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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, 14 Dec 2016 15:38:09 +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/14/t14817272108gcsr15em37b0p7.htm/, Retrieved Fri, 01 Nov 2024 03:41:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299526, Retrieved Fri, 01 Nov 2024 03:41:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact88
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2016-12-14 14:38:09] [4d72a1efe36cb2a85639504d1000816e] [Current]
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Dataseries X:
4480
4580
5360
4960
5140
5000
5080
5160
5080
5500
5260
5160
4500
4740
5840
5340
5500
5820
5620
5920
5980
6340
6220
5900
5280
5500
6460
5920
6240
6120
5980
6380
5920
6360
5860
5320
4780
4800
5480
5220
5380
5220
5200
5260
5060
5880
5580
5020
6060
5980
6680
6560
6680
6420
6660
7000
6780
7460
6960
6560
6060
6140
7160
6920
7140
7180
7340
7480
7620
8280
7740
7700
7080
7100
8380
7840
7880
8300
8140
8320
8340
8740
8520
8260
7260
7360
8620
8220
8360
8400
8080
8400
8500
8820
8580
7740
7640
7480
8900
7920
8560
8640
8340
9100
8720
9360
8800
8060
7380
7040
8020
7800
8380
8480
8320
8780
8360
9540
8880
7960
7660
7820
8680
8560
8720
8920




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=299526&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=299526&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299526&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 Mean6946.98122.25956.8219
Geometric Mean6807.89
Harmonic Mean6666.36
Quadratic Mean7080.18
Winsorized Mean ( 1 / 42 )6945.71121.99956.9325
Winsorized Mean ( 2 / 42 )6942.86121.17857.2949
Winsorized Mean ( 3 / 42 )6942.38120.01357.8469
Winsorized Mean ( 4 / 42 )6943.02119.74557.9818
Winsorized Mean ( 5 / 42 )6943.02119.52758.0874
Winsorized Mean ( 6 / 42 )6947.78118.10158.829
Winsorized Mean ( 7 / 42 )6948.89117.66459.0571
Winsorized Mean ( 8 / 42 )6948.89117.33759.2216
Winsorized Mean ( 9 / 42 )6948.89116.6159.5907
Winsorized Mean ( 10 / 42 )6948.89116.21159.7955
Winsorized Mean ( 11 / 42 )6948.89116.21159.7955
Winsorized Mean ( 12 / 42 )6950.79115.02260.43
Winsorized Mean ( 13 / 42 )6948.73114.27160.8095
Winsorized Mean ( 14 / 42 )6946.51114.00860.9297
Winsorized Mean ( 15 / 42 )6946.51112.8661.5498
Winsorized Mean ( 16 / 42 )6946.51112.25361.8824
Winsorized Mean ( 17 / 42 )6946.51112.25361.8824
Winsorized Mean ( 18 / 42 )6946.51110.90162.6368
Winsorized Mean ( 19 / 42 )6943.49110.5662.8027
Winsorized Mean ( 20 / 42 )6943.49109.81863.2271
Winsorized Mean ( 21 / 42 )6936.83107.54164.5038
Winsorized Mean ( 22 / 42 )6940.32107.12364.7885
Winsorized Mean ( 23 / 42 )6940.32106.29165.2957
Winsorized Mean ( 24 / 42 )6944.13105.83965.6104
Winsorized Mean ( 25 / 42 )6960103.09567.5104
Winsorized Mean ( 26 / 42 )6964.13102.62367.8615
Winsorized Mean ( 27 / 42 )6959.84102.15868.1283
Winsorized Mean ( 28 / 42 )6959.84102.15868.1283
Winsorized Mean ( 29 / 42 )6973.6599.576770.033
Winsorized Mean ( 30 / 42 )6983.1798.516370.8834
Winsorized Mean ( 31 / 42 )7027.4692.686775.8195
Winsorized Mean ( 32 / 42 )7027.4691.601876.7175
Winsorized Mean ( 33 / 42 )7027.4690.48877.6618
Winsorized Mean ( 34 / 42 )7022.0688.760979.1121
Winsorized Mean ( 35 / 42 )7005.485.813481.6353
Winsorized Mean ( 36 / 42 )6993.9783.425283.8352
Winsorized Mean ( 37 / 42 )6988.182.815384.3817
Winsorized Mean ( 38 / 42 )6976.0381.573185.5188
Winsorized Mean ( 39 / 42 )6976.0377.768989.7021
Winsorized Mean ( 40 / 42 )6963.3376.490991.0348
Winsorized Mean ( 41 / 42 )6950.3275.19692.4294
Winsorized Mean ( 42 / 42 )6963.6571.147897.8758
Trimmed Mean ( 1 / 42 )6945.97120.81257.4942
Trimmed Mean ( 2 / 42 )6946.23119.49858.1282
Trimmed Mean ( 3 / 42 )6948118.51158.6274
Trimmed Mean ( 4 / 42 )6950117.86558.9655
Trimmed Mean ( 5 / 42 )6951.9117.21659.3086
Trimmed Mean ( 6 / 42 )6953.86116.53359.673
Trimmed Mean ( 7 / 42 )6955116.06759.9223
Trimmed Mean ( 8 / 42 )6956115.60960.1683
Trimmed Mean ( 9 / 42 )6957.04115.13160.4271
Trimmed Mean ( 10 / 42 )6958.11114.68960.6695
Trimmed Mean ( 11 / 42 )6959.23114.22760.9248
Trimmed Mean ( 12 / 42 )6960.39113.6861.2277
Trimmed Mean ( 13 / 42 )6961.4113.20161.4957
Trimmed Mean ( 14 / 42 )6962.65112.72961.7643
Trimmed Mean ( 15 / 42 )6964.17112.19762.0707
Trimmed Mean ( 16 / 42 )6965.74111.70462.3588
Trimmed Mean ( 17 / 42 )6967.39111.18362.666
Trimmed Mean ( 18 / 42 )6969.11110.55563.0374
Trimmed Mean ( 19 / 42 )6970.91109.96363.3933
Trimmed Mean ( 20 / 42 )6973.02109.28863.8042
Trimmed Mean ( 21 / 42 )6975.24108.56364.2505
Trimmed Mean ( 22 / 42 )6978.05107.9564.6412
Trimmed Mean ( 23 / 42 )6980.75107.2565.0889
Trimmed Mean ( 24 / 42 )6983.59106.49165.5791
Trimmed Mean ( 25 / 42 )6986.32105.62166.1451
Trimmed Mean ( 26 / 42 )6988.11104.8966.6234
Trimmed Mean ( 27 / 42 )6989.72104.04167.1823
Trimmed Mean ( 28 / 42 )6991.71103.05167.847
Trimmed Mean ( 29 / 42 )6993.82101.83768.6768
Trimmed Mean ( 30 / 42 )6995.15100.68769.4744
Trimmed Mean ( 31 / 42 )6995.9499.409170.3752
Trimmed Mean ( 32 / 42 )6993.8798.590470.9387
Trimmed Mean ( 33 / 42 )6991.6797.678571.5784
Trimmed Mean ( 34 / 42 )6989.3196.655872.3114
Trimmed Mean ( 35 / 42 )6987.1495.584973.0988
Trimmed Mean ( 36 / 42 )6985.9394.63173.8228
Trimmed Mean ( 37 / 42 )6985.3893.724974.5308
Trimmed Mean ( 38 / 42 )6985.292.595875.4376
Trimmed Mean ( 39 / 42 )6985.8391.28976.5244
Trimmed Mean ( 40 / 42 )6986.5290.195877.4595
Trimmed Mean ( 41 / 42 )6988.1888.907778.6004
Trimmed Mean ( 42 / 42 )6990.9587.364880.0202
Median7060
Midrange7010
Midmean - Weighted Average at Xnp6975.24
Midmean - Weighted Average at X(n+1)p6995.94
Midmean - Empirical Distribution Function6995.94
Midmean - Empirical Distribution Function - Averaging6995.94
Midmean - Empirical Distribution Function - Interpolation6993.87
Midmean - Closest Observation6995.94
Midmean - True Basic - Statistics Graphics Toolkit6995.94
Midmean - MS Excel (old versions)6995.94
Number of observations126

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 6946.98 & 122.259 & 56.8219 \tabularnewline
Geometric Mean & 6807.89 &  &  \tabularnewline
Harmonic Mean & 6666.36 &  &  \tabularnewline
Quadratic Mean & 7080.18 &  &  \tabularnewline
Winsorized Mean ( 1 / 42 ) & 6945.71 & 121.999 & 56.9325 \tabularnewline
Winsorized Mean ( 2 / 42 ) & 6942.86 & 121.178 & 57.2949 \tabularnewline
Winsorized Mean ( 3 / 42 ) & 6942.38 & 120.013 & 57.8469 \tabularnewline
Winsorized Mean ( 4 / 42 ) & 6943.02 & 119.745 & 57.9818 \tabularnewline
Winsorized Mean ( 5 / 42 ) & 6943.02 & 119.527 & 58.0874 \tabularnewline
Winsorized Mean ( 6 / 42 ) & 6947.78 & 118.101 & 58.829 \tabularnewline
Winsorized Mean ( 7 / 42 ) & 6948.89 & 117.664 & 59.0571 \tabularnewline
Winsorized Mean ( 8 / 42 ) & 6948.89 & 117.337 & 59.2216 \tabularnewline
Winsorized Mean ( 9 / 42 ) & 6948.89 & 116.61 & 59.5907 \tabularnewline
Winsorized Mean ( 10 / 42 ) & 6948.89 & 116.211 & 59.7955 \tabularnewline
Winsorized Mean ( 11 / 42 ) & 6948.89 & 116.211 & 59.7955 \tabularnewline
Winsorized Mean ( 12 / 42 ) & 6950.79 & 115.022 & 60.43 \tabularnewline
Winsorized Mean ( 13 / 42 ) & 6948.73 & 114.271 & 60.8095 \tabularnewline
Winsorized Mean ( 14 / 42 ) & 6946.51 & 114.008 & 60.9297 \tabularnewline
Winsorized Mean ( 15 / 42 ) & 6946.51 & 112.86 & 61.5498 \tabularnewline
Winsorized Mean ( 16 / 42 ) & 6946.51 & 112.253 & 61.8824 \tabularnewline
Winsorized Mean ( 17 / 42 ) & 6946.51 & 112.253 & 61.8824 \tabularnewline
Winsorized Mean ( 18 / 42 ) & 6946.51 & 110.901 & 62.6368 \tabularnewline
Winsorized Mean ( 19 / 42 ) & 6943.49 & 110.56 & 62.8027 \tabularnewline
Winsorized Mean ( 20 / 42 ) & 6943.49 & 109.818 & 63.2271 \tabularnewline
Winsorized Mean ( 21 / 42 ) & 6936.83 & 107.541 & 64.5038 \tabularnewline
Winsorized Mean ( 22 / 42 ) & 6940.32 & 107.123 & 64.7885 \tabularnewline
Winsorized Mean ( 23 / 42 ) & 6940.32 & 106.291 & 65.2957 \tabularnewline
Winsorized Mean ( 24 / 42 ) & 6944.13 & 105.839 & 65.6104 \tabularnewline
Winsorized Mean ( 25 / 42 ) & 6960 & 103.095 & 67.5104 \tabularnewline
Winsorized Mean ( 26 / 42 ) & 6964.13 & 102.623 & 67.8615 \tabularnewline
Winsorized Mean ( 27 / 42 ) & 6959.84 & 102.158 & 68.1283 \tabularnewline
Winsorized Mean ( 28 / 42 ) & 6959.84 & 102.158 & 68.1283 \tabularnewline
Winsorized Mean ( 29 / 42 ) & 6973.65 & 99.5767 & 70.033 \tabularnewline
Winsorized Mean ( 30 / 42 ) & 6983.17 & 98.5163 & 70.8834 \tabularnewline
Winsorized Mean ( 31 / 42 ) & 7027.46 & 92.6867 & 75.8195 \tabularnewline
Winsorized Mean ( 32 / 42 ) & 7027.46 & 91.6018 & 76.7175 \tabularnewline
Winsorized Mean ( 33 / 42 ) & 7027.46 & 90.488 & 77.6618 \tabularnewline
Winsorized Mean ( 34 / 42 ) & 7022.06 & 88.7609 & 79.1121 \tabularnewline
Winsorized Mean ( 35 / 42 ) & 7005.4 & 85.8134 & 81.6353 \tabularnewline
Winsorized Mean ( 36 / 42 ) & 6993.97 & 83.4252 & 83.8352 \tabularnewline
Winsorized Mean ( 37 / 42 ) & 6988.1 & 82.8153 & 84.3817 \tabularnewline
Winsorized Mean ( 38 / 42 ) & 6976.03 & 81.5731 & 85.5188 \tabularnewline
Winsorized Mean ( 39 / 42 ) & 6976.03 & 77.7689 & 89.7021 \tabularnewline
Winsorized Mean ( 40 / 42 ) & 6963.33 & 76.4909 & 91.0348 \tabularnewline
Winsorized Mean ( 41 / 42 ) & 6950.32 & 75.196 & 92.4294 \tabularnewline
Winsorized Mean ( 42 / 42 ) & 6963.65 & 71.1478 & 97.8758 \tabularnewline
Trimmed Mean ( 1 / 42 ) & 6945.97 & 120.812 & 57.4942 \tabularnewline
Trimmed Mean ( 2 / 42 ) & 6946.23 & 119.498 & 58.1282 \tabularnewline
Trimmed Mean ( 3 / 42 ) & 6948 & 118.511 & 58.6274 \tabularnewline
Trimmed Mean ( 4 / 42 ) & 6950 & 117.865 & 58.9655 \tabularnewline
Trimmed Mean ( 5 / 42 ) & 6951.9 & 117.216 & 59.3086 \tabularnewline
Trimmed Mean ( 6 / 42 ) & 6953.86 & 116.533 & 59.673 \tabularnewline
Trimmed Mean ( 7 / 42 ) & 6955 & 116.067 & 59.9223 \tabularnewline
Trimmed Mean ( 8 / 42 ) & 6956 & 115.609 & 60.1683 \tabularnewline
Trimmed Mean ( 9 / 42 ) & 6957.04 & 115.131 & 60.4271 \tabularnewline
Trimmed Mean ( 10 / 42 ) & 6958.11 & 114.689 & 60.6695 \tabularnewline
Trimmed Mean ( 11 / 42 ) & 6959.23 & 114.227 & 60.9248 \tabularnewline
Trimmed Mean ( 12 / 42 ) & 6960.39 & 113.68 & 61.2277 \tabularnewline
Trimmed Mean ( 13 / 42 ) & 6961.4 & 113.201 & 61.4957 \tabularnewline
Trimmed Mean ( 14 / 42 ) & 6962.65 & 112.729 & 61.7643 \tabularnewline
Trimmed Mean ( 15 / 42 ) & 6964.17 & 112.197 & 62.0707 \tabularnewline
Trimmed Mean ( 16 / 42 ) & 6965.74 & 111.704 & 62.3588 \tabularnewline
Trimmed Mean ( 17 / 42 ) & 6967.39 & 111.183 & 62.666 \tabularnewline
Trimmed Mean ( 18 / 42 ) & 6969.11 & 110.555 & 63.0374 \tabularnewline
Trimmed Mean ( 19 / 42 ) & 6970.91 & 109.963 & 63.3933 \tabularnewline
Trimmed Mean ( 20 / 42 ) & 6973.02 & 109.288 & 63.8042 \tabularnewline
Trimmed Mean ( 21 / 42 ) & 6975.24 & 108.563 & 64.2505 \tabularnewline
Trimmed Mean ( 22 / 42 ) & 6978.05 & 107.95 & 64.6412 \tabularnewline
Trimmed Mean ( 23 / 42 ) & 6980.75 & 107.25 & 65.0889 \tabularnewline
Trimmed Mean ( 24 / 42 ) & 6983.59 & 106.491 & 65.5791 \tabularnewline
Trimmed Mean ( 25 / 42 ) & 6986.32 & 105.621 & 66.1451 \tabularnewline
Trimmed Mean ( 26 / 42 ) & 6988.11 & 104.89 & 66.6234 \tabularnewline
Trimmed Mean ( 27 / 42 ) & 6989.72 & 104.041 & 67.1823 \tabularnewline
Trimmed Mean ( 28 / 42 ) & 6991.71 & 103.051 & 67.847 \tabularnewline
Trimmed Mean ( 29 / 42 ) & 6993.82 & 101.837 & 68.6768 \tabularnewline
Trimmed Mean ( 30 / 42 ) & 6995.15 & 100.687 & 69.4744 \tabularnewline
Trimmed Mean ( 31 / 42 ) & 6995.94 & 99.4091 & 70.3752 \tabularnewline
Trimmed Mean ( 32 / 42 ) & 6993.87 & 98.5904 & 70.9387 \tabularnewline
Trimmed Mean ( 33 / 42 ) & 6991.67 & 97.6785 & 71.5784 \tabularnewline
Trimmed Mean ( 34 / 42 ) & 6989.31 & 96.6558 & 72.3114 \tabularnewline
Trimmed Mean ( 35 / 42 ) & 6987.14 & 95.5849 & 73.0988 \tabularnewline
Trimmed Mean ( 36 / 42 ) & 6985.93 & 94.631 & 73.8228 \tabularnewline
Trimmed Mean ( 37 / 42 ) & 6985.38 & 93.7249 & 74.5308 \tabularnewline
Trimmed Mean ( 38 / 42 ) & 6985.2 & 92.5958 & 75.4376 \tabularnewline
Trimmed Mean ( 39 / 42 ) & 6985.83 & 91.289 & 76.5244 \tabularnewline
Trimmed Mean ( 40 / 42 ) & 6986.52 & 90.1958 & 77.4595 \tabularnewline
Trimmed Mean ( 41 / 42 ) & 6988.18 & 88.9077 & 78.6004 \tabularnewline
Trimmed Mean ( 42 / 42 ) & 6990.95 & 87.3648 & 80.0202 \tabularnewline
Median & 7060 &  &  \tabularnewline
Midrange & 7010 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 6975.24 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 6995.94 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 6995.94 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 6995.94 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 6993.87 &  &  \tabularnewline
Midmean - Closest Observation & 6995.94 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 6995.94 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 6995.94 &  &  \tabularnewline
Number of observations & 126 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299526&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]6946.98[/C][C]122.259[/C][C]56.8219[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]6807.89[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]6666.36[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]7080.18[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 42 )[/C][C]6945.71[/C][C]121.999[/C][C]56.9325[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 42 )[/C][C]6942.86[/C][C]121.178[/C][C]57.2949[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 42 )[/C][C]6942.38[/C][C]120.013[/C][C]57.8469[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 42 )[/C][C]6943.02[/C][C]119.745[/C][C]57.9818[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 42 )[/C][C]6943.02[/C][C]119.527[/C][C]58.0874[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 42 )[/C][C]6947.78[/C][C]118.101[/C][C]58.829[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 42 )[/C][C]6948.89[/C][C]117.664[/C][C]59.0571[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 42 )[/C][C]6948.89[/C][C]117.337[/C][C]59.2216[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 42 )[/C][C]6948.89[/C][C]116.61[/C][C]59.5907[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 42 )[/C][C]6948.89[/C][C]116.211[/C][C]59.7955[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 42 )[/C][C]6948.89[/C][C]116.211[/C][C]59.7955[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 42 )[/C][C]6950.79[/C][C]115.022[/C][C]60.43[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 42 )[/C][C]6948.73[/C][C]114.271[/C][C]60.8095[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 42 )[/C][C]6946.51[/C][C]114.008[/C][C]60.9297[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 42 )[/C][C]6946.51[/C][C]112.86[/C][C]61.5498[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 42 )[/C][C]6946.51[/C][C]112.253[/C][C]61.8824[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 42 )[/C][C]6946.51[/C][C]112.253[/C][C]61.8824[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 42 )[/C][C]6946.51[/C][C]110.901[/C][C]62.6368[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 42 )[/C][C]6943.49[/C][C]110.56[/C][C]62.8027[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 42 )[/C][C]6943.49[/C][C]109.818[/C][C]63.2271[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 42 )[/C][C]6936.83[/C][C]107.541[/C][C]64.5038[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 42 )[/C][C]6940.32[/C][C]107.123[/C][C]64.7885[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 42 )[/C][C]6940.32[/C][C]106.291[/C][C]65.2957[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 42 )[/C][C]6944.13[/C][C]105.839[/C][C]65.6104[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 42 )[/C][C]6960[/C][C]103.095[/C][C]67.5104[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 42 )[/C][C]6964.13[/C][C]102.623[/C][C]67.8615[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 42 )[/C][C]6959.84[/C][C]102.158[/C][C]68.1283[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 42 )[/C][C]6959.84[/C][C]102.158[/C][C]68.1283[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 42 )[/C][C]6973.65[/C][C]99.5767[/C][C]70.033[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 42 )[/C][C]6983.17[/C][C]98.5163[/C][C]70.8834[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 42 )[/C][C]7027.46[/C][C]92.6867[/C][C]75.8195[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 42 )[/C][C]7027.46[/C][C]91.6018[/C][C]76.7175[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 42 )[/C][C]7027.46[/C][C]90.488[/C][C]77.6618[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 42 )[/C][C]7022.06[/C][C]88.7609[/C][C]79.1121[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 42 )[/C][C]7005.4[/C][C]85.8134[/C][C]81.6353[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 42 )[/C][C]6993.97[/C][C]83.4252[/C][C]83.8352[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 42 )[/C][C]6988.1[/C][C]82.8153[/C][C]84.3817[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 42 )[/C][C]6976.03[/C][C]81.5731[/C][C]85.5188[/C][/ROW]
[ROW][C]Winsorized Mean ( 39 / 42 )[/C][C]6976.03[/C][C]77.7689[/C][C]89.7021[/C][/ROW]
[ROW][C]Winsorized Mean ( 40 / 42 )[/C][C]6963.33[/C][C]76.4909[/C][C]91.0348[/C][/ROW]
[ROW][C]Winsorized Mean ( 41 / 42 )[/C][C]6950.32[/C][C]75.196[/C][C]92.4294[/C][/ROW]
[ROW][C]Winsorized Mean ( 42 / 42 )[/C][C]6963.65[/C][C]71.1478[/C][C]97.8758[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 42 )[/C][C]6945.97[/C][C]120.812[/C][C]57.4942[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 42 )[/C][C]6946.23[/C][C]119.498[/C][C]58.1282[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 42 )[/C][C]6948[/C][C]118.511[/C][C]58.6274[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 42 )[/C][C]6950[/C][C]117.865[/C][C]58.9655[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 42 )[/C][C]6951.9[/C][C]117.216[/C][C]59.3086[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 42 )[/C][C]6953.86[/C][C]116.533[/C][C]59.673[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 42 )[/C][C]6955[/C][C]116.067[/C][C]59.9223[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 42 )[/C][C]6956[/C][C]115.609[/C][C]60.1683[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 42 )[/C][C]6957.04[/C][C]115.131[/C][C]60.4271[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 42 )[/C][C]6958.11[/C][C]114.689[/C][C]60.6695[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 42 )[/C][C]6959.23[/C][C]114.227[/C][C]60.9248[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 42 )[/C][C]6960.39[/C][C]113.68[/C][C]61.2277[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 42 )[/C][C]6961.4[/C][C]113.201[/C][C]61.4957[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 42 )[/C][C]6962.65[/C][C]112.729[/C][C]61.7643[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 42 )[/C][C]6964.17[/C][C]112.197[/C][C]62.0707[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 42 )[/C][C]6965.74[/C][C]111.704[/C][C]62.3588[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 42 )[/C][C]6967.39[/C][C]111.183[/C][C]62.666[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 42 )[/C][C]6969.11[/C][C]110.555[/C][C]63.0374[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 42 )[/C][C]6970.91[/C][C]109.963[/C][C]63.3933[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 42 )[/C][C]6973.02[/C][C]109.288[/C][C]63.8042[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 42 )[/C][C]6975.24[/C][C]108.563[/C][C]64.2505[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 42 )[/C][C]6978.05[/C][C]107.95[/C][C]64.6412[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 42 )[/C][C]6980.75[/C][C]107.25[/C][C]65.0889[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 42 )[/C][C]6983.59[/C][C]106.491[/C][C]65.5791[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 42 )[/C][C]6986.32[/C][C]105.621[/C][C]66.1451[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 42 )[/C][C]6988.11[/C][C]104.89[/C][C]66.6234[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 42 )[/C][C]6989.72[/C][C]104.041[/C][C]67.1823[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 42 )[/C][C]6991.71[/C][C]103.051[/C][C]67.847[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 42 )[/C][C]6993.82[/C][C]101.837[/C][C]68.6768[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 42 )[/C][C]6995.15[/C][C]100.687[/C][C]69.4744[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 42 )[/C][C]6995.94[/C][C]99.4091[/C][C]70.3752[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 42 )[/C][C]6993.87[/C][C]98.5904[/C][C]70.9387[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 42 )[/C][C]6991.67[/C][C]97.6785[/C][C]71.5784[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 42 )[/C][C]6989.31[/C][C]96.6558[/C][C]72.3114[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 42 )[/C][C]6987.14[/C][C]95.5849[/C][C]73.0988[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 42 )[/C][C]6985.93[/C][C]94.631[/C][C]73.8228[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 42 )[/C][C]6985.38[/C][C]93.7249[/C][C]74.5308[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 42 )[/C][C]6985.2[/C][C]92.5958[/C][C]75.4376[/C][/ROW]
[ROW][C]Trimmed Mean ( 39 / 42 )[/C][C]6985.83[/C][C]91.289[/C][C]76.5244[/C][/ROW]
[ROW][C]Trimmed Mean ( 40 / 42 )[/C][C]6986.52[/C][C]90.1958[/C][C]77.4595[/C][/ROW]
[ROW][C]Trimmed Mean ( 41 / 42 )[/C][C]6988.18[/C][C]88.9077[/C][C]78.6004[/C][/ROW]
[ROW][C]Trimmed Mean ( 42 / 42 )[/C][C]6990.95[/C][C]87.3648[/C][C]80.0202[/C][/ROW]
[ROW][C]Median[/C][C]7060[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]7010[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]6975.24[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]6995.94[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]6995.94[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]6995.94[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]6993.87[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]6995.94[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]6995.94[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]6995.94[/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=299526&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299526&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 Mean6946.98122.25956.8219
Geometric Mean6807.89
Harmonic Mean6666.36
Quadratic Mean7080.18
Winsorized Mean ( 1 / 42 )6945.71121.99956.9325
Winsorized Mean ( 2 / 42 )6942.86121.17857.2949
Winsorized Mean ( 3 / 42 )6942.38120.01357.8469
Winsorized Mean ( 4 / 42 )6943.02119.74557.9818
Winsorized Mean ( 5 / 42 )6943.02119.52758.0874
Winsorized Mean ( 6 / 42 )6947.78118.10158.829
Winsorized Mean ( 7 / 42 )6948.89117.66459.0571
Winsorized Mean ( 8 / 42 )6948.89117.33759.2216
Winsorized Mean ( 9 / 42 )6948.89116.6159.5907
Winsorized Mean ( 10 / 42 )6948.89116.21159.7955
Winsorized Mean ( 11 / 42 )6948.89116.21159.7955
Winsorized Mean ( 12 / 42 )6950.79115.02260.43
Winsorized Mean ( 13 / 42 )6948.73114.27160.8095
Winsorized Mean ( 14 / 42 )6946.51114.00860.9297
Winsorized Mean ( 15 / 42 )6946.51112.8661.5498
Winsorized Mean ( 16 / 42 )6946.51112.25361.8824
Winsorized Mean ( 17 / 42 )6946.51112.25361.8824
Winsorized Mean ( 18 / 42 )6946.51110.90162.6368
Winsorized Mean ( 19 / 42 )6943.49110.5662.8027
Winsorized Mean ( 20 / 42 )6943.49109.81863.2271
Winsorized Mean ( 21 / 42 )6936.83107.54164.5038
Winsorized Mean ( 22 / 42 )6940.32107.12364.7885
Winsorized Mean ( 23 / 42 )6940.32106.29165.2957
Winsorized Mean ( 24 / 42 )6944.13105.83965.6104
Winsorized Mean ( 25 / 42 )6960103.09567.5104
Winsorized Mean ( 26 / 42 )6964.13102.62367.8615
Winsorized Mean ( 27 / 42 )6959.84102.15868.1283
Winsorized Mean ( 28 / 42 )6959.84102.15868.1283
Winsorized Mean ( 29 / 42 )6973.6599.576770.033
Winsorized Mean ( 30 / 42 )6983.1798.516370.8834
Winsorized Mean ( 31 / 42 )7027.4692.686775.8195
Winsorized Mean ( 32 / 42 )7027.4691.601876.7175
Winsorized Mean ( 33 / 42 )7027.4690.48877.6618
Winsorized Mean ( 34 / 42 )7022.0688.760979.1121
Winsorized Mean ( 35 / 42 )7005.485.813481.6353
Winsorized Mean ( 36 / 42 )6993.9783.425283.8352
Winsorized Mean ( 37 / 42 )6988.182.815384.3817
Winsorized Mean ( 38 / 42 )6976.0381.573185.5188
Winsorized Mean ( 39 / 42 )6976.0377.768989.7021
Winsorized Mean ( 40 / 42 )6963.3376.490991.0348
Winsorized Mean ( 41 / 42 )6950.3275.19692.4294
Winsorized Mean ( 42 / 42 )6963.6571.147897.8758
Trimmed Mean ( 1 / 42 )6945.97120.81257.4942
Trimmed Mean ( 2 / 42 )6946.23119.49858.1282
Trimmed Mean ( 3 / 42 )6948118.51158.6274
Trimmed Mean ( 4 / 42 )6950117.86558.9655
Trimmed Mean ( 5 / 42 )6951.9117.21659.3086
Trimmed Mean ( 6 / 42 )6953.86116.53359.673
Trimmed Mean ( 7 / 42 )6955116.06759.9223
Trimmed Mean ( 8 / 42 )6956115.60960.1683
Trimmed Mean ( 9 / 42 )6957.04115.13160.4271
Trimmed Mean ( 10 / 42 )6958.11114.68960.6695
Trimmed Mean ( 11 / 42 )6959.23114.22760.9248
Trimmed Mean ( 12 / 42 )6960.39113.6861.2277
Trimmed Mean ( 13 / 42 )6961.4113.20161.4957
Trimmed Mean ( 14 / 42 )6962.65112.72961.7643
Trimmed Mean ( 15 / 42 )6964.17112.19762.0707
Trimmed Mean ( 16 / 42 )6965.74111.70462.3588
Trimmed Mean ( 17 / 42 )6967.39111.18362.666
Trimmed Mean ( 18 / 42 )6969.11110.55563.0374
Trimmed Mean ( 19 / 42 )6970.91109.96363.3933
Trimmed Mean ( 20 / 42 )6973.02109.28863.8042
Trimmed Mean ( 21 / 42 )6975.24108.56364.2505
Trimmed Mean ( 22 / 42 )6978.05107.9564.6412
Trimmed Mean ( 23 / 42 )6980.75107.2565.0889
Trimmed Mean ( 24 / 42 )6983.59106.49165.5791
Trimmed Mean ( 25 / 42 )6986.32105.62166.1451
Trimmed Mean ( 26 / 42 )6988.11104.8966.6234
Trimmed Mean ( 27 / 42 )6989.72104.04167.1823
Trimmed Mean ( 28 / 42 )6991.71103.05167.847
Trimmed Mean ( 29 / 42 )6993.82101.83768.6768
Trimmed Mean ( 30 / 42 )6995.15100.68769.4744
Trimmed Mean ( 31 / 42 )6995.9499.409170.3752
Trimmed Mean ( 32 / 42 )6993.8798.590470.9387
Trimmed Mean ( 33 / 42 )6991.6797.678571.5784
Trimmed Mean ( 34 / 42 )6989.3196.655872.3114
Trimmed Mean ( 35 / 42 )6987.1495.584973.0988
Trimmed Mean ( 36 / 42 )6985.9394.63173.8228
Trimmed Mean ( 37 / 42 )6985.3893.724974.5308
Trimmed Mean ( 38 / 42 )6985.292.595875.4376
Trimmed Mean ( 39 / 42 )6985.8391.28976.5244
Trimmed Mean ( 40 / 42 )6986.5290.195877.4595
Trimmed Mean ( 41 / 42 )6988.1888.907778.6004
Trimmed Mean ( 42 / 42 )6990.9587.364880.0202
Median7060
Midrange7010
Midmean - Weighted Average at Xnp6975.24
Midmean - Weighted Average at X(n+1)p6995.94
Midmean - Empirical Distribution Function6995.94
Midmean - Empirical Distribution Function - Averaging6995.94
Midmean - Empirical Distribution Function - Interpolation6993.87
Midmean - Closest Observation6995.94
Midmean - True Basic - Statistics Graphics Toolkit6995.94
Midmean - MS Excel (old versions)6995.94
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')