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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationWed, 16 Aug 2017 16:01:41 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Aug/16/t1502892118rkhvcel4qfsf0ym.htm/, Retrieved Sat, 11 May 2024 22:48:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307401, Retrieved Sat, 11 May 2024 22:48:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact79
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Robuustheid: omze...] [2017-08-16 14:01:41] [de0d54ff4aa383cef5d270d23e3500df] [Current]
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Dataseries X:
1189593.60
1185163.20
1180670.40
1171372.80
1263350.40
1258483.20
1189593.60
1143792.00
1148222.40
1148222.40
1153152.00
1162012.80
1175803.20
1175803.20
1166942.40
1143792.00
1263350.40
1281571.20
1254052.80
1189593.60
1217174.40
1175803.20
1194460.80
1203384.00
1212681.60
1189593.60
1194460.80
1162012.80
1263350.40
1295361.60
1267843.20
1217174.40
1272273.60
1212681.60
1267843.20
1263350.40
1277140.80
1226472.00
1281571.20
1277140.80
1359820.80
1341163.20
1267843.20
1230902.40
1281571.20
1212681.60
1263350.40
1272273.60
1290931.20
1249622.40
1272273.60
1286064.00
1336732.80
1295361.60
1240262.40
1180670.40
1235832.00
1084200.00
1157582.40
1198891.20
1240262.40
1180670.40
1180670.40
1180670.40
1212681.60
1166942.40
1106913.60
1056681.60
1093123.20
950851.20
1038024.00
1088692.80
1097990.40
1047321.60
1051752.00
1038024.00
1084200.00
1051752.00
987792.00
941553.60
1019740.80
849950.40
960211.20
1010443.20
1010443.20
950851.20
895752.00
891321.60
941553.60
895752.00
808641.60
748612.80
813072.00
661502.40
799281.60
872601.60
895752.00
845083.20
781060.80
826862.40
845083.20
831292.80
693451.20
629491.20
675230.40
537451.20
679723.20
730392.00
771700.80
702811.20
638352.00
675230.40
693451.20
657009.60
519230.40
459201.60
514300.80
362731.20
528091.20
629491.20




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307401&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]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=307401&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307401&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 time2 seconds
R ServerBig Analytics Cloud Computing Center







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean104686021604.748.4552
Geometric Mean1014120
Harmonic Mean973625
Quadratic Mean1073060
Winsorized Mean ( 1 / 40 )104751021386.348.9804
Winsorized Mean ( 2 / 40 )104835021174.349.5106
Winsorized Mean ( 3 / 40 )104744021037.849.7885
Winsorized Mean ( 4 / 40 )104774020975.949.9495
Winsorized Mean ( 5 / 40 )104794020877.150.1959
Winsorized Mean ( 6 / 40 )105230019969.652.6952
Winsorized Mean ( 7 / 40 )10520401994452.7496
Winsorized Mean ( 8 / 40 )105263019839.653.057
Winsorized Mean ( 9 / 40 )105403019597.753.7833
Winsorized Mean ( 10 / 40 )105403019498.454.0575
Winsorized Mean ( 11 / 40 )105529019287.754.7131
Winsorized Mean ( 12 / 40 )105481019241.154.8204
Winsorized Mean ( 13 / 40 )105529019160.755.0759
Winsorized Mean ( 14 / 40 )105689018899.355.9222
Winsorized Mean ( 15 / 40 )105634018846.756.049
Winsorized Mean ( 16 / 40 )10575901864656.7194
Winsorized Mean ( 17 / 40 )10615001803258.8674
Winsorized Mean ( 18 / 40 )106355017550.360.6003
Winsorized Mean ( 19 / 40 )106721017007.762.7487
Winsorized Mean ( 20 / 40 )106877016781.463.6878
Winsorized Mean ( 21 / 40 )107196016327.965.652
Winsorized Mean ( 22 / 40 )107367016088.766.7347
Winsorized Mean ( 23 / 40 )107359015879.567.6085
Winsorized Mean ( 24 / 40 )10754601541669.7628
Winsorized Mean ( 25 / 40 )107546015201.870.7457
Winsorized Mean ( 26 / 40 )107642014608.173.6869
Winsorized Mean ( 27 / 40 )107642014608.173.6869
Winsorized Mean ( 28 / 40 )107652014360.374.9654
Winsorized Mean ( 29 / 40 )108081013532.279.8693
Winsorized Mean ( 30 / 40 )108438012830.484.5162
Winsorized Mean ( 31 / 40 )108312012465.586.8899
Winsorized Mean ( 32 / 40 )108312012465.586.8899
Winsorized Mean ( 33 / 40 )108189012354.787.5691
Winsorized Mean ( 34 / 40 )109486010752.7101.822
Winsorized Mean ( 35 / 40 )109486010752.7101.822
Winsorized Mean ( 36 / 40 )109765010420.5105.336
Winsorized Mean ( 37 / 40 )109479010158.7107.768
Winsorized Mean ( 38 / 40 )10963309679.83113.259
Winsorized Mean ( 39 / 40 )11038508506.84129.76
Winsorized Mean ( 40 / 40 )11114007654.86145.189
Trimmed Mean ( 1 / 40 )105000021016.849.9602
Trimmed Mean ( 2 / 40 )105259020604.851.0845
Trimmed Mean ( 3 / 40 )105482020269.452.0398
Trimmed Mean ( 4 / 40 )105745019948.253.0099
Trimmed Mean ( 5 / 40 )106010019607.254.0669
Trimmed Mean ( 6 / 40 )10628001925055.2104
Trimmed Mean ( 7 / 40 )106478019062.155.8589
Trimmed Mean ( 8 / 40 )106689018852.656.5908
Trimmed Mean ( 9 / 40 )106898018633.957.3675
Trimmed Mean ( 10 / 40 )107098018427.658.1182
Trimmed Mean ( 11 / 40 )10730501820758.9361
Trimmed Mean ( 12 / 40 )107507017987.859.7664
Trimmed Mean ( 13 / 40 )107722017741.760.7172
Trimmed Mean ( 14 / 40 )107943017470.261.7867
Trimmed Mean ( 15 / 40 )108157017196.162.8961
Trimmed Mean ( 16 / 40 )108386016885.364.19
Trimmed Mean ( 17 / 40 )108616016554.565.6109
Trimmed Mean ( 18 / 40 )108823016260.366.9255
Trimmed Mean ( 19 / 40 )109023015984.468.2061
Trimmed Mean ( 20 / 40 )109205015737.969.39
Trimmed Mean ( 21 / 40 )10938401547970.6663
Trimmed Mean ( 22 / 40 )109549015236.971.8971
Trimmed Mean ( 23 / 40 )109710014982.973.2233
Trimmed Mean ( 24 / 40 )109880014707.374.711
Trimmed Mean ( 25 / 40 )110047014442.876.195
Trimmed Mean ( 26 / 40 )110223014152.977.8801
Trimmed Mean ( 27 / 40 )11040401388679.5073
Trimmed Mean ( 28 / 40 )110595013559.781.5616
Trimmed Mean ( 29 / 40 )110799013197.183.9569
Trimmed Mean ( 30 / 40 )110986012887.686.1185
Trimmed Mean ( 31 / 40 )111162012618.888.0927
Trimmed Mean ( 32 / 40 )111359012332.990.2945
Trimmed Mean ( 33 / 40 )111571011969.693.2118
Trimmed Mean ( 34 / 40 )111807011520.397.0522
Trimmed Mean ( 35 / 40 )111971011279.899.2668
Trimmed Mean ( 36 / 40 )112148010963.9102.289
Trimmed Mean ( 37 / 40 )112321010623.5105.729
Trimmed Mean ( 38 / 40 )112531010211.6110.199
Trimmed Mean ( 39 / 40 )11274809771.48115.385
Trimmed Mean ( 40 / 40 )11293009483.03119.087
Median1155370
Midrange861276
Midmean - Weighted Average at Xnp1105970
Midmean - Weighted Average at X(n+1)p1109860
Midmean - Empirical Distribution Function1105970
Midmean - Empirical Distribution Function - Averaging1109860
Midmean - Empirical Distribution Function - Interpolation1109860
Midmean - Closest Observation1105970
Midmean - True Basic - Statistics Graphics Toolkit1109860
Midmean - MS Excel (old versions)1107990
Number of observations120

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 1046860 & 21604.7 & 48.4552 \tabularnewline
Geometric Mean & 1014120 &  &  \tabularnewline
Harmonic Mean & 973625 &  &  \tabularnewline
Quadratic Mean & 1073060 &  &  \tabularnewline
Winsorized Mean ( 1 / 40 ) & 1047510 & 21386.3 & 48.9804 \tabularnewline
Winsorized Mean ( 2 / 40 ) & 1048350 & 21174.3 & 49.5106 \tabularnewline
Winsorized Mean ( 3 / 40 ) & 1047440 & 21037.8 & 49.7885 \tabularnewline
Winsorized Mean ( 4 / 40 ) & 1047740 & 20975.9 & 49.9495 \tabularnewline
Winsorized Mean ( 5 / 40 ) & 1047940 & 20877.1 & 50.1959 \tabularnewline
Winsorized Mean ( 6 / 40 ) & 1052300 & 19969.6 & 52.6952 \tabularnewline
Winsorized Mean ( 7 / 40 ) & 1052040 & 19944 & 52.7496 \tabularnewline
Winsorized Mean ( 8 / 40 ) & 1052630 & 19839.6 & 53.057 \tabularnewline
Winsorized Mean ( 9 / 40 ) & 1054030 & 19597.7 & 53.7833 \tabularnewline
Winsorized Mean ( 10 / 40 ) & 1054030 & 19498.4 & 54.0575 \tabularnewline
Winsorized Mean ( 11 / 40 ) & 1055290 & 19287.7 & 54.7131 \tabularnewline
Winsorized Mean ( 12 / 40 ) & 1054810 & 19241.1 & 54.8204 \tabularnewline
Winsorized Mean ( 13 / 40 ) & 1055290 & 19160.7 & 55.0759 \tabularnewline
Winsorized Mean ( 14 / 40 ) & 1056890 & 18899.3 & 55.9222 \tabularnewline
Winsorized Mean ( 15 / 40 ) & 1056340 & 18846.7 & 56.049 \tabularnewline
Winsorized Mean ( 16 / 40 ) & 1057590 & 18646 & 56.7194 \tabularnewline
Winsorized Mean ( 17 / 40 ) & 1061500 & 18032 & 58.8674 \tabularnewline
Winsorized Mean ( 18 / 40 ) & 1063550 & 17550.3 & 60.6003 \tabularnewline
Winsorized Mean ( 19 / 40 ) & 1067210 & 17007.7 & 62.7487 \tabularnewline
Winsorized Mean ( 20 / 40 ) & 1068770 & 16781.4 & 63.6878 \tabularnewline
Winsorized Mean ( 21 / 40 ) & 1071960 & 16327.9 & 65.652 \tabularnewline
Winsorized Mean ( 22 / 40 ) & 1073670 & 16088.7 & 66.7347 \tabularnewline
Winsorized Mean ( 23 / 40 ) & 1073590 & 15879.5 & 67.6085 \tabularnewline
Winsorized Mean ( 24 / 40 ) & 1075460 & 15416 & 69.7628 \tabularnewline
Winsorized Mean ( 25 / 40 ) & 1075460 & 15201.8 & 70.7457 \tabularnewline
Winsorized Mean ( 26 / 40 ) & 1076420 & 14608.1 & 73.6869 \tabularnewline
Winsorized Mean ( 27 / 40 ) & 1076420 & 14608.1 & 73.6869 \tabularnewline
Winsorized Mean ( 28 / 40 ) & 1076520 & 14360.3 & 74.9654 \tabularnewline
Winsorized Mean ( 29 / 40 ) & 1080810 & 13532.2 & 79.8693 \tabularnewline
Winsorized Mean ( 30 / 40 ) & 1084380 & 12830.4 & 84.5162 \tabularnewline
Winsorized Mean ( 31 / 40 ) & 1083120 & 12465.5 & 86.8899 \tabularnewline
Winsorized Mean ( 32 / 40 ) & 1083120 & 12465.5 & 86.8899 \tabularnewline
Winsorized Mean ( 33 / 40 ) & 1081890 & 12354.7 & 87.5691 \tabularnewline
Winsorized Mean ( 34 / 40 ) & 1094860 & 10752.7 & 101.822 \tabularnewline
Winsorized Mean ( 35 / 40 ) & 1094860 & 10752.7 & 101.822 \tabularnewline
Winsorized Mean ( 36 / 40 ) & 1097650 & 10420.5 & 105.336 \tabularnewline
Winsorized Mean ( 37 / 40 ) & 1094790 & 10158.7 & 107.768 \tabularnewline
Winsorized Mean ( 38 / 40 ) & 1096330 & 9679.83 & 113.259 \tabularnewline
Winsorized Mean ( 39 / 40 ) & 1103850 & 8506.84 & 129.76 \tabularnewline
Winsorized Mean ( 40 / 40 ) & 1111400 & 7654.86 & 145.189 \tabularnewline
Trimmed Mean ( 1 / 40 ) & 1050000 & 21016.8 & 49.9602 \tabularnewline
Trimmed Mean ( 2 / 40 ) & 1052590 & 20604.8 & 51.0845 \tabularnewline
Trimmed Mean ( 3 / 40 ) & 1054820 & 20269.4 & 52.0398 \tabularnewline
Trimmed Mean ( 4 / 40 ) & 1057450 & 19948.2 & 53.0099 \tabularnewline
Trimmed Mean ( 5 / 40 ) & 1060100 & 19607.2 & 54.0669 \tabularnewline
Trimmed Mean ( 6 / 40 ) & 1062800 & 19250 & 55.2104 \tabularnewline
Trimmed Mean ( 7 / 40 ) & 1064780 & 19062.1 & 55.8589 \tabularnewline
Trimmed Mean ( 8 / 40 ) & 1066890 & 18852.6 & 56.5908 \tabularnewline
Trimmed Mean ( 9 / 40 ) & 1068980 & 18633.9 & 57.3675 \tabularnewline
Trimmed Mean ( 10 / 40 ) & 1070980 & 18427.6 & 58.1182 \tabularnewline
Trimmed Mean ( 11 / 40 ) & 1073050 & 18207 & 58.9361 \tabularnewline
Trimmed Mean ( 12 / 40 ) & 1075070 & 17987.8 & 59.7664 \tabularnewline
Trimmed Mean ( 13 / 40 ) & 1077220 & 17741.7 & 60.7172 \tabularnewline
Trimmed Mean ( 14 / 40 ) & 1079430 & 17470.2 & 61.7867 \tabularnewline
Trimmed Mean ( 15 / 40 ) & 1081570 & 17196.1 & 62.8961 \tabularnewline
Trimmed Mean ( 16 / 40 ) & 1083860 & 16885.3 & 64.19 \tabularnewline
Trimmed Mean ( 17 / 40 ) & 1086160 & 16554.5 & 65.6109 \tabularnewline
Trimmed Mean ( 18 / 40 ) & 1088230 & 16260.3 & 66.9255 \tabularnewline
Trimmed Mean ( 19 / 40 ) & 1090230 & 15984.4 & 68.2061 \tabularnewline
Trimmed Mean ( 20 / 40 ) & 1092050 & 15737.9 & 69.39 \tabularnewline
Trimmed Mean ( 21 / 40 ) & 1093840 & 15479 & 70.6663 \tabularnewline
Trimmed Mean ( 22 / 40 ) & 1095490 & 15236.9 & 71.8971 \tabularnewline
Trimmed Mean ( 23 / 40 ) & 1097100 & 14982.9 & 73.2233 \tabularnewline
Trimmed Mean ( 24 / 40 ) & 1098800 & 14707.3 & 74.711 \tabularnewline
Trimmed Mean ( 25 / 40 ) & 1100470 & 14442.8 & 76.195 \tabularnewline
Trimmed Mean ( 26 / 40 ) & 1102230 & 14152.9 & 77.8801 \tabularnewline
Trimmed Mean ( 27 / 40 ) & 1104040 & 13886 & 79.5073 \tabularnewline
Trimmed Mean ( 28 / 40 ) & 1105950 & 13559.7 & 81.5616 \tabularnewline
Trimmed Mean ( 29 / 40 ) & 1107990 & 13197.1 & 83.9569 \tabularnewline
Trimmed Mean ( 30 / 40 ) & 1109860 & 12887.6 & 86.1185 \tabularnewline
Trimmed Mean ( 31 / 40 ) & 1111620 & 12618.8 & 88.0927 \tabularnewline
Trimmed Mean ( 32 / 40 ) & 1113590 & 12332.9 & 90.2945 \tabularnewline
Trimmed Mean ( 33 / 40 ) & 1115710 & 11969.6 & 93.2118 \tabularnewline
Trimmed Mean ( 34 / 40 ) & 1118070 & 11520.3 & 97.0522 \tabularnewline
Trimmed Mean ( 35 / 40 ) & 1119710 & 11279.8 & 99.2668 \tabularnewline
Trimmed Mean ( 36 / 40 ) & 1121480 & 10963.9 & 102.289 \tabularnewline
Trimmed Mean ( 37 / 40 ) & 1123210 & 10623.5 & 105.729 \tabularnewline
Trimmed Mean ( 38 / 40 ) & 1125310 & 10211.6 & 110.199 \tabularnewline
Trimmed Mean ( 39 / 40 ) & 1127480 & 9771.48 & 115.385 \tabularnewline
Trimmed Mean ( 40 / 40 ) & 1129300 & 9483.03 & 119.087 \tabularnewline
Median & 1155370 &  &  \tabularnewline
Midrange & 861276 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 1105970 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 1109860 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 1105970 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 1109860 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 1109860 &  &  \tabularnewline
Midmean - Closest Observation & 1105970 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 1109860 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 1107990 &  &  \tabularnewline
Number of observations & 120 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307401&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]1046860[/C][C]21604.7[/C][C]48.4552[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]1014120[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]973625[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]1073060[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 40 )[/C][C]1047510[/C][C]21386.3[/C][C]48.9804[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 40 )[/C][C]1048350[/C][C]21174.3[/C][C]49.5106[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 40 )[/C][C]1047440[/C][C]21037.8[/C][C]49.7885[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 40 )[/C][C]1047740[/C][C]20975.9[/C][C]49.9495[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 40 )[/C][C]1047940[/C][C]20877.1[/C][C]50.1959[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 40 )[/C][C]1052300[/C][C]19969.6[/C][C]52.6952[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 40 )[/C][C]1052040[/C][C]19944[/C][C]52.7496[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 40 )[/C][C]1052630[/C][C]19839.6[/C][C]53.057[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 40 )[/C][C]1054030[/C][C]19597.7[/C][C]53.7833[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 40 )[/C][C]1054030[/C][C]19498.4[/C][C]54.0575[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 40 )[/C][C]1055290[/C][C]19287.7[/C][C]54.7131[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 40 )[/C][C]1054810[/C][C]19241.1[/C][C]54.8204[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 40 )[/C][C]1055290[/C][C]19160.7[/C][C]55.0759[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 40 )[/C][C]1056890[/C][C]18899.3[/C][C]55.9222[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 40 )[/C][C]1056340[/C][C]18846.7[/C][C]56.049[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 40 )[/C][C]1057590[/C][C]18646[/C][C]56.7194[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 40 )[/C][C]1061500[/C][C]18032[/C][C]58.8674[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 40 )[/C][C]1063550[/C][C]17550.3[/C][C]60.6003[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 40 )[/C][C]1067210[/C][C]17007.7[/C][C]62.7487[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 40 )[/C][C]1068770[/C][C]16781.4[/C][C]63.6878[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 40 )[/C][C]1071960[/C][C]16327.9[/C][C]65.652[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 40 )[/C][C]1073670[/C][C]16088.7[/C][C]66.7347[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 40 )[/C][C]1073590[/C][C]15879.5[/C][C]67.6085[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 40 )[/C][C]1075460[/C][C]15416[/C][C]69.7628[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 40 )[/C][C]1075460[/C][C]15201.8[/C][C]70.7457[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 40 )[/C][C]1076420[/C][C]14608.1[/C][C]73.6869[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 40 )[/C][C]1076420[/C][C]14608.1[/C][C]73.6869[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 40 )[/C][C]1076520[/C][C]14360.3[/C][C]74.9654[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 40 )[/C][C]1080810[/C][C]13532.2[/C][C]79.8693[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 40 )[/C][C]1084380[/C][C]12830.4[/C][C]84.5162[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 40 )[/C][C]1083120[/C][C]12465.5[/C][C]86.8899[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 40 )[/C][C]1083120[/C][C]12465.5[/C][C]86.8899[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 40 )[/C][C]1081890[/C][C]12354.7[/C][C]87.5691[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 40 )[/C][C]1094860[/C][C]10752.7[/C][C]101.822[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 40 )[/C][C]1094860[/C][C]10752.7[/C][C]101.822[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 40 )[/C][C]1097650[/C][C]10420.5[/C][C]105.336[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 40 )[/C][C]1094790[/C][C]10158.7[/C][C]107.768[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 40 )[/C][C]1096330[/C][C]9679.83[/C][C]113.259[/C][/ROW]
[ROW][C]Winsorized Mean ( 39 / 40 )[/C][C]1103850[/C][C]8506.84[/C][C]129.76[/C][/ROW]
[ROW][C]Winsorized Mean ( 40 / 40 )[/C][C]1111400[/C][C]7654.86[/C][C]145.189[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 40 )[/C][C]1050000[/C][C]21016.8[/C][C]49.9602[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 40 )[/C][C]1052590[/C][C]20604.8[/C][C]51.0845[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 40 )[/C][C]1054820[/C][C]20269.4[/C][C]52.0398[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 40 )[/C][C]1057450[/C][C]19948.2[/C][C]53.0099[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 40 )[/C][C]1060100[/C][C]19607.2[/C][C]54.0669[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 40 )[/C][C]1062800[/C][C]19250[/C][C]55.2104[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 40 )[/C][C]1064780[/C][C]19062.1[/C][C]55.8589[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 40 )[/C][C]1066890[/C][C]18852.6[/C][C]56.5908[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 40 )[/C][C]1068980[/C][C]18633.9[/C][C]57.3675[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 40 )[/C][C]1070980[/C][C]18427.6[/C][C]58.1182[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 40 )[/C][C]1073050[/C][C]18207[/C][C]58.9361[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 40 )[/C][C]1075070[/C][C]17987.8[/C][C]59.7664[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 40 )[/C][C]1077220[/C][C]17741.7[/C][C]60.7172[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 40 )[/C][C]1079430[/C][C]17470.2[/C][C]61.7867[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 40 )[/C][C]1081570[/C][C]17196.1[/C][C]62.8961[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 40 )[/C][C]1083860[/C][C]16885.3[/C][C]64.19[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 40 )[/C][C]1086160[/C][C]16554.5[/C][C]65.6109[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 40 )[/C][C]1088230[/C][C]16260.3[/C][C]66.9255[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 40 )[/C][C]1090230[/C][C]15984.4[/C][C]68.2061[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 40 )[/C][C]1092050[/C][C]15737.9[/C][C]69.39[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 40 )[/C][C]1093840[/C][C]15479[/C][C]70.6663[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 40 )[/C][C]1095490[/C][C]15236.9[/C][C]71.8971[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 40 )[/C][C]1097100[/C][C]14982.9[/C][C]73.2233[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 40 )[/C][C]1098800[/C][C]14707.3[/C][C]74.711[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 40 )[/C][C]1100470[/C][C]14442.8[/C][C]76.195[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 40 )[/C][C]1102230[/C][C]14152.9[/C][C]77.8801[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 40 )[/C][C]1104040[/C][C]13886[/C][C]79.5073[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 40 )[/C][C]1105950[/C][C]13559.7[/C][C]81.5616[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 40 )[/C][C]1107990[/C][C]13197.1[/C][C]83.9569[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 40 )[/C][C]1109860[/C][C]12887.6[/C][C]86.1185[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 40 )[/C][C]1111620[/C][C]12618.8[/C][C]88.0927[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 40 )[/C][C]1113590[/C][C]12332.9[/C][C]90.2945[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 40 )[/C][C]1115710[/C][C]11969.6[/C][C]93.2118[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 40 )[/C][C]1118070[/C][C]11520.3[/C][C]97.0522[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 40 )[/C][C]1119710[/C][C]11279.8[/C][C]99.2668[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 40 )[/C][C]1121480[/C][C]10963.9[/C][C]102.289[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 40 )[/C][C]1123210[/C][C]10623.5[/C][C]105.729[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 40 )[/C][C]1125310[/C][C]10211.6[/C][C]110.199[/C][/ROW]
[ROW][C]Trimmed Mean ( 39 / 40 )[/C][C]1127480[/C][C]9771.48[/C][C]115.385[/C][/ROW]
[ROW][C]Trimmed Mean ( 40 / 40 )[/C][C]1129300[/C][C]9483.03[/C][C]119.087[/C][/ROW]
[ROW][C]Median[/C][C]1155370[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]861276[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]1105970[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]1109860[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]1105970[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]1109860[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]1109860[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]1105970[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]1109860[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]1107990[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]120[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307401&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307401&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 Mean104686021604.748.4552
Geometric Mean1014120
Harmonic Mean973625
Quadratic Mean1073060
Winsorized Mean ( 1 / 40 )104751021386.348.9804
Winsorized Mean ( 2 / 40 )104835021174.349.5106
Winsorized Mean ( 3 / 40 )104744021037.849.7885
Winsorized Mean ( 4 / 40 )104774020975.949.9495
Winsorized Mean ( 5 / 40 )104794020877.150.1959
Winsorized Mean ( 6 / 40 )105230019969.652.6952
Winsorized Mean ( 7 / 40 )10520401994452.7496
Winsorized Mean ( 8 / 40 )105263019839.653.057
Winsorized Mean ( 9 / 40 )105403019597.753.7833
Winsorized Mean ( 10 / 40 )105403019498.454.0575
Winsorized Mean ( 11 / 40 )105529019287.754.7131
Winsorized Mean ( 12 / 40 )105481019241.154.8204
Winsorized Mean ( 13 / 40 )105529019160.755.0759
Winsorized Mean ( 14 / 40 )105689018899.355.9222
Winsorized Mean ( 15 / 40 )105634018846.756.049
Winsorized Mean ( 16 / 40 )10575901864656.7194
Winsorized Mean ( 17 / 40 )10615001803258.8674
Winsorized Mean ( 18 / 40 )106355017550.360.6003
Winsorized Mean ( 19 / 40 )106721017007.762.7487
Winsorized Mean ( 20 / 40 )106877016781.463.6878
Winsorized Mean ( 21 / 40 )107196016327.965.652
Winsorized Mean ( 22 / 40 )107367016088.766.7347
Winsorized Mean ( 23 / 40 )107359015879.567.6085
Winsorized Mean ( 24 / 40 )10754601541669.7628
Winsorized Mean ( 25 / 40 )107546015201.870.7457
Winsorized Mean ( 26 / 40 )107642014608.173.6869
Winsorized Mean ( 27 / 40 )107642014608.173.6869
Winsorized Mean ( 28 / 40 )107652014360.374.9654
Winsorized Mean ( 29 / 40 )108081013532.279.8693
Winsorized Mean ( 30 / 40 )108438012830.484.5162
Winsorized Mean ( 31 / 40 )108312012465.586.8899
Winsorized Mean ( 32 / 40 )108312012465.586.8899
Winsorized Mean ( 33 / 40 )108189012354.787.5691
Winsorized Mean ( 34 / 40 )109486010752.7101.822
Winsorized Mean ( 35 / 40 )109486010752.7101.822
Winsorized Mean ( 36 / 40 )109765010420.5105.336
Winsorized Mean ( 37 / 40 )109479010158.7107.768
Winsorized Mean ( 38 / 40 )10963309679.83113.259
Winsorized Mean ( 39 / 40 )11038508506.84129.76
Winsorized Mean ( 40 / 40 )11114007654.86145.189
Trimmed Mean ( 1 / 40 )105000021016.849.9602
Trimmed Mean ( 2 / 40 )105259020604.851.0845
Trimmed Mean ( 3 / 40 )105482020269.452.0398
Trimmed Mean ( 4 / 40 )105745019948.253.0099
Trimmed Mean ( 5 / 40 )106010019607.254.0669
Trimmed Mean ( 6 / 40 )10628001925055.2104
Trimmed Mean ( 7 / 40 )106478019062.155.8589
Trimmed Mean ( 8 / 40 )106689018852.656.5908
Trimmed Mean ( 9 / 40 )106898018633.957.3675
Trimmed Mean ( 10 / 40 )107098018427.658.1182
Trimmed Mean ( 11 / 40 )10730501820758.9361
Trimmed Mean ( 12 / 40 )107507017987.859.7664
Trimmed Mean ( 13 / 40 )107722017741.760.7172
Trimmed Mean ( 14 / 40 )107943017470.261.7867
Trimmed Mean ( 15 / 40 )108157017196.162.8961
Trimmed Mean ( 16 / 40 )108386016885.364.19
Trimmed Mean ( 17 / 40 )108616016554.565.6109
Trimmed Mean ( 18 / 40 )108823016260.366.9255
Trimmed Mean ( 19 / 40 )109023015984.468.2061
Trimmed Mean ( 20 / 40 )109205015737.969.39
Trimmed Mean ( 21 / 40 )10938401547970.6663
Trimmed Mean ( 22 / 40 )109549015236.971.8971
Trimmed Mean ( 23 / 40 )109710014982.973.2233
Trimmed Mean ( 24 / 40 )109880014707.374.711
Trimmed Mean ( 25 / 40 )110047014442.876.195
Trimmed Mean ( 26 / 40 )110223014152.977.8801
Trimmed Mean ( 27 / 40 )11040401388679.5073
Trimmed Mean ( 28 / 40 )110595013559.781.5616
Trimmed Mean ( 29 / 40 )110799013197.183.9569
Trimmed Mean ( 30 / 40 )110986012887.686.1185
Trimmed Mean ( 31 / 40 )111162012618.888.0927
Trimmed Mean ( 32 / 40 )111359012332.990.2945
Trimmed Mean ( 33 / 40 )111571011969.693.2118
Trimmed Mean ( 34 / 40 )111807011520.397.0522
Trimmed Mean ( 35 / 40 )111971011279.899.2668
Trimmed Mean ( 36 / 40 )112148010963.9102.289
Trimmed Mean ( 37 / 40 )112321010623.5105.729
Trimmed Mean ( 38 / 40 )112531010211.6110.199
Trimmed Mean ( 39 / 40 )11274809771.48115.385
Trimmed Mean ( 40 / 40 )11293009483.03119.087
Median1155370
Midrange861276
Midmean - Weighted Average at Xnp1105970
Midmean - Weighted Average at X(n+1)p1109860
Midmean - Empirical Distribution Function1105970
Midmean - Empirical Distribution Function - Averaging1109860
Midmean - Empirical Distribution Function - Interpolation1109860
Midmean - Closest Observation1105970
Midmean - True Basic - Statistics Graphics Toolkit1109860
Midmean - MS Excel (old versions)1107990
Number of observations120



Parameters (Session):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;
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')