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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, 22 Nov 2016 12:05:34 +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/22/t1479812767bxmd4811v74l8mk.htm/, Retrieved Sun, 05 May 2024 13:34:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296898, Retrieved Sun, 05 May 2024 13:34:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact86
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Central Tendency ...] [2016-11-22 11:05:34] [563c2945bc7c763925d38f2fb19cdb55] [Current]
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Dataseries X:
6830,20
4108,80
3131,60
7008,00
1276,80
6554,60
4387,60
4651,80
6192,20
4645,40
4540,00
5115,20
6776,20
4455,00
2579,00
7855,20
866,60
6406,40
4479,60
5164,00
6308,20
5124,80
4958,40
5410,80
7570,40
4753,80
3406,20
10495,20
723,60
6954,00
5429,60
5155,20
6930,00
6119,00
4681,20
6040,00
8226,00
5075,40
2514,40
9024,00
1964,00
7282,40
6287,60
5152,80
7425,00
6224,60
4824,40
6716,80
9293,20
4561,00
2848,00
14370,00
1855,00
8104,20
6377,80
5376,80
7959,40
6485,80
5007,80
7307,40
8797,40
5130,20
4127,40
10666,80
3591,60
9218,40
5158,20
6388,40
8356,80
6257,40
5964,40
7934,60
9725,40
4685,40
3553,80
13706,60
5067,20
9975,20
5875,40
7386,40
9005,20
7098,60
6889,60
7477,00
11208,80
5766,00
2634,80
14875,00
4293,40
9927,80
6658,00
7286,80
9332,80
8138,20
5431,20
9294,20
10176,40
5585,80
2257,60
15553,60
2402,40
8903,40
7680,60
6912,00
9595,80
7866,40
6397,40
8344,40
12090,20
4442,60
3900,60
13598,60
2402,40
10614,40
7019,60
6943,00
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
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=296898&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=296898&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296898&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 / 38 )6520.56264.07624.692
Winsorized Mean ( 2 / 38 )6518.92260.45925.0286
Winsorized Mean ( 3 / 38 )6516.72253.58925.698
Winsorized Mean ( 4 / 38 )6516.75252.07925.852
Winsorized Mean ( 5 / 38 )6464.39235.36227.4657
Winsorized Mean ( 6 / 38 )6426.29225.2428.5308
Winsorized Mean ( 7 / 38 )6393.58219.44929.1347
Winsorized Mean ( 8 / 38 )6397.69217.62829.3974
Winsorized Mean ( 9 / 38 )6393.46215.30829.6945
Winsorized Mean ( 10 / 38 )6370.78210.12430.3192
Winsorized Mean ( 11 / 38 )6371.92204.07531.2235
Winsorized Mean ( 12 / 38 )6396.36199.02432.1387
Winsorized Mean ( 13 / 38 )6404.45191.26733.4844
Winsorized Mean ( 14 / 38 )6406.62186.52434.3475
Winsorized Mean ( 15 / 38 )6377.5180.92635.2492
Winsorized Mean ( 16 / 38 )6414.8174.64236.7311
Winsorized Mean ( 17 / 38 )6445.16170.89737.7138
Winsorized Mean ( 18 / 38 )6436.44168.88138.1123
Winsorized Mean ( 19 / 38 )6431.79161.18739.9026
Winsorized Mean ( 20 / 38 )6444.79158.88240.5633
Winsorized Mean ( 21 / 38 )6436.32155.241.471
Winsorized Mean ( 22 / 38 )6418.57152.18142.1772
Winsorized Mean ( 23 / 38 )6336.08140.19645.1945
Winsorized Mean ( 24 / 38 )6346.01138.44645.8375
Winsorized Mean ( 25 / 38 )6325.02134.76546.9338
Winsorized Mean ( 26 / 38 )6324.26130.22948.5628
Winsorized Mean ( 27 / 38 )6317.84129.10648.9352
Winsorized Mean ( 28 / 38 )6289.98124.16150.6598
Winsorized Mean ( 29 / 38 )6284.83123.3250.9637
Winsorized Mean ( 30 / 38 )6284.88119.29252.6848
Winsorized Mean ( 31 / 38 )6300.76116.85753.9185
Winsorized Mean ( 32 / 38 )6289.56107.32958.6008
Winsorized Mean ( 33 / 38 )6272.26102.31961.301
Winsorized Mean ( 34 / 38 )6262.2997.46164.2544
Winsorized Mean ( 35 / 38 )6249.0895.506765.4308
Winsorized Mean ( 36 / 38 )6249.4592.912467.2618
Winsorized Mean ( 37 / 38 )6227.3289.929869.2464
Winsorized Mean ( 38 / 38 )6222.3489.03869.884
Trimmed Mean ( 1 / 38 )6496.87253.59625.619
Trimmed Mean ( 2 / 38 )6472.33241.73826.7742
Trimmed Mean ( 3 / 38 )6447.77230.50527.9724
Trimmed Mean ( 4 / 38 )6423.08220.76529.0946
Trimmed Mean ( 5 / 38 )6397.45210.230.4351
Trimmed Mean ( 6 / 38 )6382.52203.17631.4137
Trimmed Mean ( 7 / 38 )6374.23197.79832.2259
Trimmed Mean ( 8 / 38 )6371.02193.02333.0065
Trimmed Mean ( 9 / 38 )6367.07187.99833.8678
Trimmed Mean ( 10 / 38 )6363.53182.74834.8213
Trimmed Mean ( 11 / 38 )6362.64177.72935.7996
Trimmed Mean ( 12 / 38 )6361.57173.05936.7596
Trimmed Mean ( 13 / 38 )6357.84168.5637.7186
Trimmed Mean ( 14 / 38 )6353.11164.64138.5876
Trimmed Mean ( 15 / 38 )6347.95160.8739.4603
Trimmed Mean ( 16 / 38 )6345.23157.37240.32
Trimmed Mean ( 17 / 38 )6339.08154.2341.1015
Trimmed Mean ( 18 / 38 )6330.04151.09641.8942
Trimmed Mean ( 19 / 38 )6321.24147.73542.7878
Trimmed Mean ( 20 / 38 )6312.36144.8943.5665
Trimmed Mean ( 21 / 38 )6301.98141.85144.4268
Trimmed Mean ( 22 / 38 )6291.68138.78645.3337
Trimmed Mean ( 23 / 38 )6282.12135.59746.3294
Trimmed Mean ( 24 / 38 )6278.12133.54447.0115
Trimmed Mean ( 25 / 38 )6273.15131.30247.7766
Trimmed Mean ( 26 / 38 )6269.38129.11348.5574
Trimmed Mean ( 27 / 38 )6265.44127.08749.3005
Trimmed Mean ( 28 / 38 )6261.68124.75750.1911
Trimmed Mean ( 29 / 38 )6259.66122.63151.0445
Trimmed Mean ( 30 / 38 )6257.86120.1152.1012
Trimmed Mean ( 31 / 38 )6257.86117.60453.2113
Trimmed Mean ( 32 / 38 )6252.7114.84154.4465
Trimmed Mean ( 33 / 38 )6250.03112.95955.33
Trimmed Mean ( 34 / 38 )6248.4111.35656.1119
Trimmed Mean ( 35 / 38 )6247.37110.05156.7681
Trimmed Mean ( 36 / 38 )6247.25108.58957.531
Trimmed Mean ( 37 / 38 )6247.08107.04258.3611
Trimmed Mean ( 38 / 38 )6248.62105.4559.2568
MedianNA
MidrangeNA
Midmean - Weighted Average at Xnp6232.91
Midmean - Weighted Average at X(n+1)p6259.66
Midmean - Empirical Distribution Function6232.91
Midmean - Empirical Distribution Function - Averaging6259.66
Midmean - Empirical Distribution Function - Interpolation6259.66
Midmean - Closest Observation6232.91
Midmean - True Basic - Statistics Graphics Toolkit6259.66
Midmean - MS Excel (old versions)6261.68
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 / 38 ) & 6520.56 & 264.076 & 24.692 \tabularnewline
Winsorized Mean ( 2 / 38 ) & 6518.92 & 260.459 & 25.0286 \tabularnewline
Winsorized Mean ( 3 / 38 ) & 6516.72 & 253.589 & 25.698 \tabularnewline
Winsorized Mean ( 4 / 38 ) & 6516.75 & 252.079 & 25.852 \tabularnewline
Winsorized Mean ( 5 / 38 ) & 6464.39 & 235.362 & 27.4657 \tabularnewline
Winsorized Mean ( 6 / 38 ) & 6426.29 & 225.24 & 28.5308 \tabularnewline
Winsorized Mean ( 7 / 38 ) & 6393.58 & 219.449 & 29.1347 \tabularnewline
Winsorized Mean ( 8 / 38 ) & 6397.69 & 217.628 & 29.3974 \tabularnewline
Winsorized Mean ( 9 / 38 ) & 6393.46 & 215.308 & 29.6945 \tabularnewline
Winsorized Mean ( 10 / 38 ) & 6370.78 & 210.124 & 30.3192 \tabularnewline
Winsorized Mean ( 11 / 38 ) & 6371.92 & 204.075 & 31.2235 \tabularnewline
Winsorized Mean ( 12 / 38 ) & 6396.36 & 199.024 & 32.1387 \tabularnewline
Winsorized Mean ( 13 / 38 ) & 6404.45 & 191.267 & 33.4844 \tabularnewline
Winsorized Mean ( 14 / 38 ) & 6406.62 & 186.524 & 34.3475 \tabularnewline
Winsorized Mean ( 15 / 38 ) & 6377.5 & 180.926 & 35.2492 \tabularnewline
Winsorized Mean ( 16 / 38 ) & 6414.8 & 174.642 & 36.7311 \tabularnewline
Winsorized Mean ( 17 / 38 ) & 6445.16 & 170.897 & 37.7138 \tabularnewline
Winsorized Mean ( 18 / 38 ) & 6436.44 & 168.881 & 38.1123 \tabularnewline
Winsorized Mean ( 19 / 38 ) & 6431.79 & 161.187 & 39.9026 \tabularnewline
Winsorized Mean ( 20 / 38 ) & 6444.79 & 158.882 & 40.5633 \tabularnewline
Winsorized Mean ( 21 / 38 ) & 6436.32 & 155.2 & 41.471 \tabularnewline
Winsorized Mean ( 22 / 38 ) & 6418.57 & 152.181 & 42.1772 \tabularnewline
Winsorized Mean ( 23 / 38 ) & 6336.08 & 140.196 & 45.1945 \tabularnewline
Winsorized Mean ( 24 / 38 ) & 6346.01 & 138.446 & 45.8375 \tabularnewline
Winsorized Mean ( 25 / 38 ) & 6325.02 & 134.765 & 46.9338 \tabularnewline
Winsorized Mean ( 26 / 38 ) & 6324.26 & 130.229 & 48.5628 \tabularnewline
Winsorized Mean ( 27 / 38 ) & 6317.84 & 129.106 & 48.9352 \tabularnewline
Winsorized Mean ( 28 / 38 ) & 6289.98 & 124.161 & 50.6598 \tabularnewline
Winsorized Mean ( 29 / 38 ) & 6284.83 & 123.32 & 50.9637 \tabularnewline
Winsorized Mean ( 30 / 38 ) & 6284.88 & 119.292 & 52.6848 \tabularnewline
Winsorized Mean ( 31 / 38 ) & 6300.76 & 116.857 & 53.9185 \tabularnewline
Winsorized Mean ( 32 / 38 ) & 6289.56 & 107.329 & 58.6008 \tabularnewline
Winsorized Mean ( 33 / 38 ) & 6272.26 & 102.319 & 61.301 \tabularnewline
Winsorized Mean ( 34 / 38 ) & 6262.29 & 97.461 & 64.2544 \tabularnewline
Winsorized Mean ( 35 / 38 ) & 6249.08 & 95.5067 & 65.4308 \tabularnewline
Winsorized Mean ( 36 / 38 ) & 6249.45 & 92.9124 & 67.2618 \tabularnewline
Winsorized Mean ( 37 / 38 ) & 6227.32 & 89.9298 & 69.2464 \tabularnewline
Winsorized Mean ( 38 / 38 ) & 6222.34 & 89.038 & 69.884 \tabularnewline
Trimmed Mean ( 1 / 38 ) & 6496.87 & 253.596 & 25.619 \tabularnewline
Trimmed Mean ( 2 / 38 ) & 6472.33 & 241.738 & 26.7742 \tabularnewline
Trimmed Mean ( 3 / 38 ) & 6447.77 & 230.505 & 27.9724 \tabularnewline
Trimmed Mean ( 4 / 38 ) & 6423.08 & 220.765 & 29.0946 \tabularnewline
Trimmed Mean ( 5 / 38 ) & 6397.45 & 210.2 & 30.4351 \tabularnewline
Trimmed Mean ( 6 / 38 ) & 6382.52 & 203.176 & 31.4137 \tabularnewline
Trimmed Mean ( 7 / 38 ) & 6374.23 & 197.798 & 32.2259 \tabularnewline
Trimmed Mean ( 8 / 38 ) & 6371.02 & 193.023 & 33.0065 \tabularnewline
Trimmed Mean ( 9 / 38 ) & 6367.07 & 187.998 & 33.8678 \tabularnewline
Trimmed Mean ( 10 / 38 ) & 6363.53 & 182.748 & 34.8213 \tabularnewline
Trimmed Mean ( 11 / 38 ) & 6362.64 & 177.729 & 35.7996 \tabularnewline
Trimmed Mean ( 12 / 38 ) & 6361.57 & 173.059 & 36.7596 \tabularnewline
Trimmed Mean ( 13 / 38 ) & 6357.84 & 168.56 & 37.7186 \tabularnewline
Trimmed Mean ( 14 / 38 ) & 6353.11 & 164.641 & 38.5876 \tabularnewline
Trimmed Mean ( 15 / 38 ) & 6347.95 & 160.87 & 39.4603 \tabularnewline
Trimmed Mean ( 16 / 38 ) & 6345.23 & 157.372 & 40.32 \tabularnewline
Trimmed Mean ( 17 / 38 ) & 6339.08 & 154.23 & 41.1015 \tabularnewline
Trimmed Mean ( 18 / 38 ) & 6330.04 & 151.096 & 41.8942 \tabularnewline
Trimmed Mean ( 19 / 38 ) & 6321.24 & 147.735 & 42.7878 \tabularnewline
Trimmed Mean ( 20 / 38 ) & 6312.36 & 144.89 & 43.5665 \tabularnewline
Trimmed Mean ( 21 / 38 ) & 6301.98 & 141.851 & 44.4268 \tabularnewline
Trimmed Mean ( 22 / 38 ) & 6291.68 & 138.786 & 45.3337 \tabularnewline
Trimmed Mean ( 23 / 38 ) & 6282.12 & 135.597 & 46.3294 \tabularnewline
Trimmed Mean ( 24 / 38 ) & 6278.12 & 133.544 & 47.0115 \tabularnewline
Trimmed Mean ( 25 / 38 ) & 6273.15 & 131.302 & 47.7766 \tabularnewline
Trimmed Mean ( 26 / 38 ) & 6269.38 & 129.113 & 48.5574 \tabularnewline
Trimmed Mean ( 27 / 38 ) & 6265.44 & 127.087 & 49.3005 \tabularnewline
Trimmed Mean ( 28 / 38 ) & 6261.68 & 124.757 & 50.1911 \tabularnewline
Trimmed Mean ( 29 / 38 ) & 6259.66 & 122.631 & 51.0445 \tabularnewline
Trimmed Mean ( 30 / 38 ) & 6257.86 & 120.11 & 52.1012 \tabularnewline
Trimmed Mean ( 31 / 38 ) & 6257.86 & 117.604 & 53.2113 \tabularnewline
Trimmed Mean ( 32 / 38 ) & 6252.7 & 114.841 & 54.4465 \tabularnewline
Trimmed Mean ( 33 / 38 ) & 6250.03 & 112.959 & 55.33 \tabularnewline
Trimmed Mean ( 34 / 38 ) & 6248.4 & 111.356 & 56.1119 \tabularnewline
Trimmed Mean ( 35 / 38 ) & 6247.37 & 110.051 & 56.7681 \tabularnewline
Trimmed Mean ( 36 / 38 ) & 6247.25 & 108.589 & 57.531 \tabularnewline
Trimmed Mean ( 37 / 38 ) & 6247.08 & 107.042 & 58.3611 \tabularnewline
Trimmed Mean ( 38 / 38 ) & 6248.62 & 105.45 & 59.2568 \tabularnewline
Median & NA &  &  \tabularnewline
Midrange & NA &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 6232.91 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 6259.66 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 6232.91 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 6259.66 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 6259.66 &  &  \tabularnewline
Midmean - Closest Observation & 6232.91 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 6259.66 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 6261.68 &  &  \tabularnewline
Number of observations & 144 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296898&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 / 38 )[/C][C]6520.56[/C][C]264.076[/C][C]24.692[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 38 )[/C][C]6518.92[/C][C]260.459[/C][C]25.0286[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 38 )[/C][C]6516.72[/C][C]253.589[/C][C]25.698[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 38 )[/C][C]6516.75[/C][C]252.079[/C][C]25.852[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 38 )[/C][C]6464.39[/C][C]235.362[/C][C]27.4657[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 38 )[/C][C]6426.29[/C][C]225.24[/C][C]28.5308[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 38 )[/C][C]6393.58[/C][C]219.449[/C][C]29.1347[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 38 )[/C][C]6397.69[/C][C]217.628[/C][C]29.3974[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 38 )[/C][C]6393.46[/C][C]215.308[/C][C]29.6945[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 38 )[/C][C]6370.78[/C][C]210.124[/C][C]30.3192[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 38 )[/C][C]6371.92[/C][C]204.075[/C][C]31.2235[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 38 )[/C][C]6396.36[/C][C]199.024[/C][C]32.1387[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 38 )[/C][C]6404.45[/C][C]191.267[/C][C]33.4844[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 38 )[/C][C]6406.62[/C][C]186.524[/C][C]34.3475[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 38 )[/C][C]6377.5[/C][C]180.926[/C][C]35.2492[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 38 )[/C][C]6414.8[/C][C]174.642[/C][C]36.7311[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 38 )[/C][C]6445.16[/C][C]170.897[/C][C]37.7138[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 38 )[/C][C]6436.44[/C][C]168.881[/C][C]38.1123[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 38 )[/C][C]6431.79[/C][C]161.187[/C][C]39.9026[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 38 )[/C][C]6444.79[/C][C]158.882[/C][C]40.5633[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 38 )[/C][C]6436.32[/C][C]155.2[/C][C]41.471[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 38 )[/C][C]6418.57[/C][C]152.181[/C][C]42.1772[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 38 )[/C][C]6336.08[/C][C]140.196[/C][C]45.1945[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 38 )[/C][C]6346.01[/C][C]138.446[/C][C]45.8375[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 38 )[/C][C]6325.02[/C][C]134.765[/C][C]46.9338[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 38 )[/C][C]6324.26[/C][C]130.229[/C][C]48.5628[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 38 )[/C][C]6317.84[/C][C]129.106[/C][C]48.9352[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 38 )[/C][C]6289.98[/C][C]124.161[/C][C]50.6598[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 38 )[/C][C]6284.83[/C][C]123.32[/C][C]50.9637[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 38 )[/C][C]6284.88[/C][C]119.292[/C][C]52.6848[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 38 )[/C][C]6300.76[/C][C]116.857[/C][C]53.9185[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 38 )[/C][C]6289.56[/C][C]107.329[/C][C]58.6008[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 38 )[/C][C]6272.26[/C][C]102.319[/C][C]61.301[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 38 )[/C][C]6262.29[/C][C]97.461[/C][C]64.2544[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 38 )[/C][C]6249.08[/C][C]95.5067[/C][C]65.4308[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 38 )[/C][C]6249.45[/C][C]92.9124[/C][C]67.2618[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 38 )[/C][C]6227.32[/C][C]89.9298[/C][C]69.2464[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 38 )[/C][C]6222.34[/C][C]89.038[/C][C]69.884[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 38 )[/C][C]6496.87[/C][C]253.596[/C][C]25.619[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 38 )[/C][C]6472.33[/C][C]241.738[/C][C]26.7742[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 38 )[/C][C]6447.77[/C][C]230.505[/C][C]27.9724[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 38 )[/C][C]6423.08[/C][C]220.765[/C][C]29.0946[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 38 )[/C][C]6397.45[/C][C]210.2[/C][C]30.4351[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 38 )[/C][C]6382.52[/C][C]203.176[/C][C]31.4137[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 38 )[/C][C]6374.23[/C][C]197.798[/C][C]32.2259[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 38 )[/C][C]6371.02[/C][C]193.023[/C][C]33.0065[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 38 )[/C][C]6367.07[/C][C]187.998[/C][C]33.8678[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 38 )[/C][C]6363.53[/C][C]182.748[/C][C]34.8213[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 38 )[/C][C]6362.64[/C][C]177.729[/C][C]35.7996[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 38 )[/C][C]6361.57[/C][C]173.059[/C][C]36.7596[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 38 )[/C][C]6357.84[/C][C]168.56[/C][C]37.7186[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 38 )[/C][C]6353.11[/C][C]164.641[/C][C]38.5876[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 38 )[/C][C]6347.95[/C][C]160.87[/C][C]39.4603[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 38 )[/C][C]6345.23[/C][C]157.372[/C][C]40.32[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 38 )[/C][C]6339.08[/C][C]154.23[/C][C]41.1015[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 38 )[/C][C]6330.04[/C][C]151.096[/C][C]41.8942[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 38 )[/C][C]6321.24[/C][C]147.735[/C][C]42.7878[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 38 )[/C][C]6312.36[/C][C]144.89[/C][C]43.5665[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 38 )[/C][C]6301.98[/C][C]141.851[/C][C]44.4268[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 38 )[/C][C]6291.68[/C][C]138.786[/C][C]45.3337[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 38 )[/C][C]6282.12[/C][C]135.597[/C][C]46.3294[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 38 )[/C][C]6278.12[/C][C]133.544[/C][C]47.0115[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 38 )[/C][C]6273.15[/C][C]131.302[/C][C]47.7766[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 38 )[/C][C]6269.38[/C][C]129.113[/C][C]48.5574[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 38 )[/C][C]6265.44[/C][C]127.087[/C][C]49.3005[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 38 )[/C][C]6261.68[/C][C]124.757[/C][C]50.1911[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 38 )[/C][C]6259.66[/C][C]122.631[/C][C]51.0445[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 38 )[/C][C]6257.86[/C][C]120.11[/C][C]52.1012[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 38 )[/C][C]6257.86[/C][C]117.604[/C][C]53.2113[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 38 )[/C][C]6252.7[/C][C]114.841[/C][C]54.4465[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 38 )[/C][C]6250.03[/C][C]112.959[/C][C]55.33[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 38 )[/C][C]6248.4[/C][C]111.356[/C][C]56.1119[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 38 )[/C][C]6247.37[/C][C]110.051[/C][C]56.7681[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 38 )[/C][C]6247.25[/C][C]108.589[/C][C]57.531[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 38 )[/C][C]6247.08[/C][C]107.042[/C][C]58.3611[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 38 )[/C][C]6248.62[/C][C]105.45[/C][C]59.2568[/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]6232.91[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]6259.66[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]6232.91[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]6259.66[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]6259.66[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]6232.91[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]6259.66[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]6261.68[/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=296898&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296898&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 / 38 )6520.56264.07624.692
Winsorized Mean ( 2 / 38 )6518.92260.45925.0286
Winsorized Mean ( 3 / 38 )6516.72253.58925.698
Winsorized Mean ( 4 / 38 )6516.75252.07925.852
Winsorized Mean ( 5 / 38 )6464.39235.36227.4657
Winsorized Mean ( 6 / 38 )6426.29225.2428.5308
Winsorized Mean ( 7 / 38 )6393.58219.44929.1347
Winsorized Mean ( 8 / 38 )6397.69217.62829.3974
Winsorized Mean ( 9 / 38 )6393.46215.30829.6945
Winsorized Mean ( 10 / 38 )6370.78210.12430.3192
Winsorized Mean ( 11 / 38 )6371.92204.07531.2235
Winsorized Mean ( 12 / 38 )6396.36199.02432.1387
Winsorized Mean ( 13 / 38 )6404.45191.26733.4844
Winsorized Mean ( 14 / 38 )6406.62186.52434.3475
Winsorized Mean ( 15 / 38 )6377.5180.92635.2492
Winsorized Mean ( 16 / 38 )6414.8174.64236.7311
Winsorized Mean ( 17 / 38 )6445.16170.89737.7138
Winsorized Mean ( 18 / 38 )6436.44168.88138.1123
Winsorized Mean ( 19 / 38 )6431.79161.18739.9026
Winsorized Mean ( 20 / 38 )6444.79158.88240.5633
Winsorized Mean ( 21 / 38 )6436.32155.241.471
Winsorized Mean ( 22 / 38 )6418.57152.18142.1772
Winsorized Mean ( 23 / 38 )6336.08140.19645.1945
Winsorized Mean ( 24 / 38 )6346.01138.44645.8375
Winsorized Mean ( 25 / 38 )6325.02134.76546.9338
Winsorized Mean ( 26 / 38 )6324.26130.22948.5628
Winsorized Mean ( 27 / 38 )6317.84129.10648.9352
Winsorized Mean ( 28 / 38 )6289.98124.16150.6598
Winsorized Mean ( 29 / 38 )6284.83123.3250.9637
Winsorized Mean ( 30 / 38 )6284.88119.29252.6848
Winsorized Mean ( 31 / 38 )6300.76116.85753.9185
Winsorized Mean ( 32 / 38 )6289.56107.32958.6008
Winsorized Mean ( 33 / 38 )6272.26102.31961.301
Winsorized Mean ( 34 / 38 )6262.2997.46164.2544
Winsorized Mean ( 35 / 38 )6249.0895.506765.4308
Winsorized Mean ( 36 / 38 )6249.4592.912467.2618
Winsorized Mean ( 37 / 38 )6227.3289.929869.2464
Winsorized Mean ( 38 / 38 )6222.3489.03869.884
Trimmed Mean ( 1 / 38 )6496.87253.59625.619
Trimmed Mean ( 2 / 38 )6472.33241.73826.7742
Trimmed Mean ( 3 / 38 )6447.77230.50527.9724
Trimmed Mean ( 4 / 38 )6423.08220.76529.0946
Trimmed Mean ( 5 / 38 )6397.45210.230.4351
Trimmed Mean ( 6 / 38 )6382.52203.17631.4137
Trimmed Mean ( 7 / 38 )6374.23197.79832.2259
Trimmed Mean ( 8 / 38 )6371.02193.02333.0065
Trimmed Mean ( 9 / 38 )6367.07187.99833.8678
Trimmed Mean ( 10 / 38 )6363.53182.74834.8213
Trimmed Mean ( 11 / 38 )6362.64177.72935.7996
Trimmed Mean ( 12 / 38 )6361.57173.05936.7596
Trimmed Mean ( 13 / 38 )6357.84168.5637.7186
Trimmed Mean ( 14 / 38 )6353.11164.64138.5876
Trimmed Mean ( 15 / 38 )6347.95160.8739.4603
Trimmed Mean ( 16 / 38 )6345.23157.37240.32
Trimmed Mean ( 17 / 38 )6339.08154.2341.1015
Trimmed Mean ( 18 / 38 )6330.04151.09641.8942
Trimmed Mean ( 19 / 38 )6321.24147.73542.7878
Trimmed Mean ( 20 / 38 )6312.36144.8943.5665
Trimmed Mean ( 21 / 38 )6301.98141.85144.4268
Trimmed Mean ( 22 / 38 )6291.68138.78645.3337
Trimmed Mean ( 23 / 38 )6282.12135.59746.3294
Trimmed Mean ( 24 / 38 )6278.12133.54447.0115
Trimmed Mean ( 25 / 38 )6273.15131.30247.7766
Trimmed Mean ( 26 / 38 )6269.38129.11348.5574
Trimmed Mean ( 27 / 38 )6265.44127.08749.3005
Trimmed Mean ( 28 / 38 )6261.68124.75750.1911
Trimmed Mean ( 29 / 38 )6259.66122.63151.0445
Trimmed Mean ( 30 / 38 )6257.86120.1152.1012
Trimmed Mean ( 31 / 38 )6257.86117.60453.2113
Trimmed Mean ( 32 / 38 )6252.7114.84154.4465
Trimmed Mean ( 33 / 38 )6250.03112.95955.33
Trimmed Mean ( 34 / 38 )6248.4111.35656.1119
Trimmed Mean ( 35 / 38 )6247.37110.05156.7681
Trimmed Mean ( 36 / 38 )6247.25108.58957.531
Trimmed Mean ( 37 / 38 )6247.08107.04258.3611
Trimmed Mean ( 38 / 38 )6248.62105.4559.2568
MedianNA
MidrangeNA
Midmean - Weighted Average at Xnp6232.91
Midmean - Weighted Average at X(n+1)p6259.66
Midmean - Empirical Distribution Function6232.91
Midmean - Empirical Distribution Function - Averaging6259.66
Midmean - Empirical Distribution Function - Interpolation6259.66
Midmean - Closest Observation6232.91
Midmean - True Basic - Statistics Graphics Toolkit6259.66
Midmean - MS Excel (old versions)6261.68
Number of observations144



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')