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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 computationMon, 10 Aug 2015 09:27:53 +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/2015/Aug/10/t143919651195cwo02xv4knaba.htm/, Retrieved Sun, 19 May 2024 11:15:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279970, Retrieved Sun, 19 May 2024 11:15:20 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [omzetontwikkeling...] [2014-09-24 09:10:11] [3d50c3f1d1505d45371c80c331b9aa00]
- R  D  [Histogram] [] [2015-07-23 12:50:11] [74be16979710d4c4e7c6647856088456]
- RMPD    [Harrell-Davis Quantiles] [] [2015-08-10 08:16:05] [74be16979710d4c4e7c6647856088456]
- RMP         [Central Tendency] [] [2015-08-10 08:27:53] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
1053000
1014000
1072500
858000
1111500
1092000
1170000
1209000
1345500
1170000
1111500
1384500
1170000
877500
1033500
780000
1092000
897000
1189500
1072500
1131000
1267500
1248000
1482000
1072500
897000
994500
721500
1033500
799500
1131000
1072500
955500
1365000
1228500
1404000
1053000
975000
877500
721500
955500
858000
1170000
1131000
975000
1306500
1209000
1560000
1248000
760500
760500
760500
897000
897000
1209000
1111500
994500
1248000
1150500
1657500
1306500
760500
799500
663000
916500
1053000
1326000
1306500
1053000
1228500
1092000
1560000
1189500
955500
858000
643500
955500
1150500
1345500
1267500
936000
1345500
1053000
1618500
1345500
975000
897000
604500
955500
916500
1384500
1384500
1053000
1365000
1014000
1579500
1345500
994500
760500
526500
1033500
994500
1306500
1501500
1111500
1248000
936000
1618500




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279970&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279970&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279970&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean1094708.3333333322829.351856865547.9517920700022
Geometric Mean1068405.49586893
Harmonic Mean1040961.74302124
Quadratic Mean1119889.51277942
Winsorized Mean ( 1 / 36 )1095069.4444444422591.303018276248.4730537038321
Winsorized Mean ( 2 / 36 )1095791.6666666722450.009005241248.8102996489152
Winsorized Mean ( 3 / 36 )109525022120.80521510249.5122121165944
Winsorized Mean ( 4 / 36 )1096694.4444444421600.558979013450.7715770462221
Winsorized Mean ( 5 / 36 )1096694.4444444421600.558979013450.7715770462221
Winsorized Mean ( 6 / 36 )1095611.1111111120634.927866784153.094981391949
Winsorized Mean ( 7 / 36 )1094347.2222222220406.540560402753.6272779299848
Winsorized Mean ( 8 / 36 )1088569.4444444419454.096171171755.9557963971389
Winsorized Mean ( 9 / 36 )1086944.4444444419213.34144097156.5723795511497
Winsorized Mean ( 10 / 36 )1086944.4444444419213.34144097156.5723795511497
Winsorized Mean ( 11 / 36 )1088930.5555555618903.935952427557.6033773228968
Winsorized Mean ( 12 / 36 )1088930.5555555618266.559766645659.6133354866265
Winsorized Mean ( 13 / 36 )1088930.5555555618266.559766645659.6133354866265
Winsorized Mean ( 14 / 36 )1093986.1111111116851.292377475464.9200124598993
Winsorized Mean ( 15 / 36 )1093986.1111111116851.292377475464.9200124598993
Winsorized Mean ( 16 / 36 )1093986.1111111116851.292377475464.9200124598993
Winsorized Mean ( 17 / 36 )1097055.5555555616458.985565284366.6538986381696
Winsorized Mean ( 18 / 36 )1097055.5555555616458.985565284366.6538986381696
Winsorized Mean ( 19 / 36 )1097055.5555555615560.824189352770.5011214191471
Winsorized Mean ( 20 / 36 )1093444.4444444415073.895421551772.538943243636
Winsorized Mean ( 21 / 36 )1093444.4444444415073.895421551772.538943243636
Winsorized Mean ( 22 / 36 )1093444.4444444415073.895421551772.538943243636
Winsorized Mean ( 23 / 36 )1093444.4444444415073.895421551772.538943243636
Winsorized Mean ( 24 / 36 )1089111.1111111113437.647394014581.0492401814493
Winsorized Mean ( 25 / 36 )1089111.1111111113437.647394014581.0492401814493
Winsorized Mean ( 26 / 36 )1089111.1111111112307.817079211788.4893807002259
Winsorized Mean ( 27 / 36 )1089111.1111111112307.817079211788.4893807002259
Winsorized Mean ( 28 / 36 )1094166.6666666711734.410572540293.2442801368428
Winsorized Mean ( 29 / 36 )1094166.6666666711734.410572540293.2442801368428
Winsorized Mean ( 30 / 36 )108875011083.063965058798.2354702122514
Winsorized Mean ( 31 / 36 )108875011083.063965058798.2354702122514
Winsorized Mean ( 32 / 36 )1082972.2222222210415.5104931229103.976874003179
Winsorized Mean ( 33 / 36 )1088930.555555569748.85935214658111.698252710537
Winsorized Mean ( 34 / 36 )1088930.555555569748.85935214658111.698252710537
Winsorized Mean ( 35 / 36 )1082611.111111119035.26688327541119.820601327788
Winsorized Mean ( 36 / 36 )1089111.111111118327.75600830386130.780862218481
Trimmed Mean ( 1 / 36 )1094759.4339622621992.305718876549.7792022335615
Trimmed Mean ( 2 / 36 )1094437.521318.741434406751.3368719897165
Trimmed Mean ( 3 / 36 )1093720.5882352920643.982735328552.9801154291603
Trimmed Mean ( 4 / 36 )109317020022.49394147454.5970948072377
Trimmed Mean ( 5 / 36 )1092198.9795918419494.860516714856.024970204603
Trimmed Mean ( 6 / 36 )1091187.518896.061576214957.7468217701785
Trimmed Mean ( 7 / 36 )1090340.4255319118458.742900700159.0690509856206
Trimmed Mean ( 8 / 36 )1089668.4782608718012.796516380660.4941313399025
Trimmed Mean ( 9 / 36 )1089833.3333333317699.205071832561.5752701271174
Trimmed Mean ( 10 / 36 )1090227.2727272717384.959067981262.7109484965771
Trimmed Mean ( 11 / 36 )1090639.5348837217024.139237241964.0642983286839
Trimmed Mean ( 12 / 36 )1090839.2857142916662.677005368865.4660283796421
Trimmed Mean ( 13 / 36 )1091048.780487816350.631958546766.7282330893331
Trimmed Mean ( 14 / 36 )1091268.7515988.719678018268.2524162019245
Trimmed Mean ( 15 / 36 )109100015785.493916308769.1140870082526
Trimmed Mean ( 16 / 36 )1090717.1052631615545.748376647270.161762485596
Trimmed Mean ( 17 / 36 )1090418.9189189215262.982308062571.4420613816027
Trimmed Mean ( 18 / 36 )1089833.3333333314985.758758608372.7246014625251
Trimmed Mean ( 19 / 36 )1089214.2857142914656.447261108674.3163923909824
Trimmed Mean ( 20 / 36 )1088558.8235294114398.202080731175.6038022959975
Trimmed Mean ( 21 / 36 )1088159.0909090914161.016941817676.8418748017838
Trimmed Mean ( 22 / 36 )1087734.37513873.6010696878.4031751768607
Trimmed Mean ( 23 / 36 )1087282.2580645213524.912971407880.3910724130407
Trimmed Mean ( 24 / 36 )108680013100.417253026382.9591896967204
Trimmed Mean ( 25 / 36 )1086620.6896551712849.843111463984.5629538220395
Trimmed Mean ( 26 / 36 )1086428.5714285712538.527822790686.6472194170857
Trimmed Mean ( 27 / 36 )1086222.2222222212335.35641707188.0576276433317
Trimmed Mean ( 28 / 36 )108600012076.045807835589.930099411792
Trimmed Mean ( 29 / 36 )108537011839.90838698791.6704728216401
Trimmed Mean ( 30 / 36 )1084687.511533.798477250794.0442562907132
Trimmed Mean ( 31 / 36 )1084369.5652173911266.131052170896.2503951175366
Trimmed Mean ( 32 / 36 )1084022.7272727310913.604047948499.3276577114332
Trimmed Mean ( 33 / 36 )1084107.1428571410592.5561665898102.346131170543
Trimmed Mean ( 34 / 36 )1083712.510306.3163278642105.150323891192
Trimmed Mean ( 35 / 36 )1083276.315789479913.59716434917109.271770663136
Trimmed Mean ( 36 / 36 )1083333.333333339560.72903509663113.310745378988
Median1072500
Midrange1092000
Midmean - Weighted Average at Xnp1086428.57142857
Midmean - Weighted Average at X(n+1)p1086428.57142857
Midmean - Empirical Distribution Function1086428.57142857
Midmean - Empirical Distribution Function - Averaging1086428.57142857
Midmean - Empirical Distribution Function - Interpolation1086428.57142857
Midmean - Closest Observation1086428.57142857
Midmean - True Basic - Statistics Graphics Toolkit1086428.57142857
Midmean - MS Excel (old versions)1086428.57142857
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 1094708.33333333 & 22829.3518568655 & 47.9517920700022 \tabularnewline
Geometric Mean & 1068405.49586893 &  &  \tabularnewline
Harmonic Mean & 1040961.74302124 &  &  \tabularnewline
Quadratic Mean & 1119889.51277942 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 1095069.44444444 & 22591.3030182762 & 48.4730537038321 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 1095791.66666667 & 22450.0090052412 & 48.8102996489152 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 1095250 & 22120.805215102 & 49.5122121165944 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 1096694.44444444 & 21600.5589790134 & 50.7715770462221 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 1096694.44444444 & 21600.5589790134 & 50.7715770462221 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 1095611.11111111 & 20634.9278667841 & 53.094981391949 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 1094347.22222222 & 20406.5405604027 & 53.6272779299848 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 1088569.44444444 & 19454.0961711717 & 55.9557963971389 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 1086944.44444444 & 19213.341440971 & 56.5723795511497 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 1086944.44444444 & 19213.341440971 & 56.5723795511497 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 1088930.55555556 & 18903.9359524275 & 57.6033773228968 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 1088930.55555556 & 18266.5597666456 & 59.6133354866265 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 1088930.55555556 & 18266.5597666456 & 59.6133354866265 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 1093986.11111111 & 16851.2923774754 & 64.9200124598993 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 1093986.11111111 & 16851.2923774754 & 64.9200124598993 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 1093986.11111111 & 16851.2923774754 & 64.9200124598993 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 1097055.55555556 & 16458.9855652843 & 66.6538986381696 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 1097055.55555556 & 16458.9855652843 & 66.6538986381696 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 1097055.55555556 & 15560.8241893527 & 70.5011214191471 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 1093444.44444444 & 15073.8954215517 & 72.538943243636 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 1093444.44444444 & 15073.8954215517 & 72.538943243636 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 1093444.44444444 & 15073.8954215517 & 72.538943243636 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 1093444.44444444 & 15073.8954215517 & 72.538943243636 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 1089111.11111111 & 13437.6473940145 & 81.0492401814493 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 1089111.11111111 & 13437.6473940145 & 81.0492401814493 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 1089111.11111111 & 12307.8170792117 & 88.4893807002259 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 1089111.11111111 & 12307.8170792117 & 88.4893807002259 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 1094166.66666667 & 11734.4105725402 & 93.2442801368428 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 1094166.66666667 & 11734.4105725402 & 93.2442801368428 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 1088750 & 11083.0639650587 & 98.2354702122514 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 1088750 & 11083.0639650587 & 98.2354702122514 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 1082972.22222222 & 10415.5104931229 & 103.976874003179 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 1088930.55555556 & 9748.85935214658 & 111.698252710537 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 1088930.55555556 & 9748.85935214658 & 111.698252710537 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 1082611.11111111 & 9035.26688327541 & 119.820601327788 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 1089111.11111111 & 8327.75600830386 & 130.780862218481 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 1094759.43396226 & 21992.3057188765 & 49.7792022335615 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 1094437.5 & 21318.7414344067 & 51.3368719897165 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 1093720.58823529 & 20643.9827353285 & 52.9801154291603 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 1093170 & 20022.493941474 & 54.5970948072377 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 1092198.97959184 & 19494.8605167148 & 56.024970204603 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 1091187.5 & 18896.0615762149 & 57.7468217701785 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 1090340.42553191 & 18458.7429007001 & 59.0690509856206 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 1089668.47826087 & 18012.7965163806 & 60.4941313399025 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 1089833.33333333 & 17699.2050718325 & 61.5752701271174 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 1090227.27272727 & 17384.9590679812 & 62.7109484965771 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 1090639.53488372 & 17024.1392372419 & 64.0642983286839 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 1090839.28571429 & 16662.6770053688 & 65.4660283796421 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 1091048.7804878 & 16350.6319585467 & 66.7282330893331 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 1091268.75 & 15988.7196780182 & 68.2524162019245 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 1091000 & 15785.4939163087 & 69.1140870082526 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 1090717.10526316 & 15545.7483766472 & 70.161762485596 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 1090418.91891892 & 15262.9823080625 & 71.4420613816027 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 1089833.33333333 & 14985.7587586083 & 72.7246014625251 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 1089214.28571429 & 14656.4472611086 & 74.3163923909824 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 1088558.82352941 & 14398.2020807311 & 75.6038022959975 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 1088159.09090909 & 14161.0169418176 & 76.8418748017838 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 1087734.375 & 13873.60106968 & 78.4031751768607 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 1087282.25806452 & 13524.9129714078 & 80.3910724130407 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 1086800 & 13100.4172530263 & 82.9591896967204 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 1086620.68965517 & 12849.8431114639 & 84.5629538220395 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 1086428.57142857 & 12538.5278227906 & 86.6472194170857 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 1086222.22222222 & 12335.356417071 & 88.0576276433317 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 1086000 & 12076.0458078355 & 89.930099411792 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 1085370 & 11839.908386987 & 91.6704728216401 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 1084687.5 & 11533.7984772507 & 94.0442562907132 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 1084369.56521739 & 11266.1310521708 & 96.2503951175366 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 1084022.72727273 & 10913.6040479484 & 99.3276577114332 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 1084107.14285714 & 10592.5561665898 & 102.346131170543 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 1083712.5 & 10306.3163278642 & 105.150323891192 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 1083276.31578947 & 9913.59716434917 & 109.271770663136 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 1083333.33333333 & 9560.72903509663 & 113.310745378988 \tabularnewline
Median & 1072500 &  &  \tabularnewline
Midrange & 1092000 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 1086428.57142857 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 1086428.57142857 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 1086428.57142857 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 1086428.57142857 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 1086428.57142857 &  &  \tabularnewline
Midmean - Closest Observation & 1086428.57142857 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 1086428.57142857 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 1086428.57142857 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279970&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]1094708.33333333[/C][C]22829.3518568655[/C][C]47.9517920700022[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]1068405.49586893[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]1040961.74302124[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]1119889.51277942[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]1095069.44444444[/C][C]22591.3030182762[/C][C]48.4730537038321[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]1095791.66666667[/C][C]22450.0090052412[/C][C]48.8102996489152[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]1095250[/C][C]22120.805215102[/C][C]49.5122121165944[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]1096694.44444444[/C][C]21600.5589790134[/C][C]50.7715770462221[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]1096694.44444444[/C][C]21600.5589790134[/C][C]50.7715770462221[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]1095611.11111111[/C][C]20634.9278667841[/C][C]53.094981391949[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]1094347.22222222[/C][C]20406.5405604027[/C][C]53.6272779299848[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]1088569.44444444[/C][C]19454.0961711717[/C][C]55.9557963971389[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]1086944.44444444[/C][C]19213.341440971[/C][C]56.5723795511497[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]1086944.44444444[/C][C]19213.341440971[/C][C]56.5723795511497[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]1088930.55555556[/C][C]18903.9359524275[/C][C]57.6033773228968[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]1088930.55555556[/C][C]18266.5597666456[/C][C]59.6133354866265[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]1088930.55555556[/C][C]18266.5597666456[/C][C]59.6133354866265[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]1093986.11111111[/C][C]16851.2923774754[/C][C]64.9200124598993[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]1093986.11111111[/C][C]16851.2923774754[/C][C]64.9200124598993[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]1093986.11111111[/C][C]16851.2923774754[/C][C]64.9200124598993[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]1097055.55555556[/C][C]16458.9855652843[/C][C]66.6538986381696[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]1097055.55555556[/C][C]16458.9855652843[/C][C]66.6538986381696[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]1097055.55555556[/C][C]15560.8241893527[/C][C]70.5011214191471[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]1093444.44444444[/C][C]15073.8954215517[/C][C]72.538943243636[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]1093444.44444444[/C][C]15073.8954215517[/C][C]72.538943243636[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]1093444.44444444[/C][C]15073.8954215517[/C][C]72.538943243636[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]1093444.44444444[/C][C]15073.8954215517[/C][C]72.538943243636[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]1089111.11111111[/C][C]13437.6473940145[/C][C]81.0492401814493[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]1089111.11111111[/C][C]13437.6473940145[/C][C]81.0492401814493[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]1089111.11111111[/C][C]12307.8170792117[/C][C]88.4893807002259[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]1089111.11111111[/C][C]12307.8170792117[/C][C]88.4893807002259[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]1094166.66666667[/C][C]11734.4105725402[/C][C]93.2442801368428[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]1094166.66666667[/C][C]11734.4105725402[/C][C]93.2442801368428[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]1088750[/C][C]11083.0639650587[/C][C]98.2354702122514[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]1088750[/C][C]11083.0639650587[/C][C]98.2354702122514[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]1082972.22222222[/C][C]10415.5104931229[/C][C]103.976874003179[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]1088930.55555556[/C][C]9748.85935214658[/C][C]111.698252710537[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]1088930.55555556[/C][C]9748.85935214658[/C][C]111.698252710537[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]1082611.11111111[/C][C]9035.26688327541[/C][C]119.820601327788[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]1089111.11111111[/C][C]8327.75600830386[/C][C]130.780862218481[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]1094759.43396226[/C][C]21992.3057188765[/C][C]49.7792022335615[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]1094437.5[/C][C]21318.7414344067[/C][C]51.3368719897165[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]1093720.58823529[/C][C]20643.9827353285[/C][C]52.9801154291603[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]1093170[/C][C]20022.493941474[/C][C]54.5970948072377[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]1092198.97959184[/C][C]19494.8605167148[/C][C]56.024970204603[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]1091187.5[/C][C]18896.0615762149[/C][C]57.7468217701785[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]1090340.42553191[/C][C]18458.7429007001[/C][C]59.0690509856206[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]1089668.47826087[/C][C]18012.7965163806[/C][C]60.4941313399025[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]1089833.33333333[/C][C]17699.2050718325[/C][C]61.5752701271174[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]1090227.27272727[/C][C]17384.9590679812[/C][C]62.7109484965771[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]1090639.53488372[/C][C]17024.1392372419[/C][C]64.0642983286839[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]1090839.28571429[/C][C]16662.6770053688[/C][C]65.4660283796421[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]1091048.7804878[/C][C]16350.6319585467[/C][C]66.7282330893331[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]1091268.75[/C][C]15988.7196780182[/C][C]68.2524162019245[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]1091000[/C][C]15785.4939163087[/C][C]69.1140870082526[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]1090717.10526316[/C][C]15545.7483766472[/C][C]70.161762485596[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]1090418.91891892[/C][C]15262.9823080625[/C][C]71.4420613816027[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]1089833.33333333[/C][C]14985.7587586083[/C][C]72.7246014625251[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]1089214.28571429[/C][C]14656.4472611086[/C][C]74.3163923909824[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]1088558.82352941[/C][C]14398.2020807311[/C][C]75.6038022959975[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]1088159.09090909[/C][C]14161.0169418176[/C][C]76.8418748017838[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]1087734.375[/C][C]13873.60106968[/C][C]78.4031751768607[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]1087282.25806452[/C][C]13524.9129714078[/C][C]80.3910724130407[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]1086800[/C][C]13100.4172530263[/C][C]82.9591896967204[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]1086620.68965517[/C][C]12849.8431114639[/C][C]84.5629538220395[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]1086428.57142857[/C][C]12538.5278227906[/C][C]86.6472194170857[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]1086222.22222222[/C][C]12335.356417071[/C][C]88.0576276433317[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]1086000[/C][C]12076.0458078355[/C][C]89.930099411792[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]1085370[/C][C]11839.908386987[/C][C]91.6704728216401[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]1084687.5[/C][C]11533.7984772507[/C][C]94.0442562907132[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]1084369.56521739[/C][C]11266.1310521708[/C][C]96.2503951175366[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]1084022.72727273[/C][C]10913.6040479484[/C][C]99.3276577114332[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]1084107.14285714[/C][C]10592.5561665898[/C][C]102.346131170543[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]1083712.5[/C][C]10306.3163278642[/C][C]105.150323891192[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]1083276.31578947[/C][C]9913.59716434917[/C][C]109.271770663136[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]1083333.33333333[/C][C]9560.72903509663[/C][C]113.310745378988[/C][/ROW]
[ROW][C]Median[/C][C]1072500[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]1092000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]1086428.57142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]1086428.57142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]1086428.57142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]1086428.57142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]1086428.57142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]1086428.57142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]1086428.57142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]1086428.57142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]108[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279970&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279970&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 Mean1094708.3333333322829.351856865547.9517920700022
Geometric Mean1068405.49586893
Harmonic Mean1040961.74302124
Quadratic Mean1119889.51277942
Winsorized Mean ( 1 / 36 )1095069.4444444422591.303018276248.4730537038321
Winsorized Mean ( 2 / 36 )1095791.6666666722450.009005241248.8102996489152
Winsorized Mean ( 3 / 36 )109525022120.80521510249.5122121165944
Winsorized Mean ( 4 / 36 )1096694.4444444421600.558979013450.7715770462221
Winsorized Mean ( 5 / 36 )1096694.4444444421600.558979013450.7715770462221
Winsorized Mean ( 6 / 36 )1095611.1111111120634.927866784153.094981391949
Winsorized Mean ( 7 / 36 )1094347.2222222220406.540560402753.6272779299848
Winsorized Mean ( 8 / 36 )1088569.4444444419454.096171171755.9557963971389
Winsorized Mean ( 9 / 36 )1086944.4444444419213.34144097156.5723795511497
Winsorized Mean ( 10 / 36 )1086944.4444444419213.34144097156.5723795511497
Winsorized Mean ( 11 / 36 )1088930.5555555618903.935952427557.6033773228968
Winsorized Mean ( 12 / 36 )1088930.5555555618266.559766645659.6133354866265
Winsorized Mean ( 13 / 36 )1088930.5555555618266.559766645659.6133354866265
Winsorized Mean ( 14 / 36 )1093986.1111111116851.292377475464.9200124598993
Winsorized Mean ( 15 / 36 )1093986.1111111116851.292377475464.9200124598993
Winsorized Mean ( 16 / 36 )1093986.1111111116851.292377475464.9200124598993
Winsorized Mean ( 17 / 36 )1097055.5555555616458.985565284366.6538986381696
Winsorized Mean ( 18 / 36 )1097055.5555555616458.985565284366.6538986381696
Winsorized Mean ( 19 / 36 )1097055.5555555615560.824189352770.5011214191471
Winsorized Mean ( 20 / 36 )1093444.4444444415073.895421551772.538943243636
Winsorized Mean ( 21 / 36 )1093444.4444444415073.895421551772.538943243636
Winsorized Mean ( 22 / 36 )1093444.4444444415073.895421551772.538943243636
Winsorized Mean ( 23 / 36 )1093444.4444444415073.895421551772.538943243636
Winsorized Mean ( 24 / 36 )1089111.1111111113437.647394014581.0492401814493
Winsorized Mean ( 25 / 36 )1089111.1111111113437.647394014581.0492401814493
Winsorized Mean ( 26 / 36 )1089111.1111111112307.817079211788.4893807002259
Winsorized Mean ( 27 / 36 )1089111.1111111112307.817079211788.4893807002259
Winsorized Mean ( 28 / 36 )1094166.6666666711734.410572540293.2442801368428
Winsorized Mean ( 29 / 36 )1094166.6666666711734.410572540293.2442801368428
Winsorized Mean ( 30 / 36 )108875011083.063965058798.2354702122514
Winsorized Mean ( 31 / 36 )108875011083.063965058798.2354702122514
Winsorized Mean ( 32 / 36 )1082972.2222222210415.5104931229103.976874003179
Winsorized Mean ( 33 / 36 )1088930.555555569748.85935214658111.698252710537
Winsorized Mean ( 34 / 36 )1088930.555555569748.85935214658111.698252710537
Winsorized Mean ( 35 / 36 )1082611.111111119035.26688327541119.820601327788
Winsorized Mean ( 36 / 36 )1089111.111111118327.75600830386130.780862218481
Trimmed Mean ( 1 / 36 )1094759.4339622621992.305718876549.7792022335615
Trimmed Mean ( 2 / 36 )1094437.521318.741434406751.3368719897165
Trimmed Mean ( 3 / 36 )1093720.5882352920643.982735328552.9801154291603
Trimmed Mean ( 4 / 36 )109317020022.49394147454.5970948072377
Trimmed Mean ( 5 / 36 )1092198.9795918419494.860516714856.024970204603
Trimmed Mean ( 6 / 36 )1091187.518896.061576214957.7468217701785
Trimmed Mean ( 7 / 36 )1090340.4255319118458.742900700159.0690509856206
Trimmed Mean ( 8 / 36 )1089668.4782608718012.796516380660.4941313399025
Trimmed Mean ( 9 / 36 )1089833.3333333317699.205071832561.5752701271174
Trimmed Mean ( 10 / 36 )1090227.2727272717384.959067981262.7109484965771
Trimmed Mean ( 11 / 36 )1090639.5348837217024.139237241964.0642983286839
Trimmed Mean ( 12 / 36 )1090839.2857142916662.677005368865.4660283796421
Trimmed Mean ( 13 / 36 )1091048.780487816350.631958546766.7282330893331
Trimmed Mean ( 14 / 36 )1091268.7515988.719678018268.2524162019245
Trimmed Mean ( 15 / 36 )109100015785.493916308769.1140870082526
Trimmed Mean ( 16 / 36 )1090717.1052631615545.748376647270.161762485596
Trimmed Mean ( 17 / 36 )1090418.9189189215262.982308062571.4420613816027
Trimmed Mean ( 18 / 36 )1089833.3333333314985.758758608372.7246014625251
Trimmed Mean ( 19 / 36 )1089214.2857142914656.447261108674.3163923909824
Trimmed Mean ( 20 / 36 )1088558.8235294114398.202080731175.6038022959975
Trimmed Mean ( 21 / 36 )1088159.0909090914161.016941817676.8418748017838
Trimmed Mean ( 22 / 36 )1087734.37513873.6010696878.4031751768607
Trimmed Mean ( 23 / 36 )1087282.2580645213524.912971407880.3910724130407
Trimmed Mean ( 24 / 36 )108680013100.417253026382.9591896967204
Trimmed Mean ( 25 / 36 )1086620.6896551712849.843111463984.5629538220395
Trimmed Mean ( 26 / 36 )1086428.5714285712538.527822790686.6472194170857
Trimmed Mean ( 27 / 36 )1086222.2222222212335.35641707188.0576276433317
Trimmed Mean ( 28 / 36 )108600012076.045807835589.930099411792
Trimmed Mean ( 29 / 36 )108537011839.90838698791.6704728216401
Trimmed Mean ( 30 / 36 )1084687.511533.798477250794.0442562907132
Trimmed Mean ( 31 / 36 )1084369.5652173911266.131052170896.2503951175366
Trimmed Mean ( 32 / 36 )1084022.7272727310913.604047948499.3276577114332
Trimmed Mean ( 33 / 36 )1084107.1428571410592.5561665898102.346131170543
Trimmed Mean ( 34 / 36 )1083712.510306.3163278642105.150323891192
Trimmed Mean ( 35 / 36 )1083276.315789479913.59716434917109.271770663136
Trimmed Mean ( 36 / 36 )1083333.333333339560.72903509663113.310745378988
Median1072500
Midrange1092000
Midmean - Weighted Average at Xnp1086428.57142857
Midmean - Weighted Average at X(n+1)p1086428.57142857
Midmean - Empirical Distribution Function1086428.57142857
Midmean - Empirical Distribution Function - Averaging1086428.57142857
Midmean - Empirical Distribution Function - Interpolation1086428.57142857
Midmean - Closest Observation1086428.57142857
Midmean - True Basic - Statistics Graphics Toolkit1086428.57142857
Midmean - MS Excel (old versions)1086428.57142857
Number of observations108



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,hyperlink('arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE)
a<-table.element(a,arm)
a<-table.element(a,hyperlink('arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean'))
a<-table.element(a,armose)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE)
a<-table.element(a,geo)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE)
a<-table.element(a,har)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE)
a<-table.element(a,qua)
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,hyperlink('winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE)
a<-table.element(a,win[j,1])
a<-table.element(a,win[j,2])
a<-table.element(a,win[j,1]/win[j,2])
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,hyperlink('arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE)
a<-table.element(a,tri[j,1])
a<-table.element(a,tri[j,2])
a<-table.element(a,tri[j,1]/tri[j,2])
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,hyperlink('median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE)
a<-table.element(a,median(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE)
a<-table.element(a,midr)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_1.htm','Weighted Average at Xnp',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[2])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_3.htm','Empirical Distribution Function',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[3])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[4])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[5])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_6.htm','Closest Observation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[6])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[7])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_8.htm','MS Excel (old versions)',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[8])
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,length(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')