9358 & 62.121 \tabularnewline
Trimmed Mean ( 16 / 42 ) & 5526.19 & 88.2732 & 62.6033 \tabularnewline
Trimmed Mean ( 17 / 42 ) & 5527.11 & 87.7904 & 62.958 \tabularnewline
Trimmed Mean ( 18 / 42 ) & 5528.08 & 87.3053 & 63.3189 \tabularnewline
Trimmed Mean ( 19 / 42 ) & 5529.33 & 86.7853 & 63.7128 \tabularnewline
Trimmed Mean ( 20 / 42 ) & 5530.94 & 86.2268 & 64.1441 \tabularnewline
Trimmed Mean ( 21 / 42 ) & 5531.61 & 85.7773 & 64.488 \tabularnewline
Trimmed Mean ( 22 / 42 ) & 5532.04 & 85.3239 & 64.8357 \tabularnewline
Trimmed Mean ( 23 / 42 ) & 5532.55 & 84.7912 & 65.2491 \tabularnewline
Trimmed Mean ( 24 / 42 ) & 5533.41 & 84.2509 & 65.6778 \tabularnewline
Trimmed Mean ( 25 / 42 ) & 5534.29 & 83.6081 & 66.1932 \tabularnewline
Trimmed Mean ( 26 / 42 ) & 5534.35 & 83.1851 & 66.5305 \tabularnewline
Trimmed Mean ( 27 / 42 ) & 5533.81 & 82.8406 & 66.8007 \tabularnewline
Trimmed Mean ( 28 / 42 ) & 5533.27 & 82.4142 & 67.1398 \tabularnewline
Trimmed Mean ( 29 / 42 ) & 5532.94 & 81.9854 & 67.4869 \tabularnewline
Trimmed Mean ( 30 / 42 ) & 5531.86 & 81.6367 & 67.762 \tabularnewline
Trimmed Mean ( 31 / 42 ) & 5530.66 & 81.1772 & 68.1307 \tabularnewline
Trimmed Mean ( 32 / 42 ) & 5529.6 & 80.6202 & 68.5882 \tabularnewline
Trimmed Mean ( 33 / 42 ) & 5528.83 & 80.0306 & 69.084 \tabularnewline
Trimmed Mean ( 34 / 42 ) & 5527.98 & 79.3269 & 69.6861 \tabularnewline
Trimmed Mean ( 35 / 42 ) & 5526.71 & 78.6471 & 70.2723 \tabularnewline
Trimmed Mean ( 36 / 42 ) & 5525.7 & 77.85 & 70.9788 \tabularnewline
Trimmed Mean ( 37 / 42 ) & 5524.12 & 77.0659 & 71.6804 \tabularnewline
Trimmed Mean ( 38 / 42 ) & 5521.52 & 76.2155 & 72.4462 \tabularnewline
Trimmed Mean ( 39 / 42 ) & 5519.12 & 75.4034 & 73.1946 \tabularnewline
Trimmed Mean ( 40 / 42 ) & 5515.52 & 74.5263 & 74.0078 \tabularnewline
Trimmed Mean ( 41 / 42 ) & 5512.23 & 73.8175 & 74.6737 \tabularnewline
Trimmed Mean ( 42 / 42 ) & 5509.12 & 73.2257 & 75.2348 \tabularnewline
Median & 5512 &  &  \tabularnewline
Midrange & 5107.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 5514.32 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 5530.66 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 5530.66 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 5530.66 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 5529.6 &  &  \tabularnewline
Midmean - Closest Observation & 5530.66 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 5530.66 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 5530.66 &  &  \tabularnewline
Number of observations & 126 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297808&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]5470.02[/C][C]109.842[/C][C]49.799[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]5318.51[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]5151.37[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]5606.19[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 42 )[/C][C]5472.41[/C][C]109.191[/C][C]50.1179[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 42 )[/C][C]5469.08[/C][C]108.507[/C][C]50.4031[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 42 )[/C][C]5475.22[/C][C]106.368[/C][C]51.4745[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 42 )[/C][C]5471.19[/C][C]104.896[/C][C]52.1582[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 42 )[/C][C]5474.8[/C][C]103.944[/C][C]52.6707[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 42 )[/C][C]5473.61[/C][C]103.587[/C][C]52.8407[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 42 )[/C][C]5473.94[/C][C]101.945[/C][C]53.6951[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 42 )[/C][C]5479.28[/C][C]100.836[/C][C]54.3386[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 42 )[/C][C]5478.21[/C][C]100.622[/C][C]54.4434[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 42 )[/C][C]5485.83[/C][C]98.7292[/C][C]55.5644[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 42 )[/C][C]5494.03[/C][C]97.4467[/C][C]56.3798[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 42 )[/C][C]5494.7[/C][C]97.1499[/C][C]56.559[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 42 )[/C][C]5510.17[/C][C]94.6258[/C][C]58.2312[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 42 )[/C][C]5513.29[/C][C]92.4194[/C][C]59.6551[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 42 )[/C][C]5509[/C][C]91.6671[/C][C]60.0979[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 42 )[/C][C]5515.48[/C][C]89.308[/C][C]61.7579[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 42 )[/C][C]5515.34[/C][C]88.5507[/C][C]62.2846[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 42 )[/C][C]5512.34[/C][C]88.0352[/C][C]62.6152[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 42 )[/C][C]5508.42[/C][C]87.4821[/C][C]62.9662[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 42 )[/C][C]5522.07[/C][C]85.5906[/C][C]64.5173[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 42 )[/C][C]5525.74[/C][C]84.7422[/C][C]65.2065[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 42 )[/C][C]5524.87[/C][C]84.5235[/C][C]65.3649[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 42 )[/C][C]5520.3[/C][C]83.5544[/C][C]66.0683[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 42 )[/C][C]5520.68[/C][C]83.381[/C][C]66.2103[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 42 )[/C][C]5533.38[/C][C]80.2575[/C][C]68.9453[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 42 )[/C][C]5542.46[/C][C]78.5382[/C][C]70.5702[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 42 )[/C][C]5541.82[/C][C]78.2803[/C][C]70.7945[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 42 )[/C][C]5538.26[/C][C]77.2153[/C][C]71.7249[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 42 )[/C][C]5549.31[/C][C]75.398[/C][C]73.6002[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 42 )[/C][C]5550.26[/C][C]75.2473[/C][C]73.7602[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 42 )[/C][C]5546.82[/C][C]74.8206[/C][C]74.1349[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 42 )[/C][C]5541.23[/C][C]73.7329[/C][C]75.1528[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 42 )[/C][C]5541.75[/C][C]73.1793[/C][C]75.7284[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 42 )[/C][C]5547.15[/C][C]71.4273[/C][C]77.6615[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 42 )[/C][C]5541.87[/C][C]70.6923[/C][C]78.3943[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 42 )[/C][C]5549.3[/C][C]68.8619[/C][C]80.5859[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 42 )[/C][C]5562.22[/C][C]67.5001[/C][C]82.4032[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 42 )[/C][C]5556.19[/C][C]65.4398[/C][C]84.9054[/C][/ROW]
[ROW][C]Winsorized Mean ( 39 / 42 )[/C][C]5570.43[/C][C]63.9113[/C][C]87.1588[/C][/ROW]
[ROW][C]Winsorized Mean ( 40 / 42 )[/C][C]5561.54[/C][C]61.0561[/C][C]91.089[/C][/ROW]
[ROW][C]Winsorized Mean ( 41 / 42 )[/C][C]5554.71[/C][C]58.6565[/C][C]94.6989[/C][/ROW]
[ROW][C]Winsorized Mean ( 42 / 42 )[/C][C]5550.04[/C][C]57.7142[/C][C]96.1642[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 42 )[/C][C]5475.87[/C][C]107.01[/C][C]51.1717[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 42 )[/C][C]5479.44[/C][C]104.602[/C][C]52.3837[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 42 )[/C][C]5484.88[/C][C]102.337[/C][C]53.5964[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 42 )[/C][C]5488.32[/C][C]100.699[/C][C]54.502[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 42 )[/C][C]5492.97[/C][C]99.346[/C][C]55.2913[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 42 )[/C][C]5496.99[/C][C]98.0912[/C][C]56.0396[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 42 )[/C][C]5501.38[/C][C]96.7734[/C][C]56.848[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 42 )[/C][C]5505.86[/C][C]95.6343[/C][C]57.572[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 42 )[/C][C]5509.74[/C][C]94.5634[/C][C]58.2651[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 42 )[/C][C]5513.91[/C][C]93.3956[/C][C]59.0382[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 42 )[/C][C]5517.31[/C][C]92.3862[/C][C]59.7201[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 42 )[/C][C]5519.92[/C][C]91.4399[/C][C]60.3667[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 42 )[/C][C]5522.57[/C][C]90.4092[/C][C]61.0842[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 42 )[/C][C]5523.8[/C][C]89.5883[/C][C]61.6576[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 42 )[/C][C]5524.78[/C][C]88.9358[/C][C]62.121[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 42 )[/C][C]5526.19[/C][C]88.2732[/C][C]62.6033[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 42 )[/C][C]5527.11[/C][C]87.7904[/C][C]62.958[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 42 )[/C][C]5528.08[/C][C]87.3053[/C][C]63.3189[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 42 )[/C][C]5529.33[/C][C]86.7853[/C][C]63.7128[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 42 )[/C][C]5530.94[/C][C]86.2268[/C][C]64.1441[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 42 )[/C][C]5531.61[/C][C]85.7773[/C][C]64.488[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 42 )[/C][C]5532.04[/C][C]85.3239[/C][C]64.8357[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 42 )[/C][C]5532.55[/C][C]84.7912[/C][C]65.2491[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 42 )[/C][C]5533.41[/C][C]84.2509[/C][C]65.6778[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 42 )[/C][C]5534.29[/C][C]83.6081[/C][C]66.1932[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 42 )[/C][C]5534.35[/C][C]83.1851[/C][C]66.5305[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 42 )[/C][C]5533.81[/C][C]82.8406[/C][C]66.8007[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 42 )[/C][C]5533.27[/C][C]82.4142[/C][C]67.1398[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 42 )[/C][C]5532.94[/C][C]81.9854[/C][C]67.4869[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 42 )[/C][C]5531.86[/C][C]81.6367[/C][C]67.762[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 42 )[/C][C]5530.66[/C][C]81.1772[/C][C]68.1307[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 42 )[/C][C]5529.6[/C][C]80.6202[/C][C]68.5882[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 42 )[/C][C]5528.83[/C][C]80.0306[/C][C]69.084[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 42 )[/C][C]5527.98[/C][C]79.3269[/C][C]69.6861[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 42 )[/C][C]5526.71[/C][C]78.6471[/C][C]70.2723[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 42 )[/C][C]5525.7[/C][C]77.85[/C][C]70.9788[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 42 )[/C][C]5524.12[/C][C]77.0659[/C][C]71.6804[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 42 )[/C][C]5521.52[/C][C]76.2155[/C][C]72.4462[/C][/ROW]
[ROW][C]Trimmed Mean ( 39 / 42 )[/C][C]5519.12[/C][C]75.4034[/C][C]73.1946[/C][/ROW]
[ROW][C]Trimmed Mean ( 40 / 42 )[/C][C]5515.52[/C][C]74.5263[/C][C]74.0078[/C][/ROW]
[ROW][C]Trimmed Mean ( 41 / 42 )[/C][C]5512.23[/C][C]73.8175[/C][C]74.6737[/C][/ROW]
[ROW][C]Trimmed Mean ( 42 / 42 )[/C][C]5509.12[/C][C]73.2257[/C][C]75.2348[/C][/ROW]
[ROW][C]Median[/C][C]5512[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]5107.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]5514.32[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]5530.66[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]5530.66[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]5530.66[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]5529.6[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]5530.66[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]5530.66[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]5530.66[/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=297808&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297808&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 Mean5470.02109.84249.799
Geometric Mean5318.51
Harmonic Mean5151.37
Quadratic Mean5606.19
Winsorized Mean ( 1 / 42 )5472.41109.19150.1179
Winsorized Mean ( 2 / 42 )5469.08108.50750.4031
Winsorized Mean ( 3 / 42 )5475.22106.36851.4745
Winsorized Mean ( 4 / 42 )5471.19104.89652.1582
Winsorized Mean ( 5 / 42 )5474.8103.94452.6707
Winsorized Mean ( 6 / 42 )5473.61103.58752.8407
Winsorized Mean ( 7 / 42 )5473.94101.94553.6951
Winsorized Mean ( 8 / 42 )5479.28100.83654.3386
Winsorized Mean ( 9 / 42 )5478.21100.62254.4434
Winsorized Mean ( 10 / 42 )5485.8398.729255.5644
Winsorized Mean ( 11 / 42 )5494.0397.446756.3798
Winsorized Mean ( 12 / 42 )5494.797.149956.559
Winsorized Mean ( 13 / 42 )5510.1794.625858.2312
Winsorized Mean ( 14 / 42 )5513.2992.419459.6551
Winsorized Mean ( 15 / 42 )550991.667160.0979
Winsorized Mean ( 16 / 42 )5515.4889.30861.7579
Winsorized Mean ( 17 / 42 )5515.3488.550762.2846
Winsorized Mean ( 18 / 42 )5512.3488.035262.6152
Winsorized Mean ( 19 / 42 )5508.4287.482162.9662
Winsorized Mean ( 20 / 42 )5522.0785.590664.5173
Winsorized Mean ( 21 / 42 )5525.7484.742265.2065
Winsorized Mean ( 22 / 42 )5524.8784.523565.3649
Winsorized Mean ( 23 / 42 )5520.383.554466.0683
Winsorized Mean ( 24 / 42 )5520.6883.38166.2103
Winsorized Mean ( 25 / 42 )5533.3880.257568.9453
Winsorized Mean ( 26 / 42 )5542.4678.538270.5702
Winsorized Mean ( 27 / 42 )5541.8278.280370.7945
Winsorized Mean ( 28 / 42 )5538.2677.215371.7249
Winsorized Mean ( 29 / 42 )5549.3175.39873.6002
Winsorized Mean ( 30 / 42 )5550.2675.247373.7602
Winsorized Mean ( 31 / 42 )5546.8274.820674.1349
Winsorized Mean ( 32 / 42 )5541.2373.732975.1528
Winsorized Mean ( 33 / 42 )5541.7573.179375.7284
Winsorized Mean ( 34 / 42 )5547.1571.427377.6615
Winsorized Mean ( 35 / 42 )5541.8770.692378.3943
Winsorized Mean ( 36 / 42 )5549.368.861980.5859
Winsorized Mean ( 37 / 42 )5562.2267.500182.4032
Winsorized Mean ( 38 / 42 )5556.1965.439884.9054
Winsorized Mean ( 39 / 42 )5570.4363.911387.1588
Winsorized Mean ( 40 / 42 )5561.5461.056191.089
Winsorized Mean ( 41 / 42 )5554.7158.656594.6989
Winsorized Mean ( 42 / 42 )5550.0457.714296.1642
Trimmed Mean ( 1 / 42 )5475.87107.0151.1717
Trimmed Mean ( 2 / 42 )5479.44104.60252.3837
Trimmed Mean ( 3 / 42 )5484.88102.33753.5964
Trimmed Mean ( 4 / 42 )5488.32100.69954.502
Trimmed Mean ( 5 / 42 )5492.9799.34655.2913
Trimmed Mean ( 6 / 42 )5496.9998.091256.0396
Trimmed Mean ( 7 / 42 )5501.3896.773456.848
Trimmed Mean ( 8 / 42 )5505.8695.634357.572
Trimmed Mean ( 9 / 42 )5509.7494.563458.2651
Trimmed Mean ( 10 / 42 )5513.9193.395659.0382
Trimmed Mean ( 11 / 42 )5517.3192.386259.7201
Trimmed Mean ( 12 / 42 )5519.9291.439960.3667
Trimmed Mean ( 13 / 42 )5522.5790.409261.0842
Trimmed Mean ( 14 / 42 )5523.889.588361.6576
Trimmed Mean ( 15 / 42 )5524.7888.935862.121
Trimmed Mean ( 16 / 42 )5526.1988.273262.6033
Trimmed Mean ( 17 / 42 )5527.1187.790462.958
Trimmed Mean ( 18 / 42 )5528.0887.305363.3189
Trimmed Mean ( 19 / 42 )5529.3386.785363.7128
Trimmed Mean ( 20 / 42 )5530.9486.226864.1441
Trimmed Mean ( 21 / 42 )5531.6185.777364.488
Trimmed Mean ( 22 / 42 )5532.0485.323964.8357
Trimmed Mean ( 23 / 42 )5532.5584.791265.2491
Trimmed Mean ( 24 / 42 )5533.4184.250965.6778
Trimmed Mean ( 25 / 42 )5534.2983.608166.1932
Trimmed Mean ( 26 / 42 )5534.3583.185166.5305
Trimmed Mean ( 27 / 42 )5533.8182.840666.8007
Trimmed Mean ( 28 / 42 )5533.2782.414267.1398
Trimmed Mean ( 29 / 42 )5532.9481.985467.4869
Trimmed Mean ( 30 / 42 )5531.8681.636767.762
Trimmed Mean ( 31 / 42 )5530.6681.177268.1307
Trimmed Mean ( 32 / 42 )5529.680.620268.5882
Trimmed Mean ( 33 / 42 )5528.8380.030669.084
Trimmed Mean ( 34 / 42 )5527.9879.326969.6861
Trimmed Mean ( 35 / 42 )5526.7178.647170.2723
Trimmed Mean ( 36 / 42 )5525.777.8570.9788
Trimmed Mean ( 37 / 42 )5524.1277.065971.6804
Trimmed Mean ( 38 / 42 )5521.5276.215572.4462
Trimmed Mean ( 39 / 42 )5519.1275.403473.1946
Trimmed Mean ( 40 / 42 )5515.5274.526374.0078
Trimmed Mean ( 41 / 42 )5512.2373.817574.6737
Trimmed Mean ( 42 / 42 )5509.1273.225775.2348
Median5512
Midrange5107.5
Midmean - Weighted Average at Xnp5514.32
Midmean - Weighted Average at X(n+1)p5530.66
Midmean - Empirical Distribution Function5530.66
Midmean - Empirical Distribution Function - Averaging5530.66
Midmean - Empirical Distribution Function - Interpolation5529.6
Midmean - Closest Observation5530.66
Midmean - True Basic - Statistics Graphics Toolkit5530.66
Midmean - MS Excel (old versions)5530.66
Number of observations126



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')