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Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSat, 08 Aug 2015 14:58:36 +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/08/t1439042597aooeraff1uel6kv.htm/, Retrieved Wed, 15 May 2024 23:24:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279937, Retrieved Wed, 15 May 2024 23:24:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords Reeks B Sebastiaan Lunders MAR204A Aantal verkochte exemplaren "Financial Times" Ottevaere
Estimated Impact166
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Datareeks - Aanta...] [2014-09-20 19:16:40] [ce8eed4eee7214d9613cef9db4d6a404]
- R PD  [Univariate Data Series] [Reeks B beschrijv...] [2015-08-08 13:11:55] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP     [Histogram] [Histogram & Frequ...] [2015-08-08 13:19:29] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP       [Kernel Density Estimation] [Dichtheidsgrafiek...] [2015-08-08 13:26:11] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMPD        [Notched Boxplots] [Notched Boxplots ...] [2015-08-08 13:32:37] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP           [Harrell-Davis Quantiles] [Decielen Reeks B ...] [2015-08-08 13:36:12] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- R P             [Harrell-Davis Quantiles] [Percentielen Reek...] [2015-08-08 13:40:38] [ae4fb4fa0c3c4ff80e7ff1f0f4c7f14a]
- RMP                 [Central Tendency] [Central tendency ...] [2015-08-08 13:58:36] [2cf7618d5ff65529ef2e27cea5366de0] [Current]
- RM                    [Mean versus Median] [Mean versus Media...] [2015-08-08 14:14:22] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP                     [Mean Plot] [Mean plot Reeks B...] [2015-08-08 14:23:08] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP                       [(Partial) Autocorrelation Function] [Autocorrelation R...] [2015-08-08 15:43:39] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP                         [Variability] [Variability Reeks...] [2015-08-09 13:39:05] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP                           [Standard Deviation-Mean Plot] [Standard Deviatio...] [2015-08-09 13:45:20] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP                             [Classical Decomposition] [Classic Decomposi...] [2015-08-09 14:52:17] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP                               [Exponential Smoothing] [Exponential Smoot...] [2015-08-09 15:17:07] [039d3b62ab99f9eeb4c9cc4c099c66fc]
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Dataseries X:
982800
946400
1001000
800800
1037400
1019200
1092000
1128400
1255800
1092000
1037400
1292200
1092000
819000
964600
728000
1019200
837200
1110200
1001000
1055600
1183000
1164800
1383200
1001000
837200
928200
673400
964600
746200
1055600
1001000
891800
1274000
1146600
1310400
982800
910000
819000
673400
891800
800800
1092000
1055600
910000
1219400
1128400
1456000
1164800
709800
709800
709800
837200
837200
1128400
1037400
928200
1164800
1073800
1547000
1219400
709800
746200
618800
855400
982800
1237600
1219400
982800
1146600
1019200
1456000
1110200
891800
800800
600600
891800
1073800
1255800
1183000
873600
1255800
982800
1510600
1255800
910000
837200
564200
891800
855400
1292200
1292200
982800
1274000
946400
1474200
1255800
928200
709800
491400
964600
928200
1219400
1401400
1037400
1164800
873600
1510600




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=279937&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=279937&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279937&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 Mean1021727.7777777821307.395066407847.9517920700022
Geometric Mean997178.462810999
Harmonic Mean971564.293486488
Quadratic Mean1045230.21192746
Winsorized Mean ( 1 / 36 )1022064.8148148121085.216150391148.473053703832
Winsorized Mean ( 2 / 36 )1022738.8888888920953.341738225148.8102996489152
Winsorized Mean ( 3 / 36 )1022233.3333333320646.084867428649.5122121165944
Winsorized Mean ( 4 / 36 )1023581.4814814820160.521713745950.771577046222
Winsorized Mean ( 5 / 36 )1023581.4814814820160.521713745950.771577046222
Winsorized Mean ( 6 / 36 )1022570.3703703719259.266008998553.094981391949
Winsorized Mean ( 7 / 36 )1021390.7407407419046.104523042553.6272779299848
Winsorized Mean ( 8 / 36 )1015998.1481481518157.156426426955.9557963971389
Winsorized Mean ( 9 / 36 )1014481.4814814817932.452011572956.5723795511497
Winsorized Mean ( 10 / 36 )1014481.4814814817932.452011572956.5723795511497
Winsorized Mean ( 11 / 36 )1016335.1851851917643.67355559957.6033773228968
Winsorized Mean ( 12 / 36 )1016335.1851851917048.789115535959.6133354866265
Winsorized Mean ( 13 / 36 )1016335.1851851917048.789115535959.6133354866265
Winsorized Mean ( 14 / 36 )1021053.703703715727.872885643764.9200124598993
Winsorized Mean ( 15 / 36 )1021053.703703715727.872885643764.9200124598993
Winsorized Mean ( 16 / 36 )1021053.703703715727.872885643764.9200124598993
Winsorized Mean ( 17 / 36 )1023918.5185185215361.71986093266.6538986381696
Winsorized Mean ( 18 / 36 )1023918.5185185215361.71986093266.6538986381696
Winsorized Mean ( 19 / 36 )1023918.5185185214523.435910062570.5011214191471
Winsorized Mean ( 20 / 36 )1020548.1481481514068.969060114972.538943243636
Winsorized Mean ( 21 / 36 )1020548.1481481514068.969060114972.538943243636
Winsorized Mean ( 22 / 36 )1020548.1481481514068.969060114972.538943243636
Winsorized Mean ( 23 / 36 )1020548.1481481514068.969060114972.538943243636
Winsorized Mean ( 24 / 36 )1016503.703703712541.804234413681.0492401814493
Winsorized Mean ( 25 / 36 )1016503.703703712541.804234413681.0492401814493
Winsorized Mean ( 26 / 36 )1016503.703703711487.295940597688.489380700226
Winsorized Mean ( 27 / 36 )1016503.703703711487.295940597688.489380700226
Winsorized Mean ( 28 / 36 )1021222.2222222210952.116534370893.2442801368428
Winsorized Mean ( 29 / 36 )1021222.2222222210952.116534370893.2442801368428
Winsorized Mean ( 30 / 36 )1016166.6666666710344.193034054898.2354702122514
Winsorized Mean ( 31 / 36 )1016166.6666666710344.193034054898.2354702122514
Winsorized Mean ( 32 / 36 )1010774.074074079721.14312691468103.976874003179
Winsorized Mean ( 33 / 36 )1016335.185185199098.93539533681111.698252710537
Winsorized Mean ( 34 / 36 )1016335.185185199098.93539533681111.698252710537
Winsorized Mean ( 35 / 36 )1010437.037037048432.91575772372119.820601327788
Winsorized Mean ( 36 / 36 )1016503.70370377772.57227441693130.780862218481
Trimmed Mean ( 1 / 36 )1021775.4716981120526.152004284749.7792022335615
Trimmed Mean ( 2 / 36 )102147519897.492005446251.3368719897165
Trimmed Mean ( 3 / 36 )1020805.8823529419267.717219639952.9801154291603
Trimmed Mean ( 4 / 36 )102029218687.661012042454.5970948072377
Trimmed Mean ( 5 / 36 )1019385.7142857118195.203148933856.024970204603
Trimmed Mean ( 6 / 36 )1018441.6666666717636.324137800657.7468217701785
Trimmed Mean ( 7 / 36 )1017651.0638297917228.160040653459.0690509856206
Trimmed Mean ( 8 / 36 )1017023.9130434816811.943415288660.4941313399025
Trimmed Mean ( 9 / 36 )1017177.7777777816519.258067043761.5752701271174
Trimmed Mean ( 10 / 36 )1017545.4545454516225.961796782562.7109484965771
Trimmed Mean ( 11 / 36 )1017930.2325581415889.196621425864.0642983286839
Trimmed Mean ( 12 / 36 )1018116.6666666715551.831871677665.4660283796421
Trimmed Mean ( 13 / 36 )1018312.1951219515260.589827976966.7282330893331
Trimmed Mean ( 14 / 36 )1018517.514922.80503281768.2524162019245
Trimmed Mean ( 15 / 36 )1018266.6666666714733.127655221469.1140870082526
Trimmed Mean ( 16 / 36 )1018002.6315789514509.365151537370.161762485596
Trimmed Mean ( 17 / 36 )1017724.3243243214245.450154191771.4420613816027
Trimmed Mean ( 18 / 36 )1017177.7777777813986.708174701172.7246014625251
Trimmed Mean ( 19 / 36 )101660013679.350777034774.3163923909824
Trimmed Mean ( 20 / 36 )1015988.2352941213438.321942015775.6038022959975
Trimmed Mean ( 21 / 36 )1015615.1515151513216.949145696576.8418748017838
Trimmed Mean ( 22 / 36 )1015218.7512948.694331701378.4031751768607
Trimmed Mean ( 23 / 36 )1014796.7741935512623.252106647380.3910724130407
Trimmed Mean ( 24 / 36 )1014346.6666666712227.056102824682.9591896967204
Trimmed Mean ( 25 / 36 )1014179.3103448311993.18690403384.5629538220395
Trimmed Mean ( 26 / 36 )101400011702.625967937986.6472194170857
Trimmed Mean ( 27 / 36 )1013807.4074074111512.999322599688.0576276433317
Trimmed Mean ( 28 / 36 )101360011270.976087313189.930099411792
Trimmed Mean ( 29 / 36 )101301211050.581161187991.6704728216401
Trimmed Mean ( 30 / 36 )101237510764.878578767394.0442562907132
Trimmed Mean ( 31 / 36 )1012078.2608695710515.055648692896.2503951175366
Trimmed Mean ( 32 / 36 )1011754.5454545510186.030444751899.3276577114332
Trimmed Mean ( 33 / 36 )1011833.333333339886.3857554838102.346131170543
Trimmed Mean ( 34 / 36 )10114659619.22857267324105.150323891192
Trimmed Mean ( 35 / 36 )1011057.894736849252.69068672589109.271770663136
Trimmed Mean ( 36 / 36 )1011111.111111118923.34709942352113.310745378988
Median1001000
Midrange1019200
Midmean - Weighted Average at Xnp1014000
Midmean - Weighted Average at X(n+1)p1014000
Midmean - Empirical Distribution Function1014000
Midmean - Empirical Distribution Function - Averaging1014000
Midmean - Empirical Distribution Function - Interpolation1014000
Midmean - Closest Observation1014000
Midmean - True Basic - Statistics Graphics Toolkit1014000
Midmean - MS Excel (old versions)1014000
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 1021727.77777778 & 21307.3950664078 & 47.9517920700022 \tabularnewline
Geometric Mean & 997178.462810999 &  &  \tabularnewline
Harmonic Mean & 971564.293486488 &  &  \tabularnewline
Quadratic Mean & 1045230.21192746 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 1022064.81481481 & 21085.2161503911 & 48.473053703832 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 1022738.88888889 & 20953.3417382251 & 48.8102996489152 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 1022233.33333333 & 20646.0848674286 & 49.5122121165944 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 1023581.48148148 & 20160.5217137459 & 50.771577046222 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 1023581.48148148 & 20160.5217137459 & 50.771577046222 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 1022570.37037037 & 19259.2660089985 & 53.094981391949 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 1021390.74074074 & 19046.1045230425 & 53.6272779299848 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 1015998.14814815 & 18157.1564264269 & 55.9557963971389 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 1014481.48148148 & 17932.4520115729 & 56.5723795511497 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 1014481.48148148 & 17932.4520115729 & 56.5723795511497 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 1016335.18518519 & 17643.673555599 & 57.6033773228968 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 1016335.18518519 & 17048.7891155359 & 59.6133354866265 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 1016335.18518519 & 17048.7891155359 & 59.6133354866265 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 1021053.7037037 & 15727.8728856437 & 64.9200124598993 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 1021053.7037037 & 15727.8728856437 & 64.9200124598993 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 1021053.7037037 & 15727.8728856437 & 64.9200124598993 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 1023918.51851852 & 15361.719860932 & 66.6538986381696 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 1023918.51851852 & 15361.719860932 & 66.6538986381696 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 1023918.51851852 & 14523.4359100625 & 70.5011214191471 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 1020548.14814815 & 14068.9690601149 & 72.538943243636 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 1020548.14814815 & 14068.9690601149 & 72.538943243636 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 1020548.14814815 & 14068.9690601149 & 72.538943243636 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 1020548.14814815 & 14068.9690601149 & 72.538943243636 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 1016503.7037037 & 12541.8042344136 & 81.0492401814493 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 1016503.7037037 & 12541.8042344136 & 81.0492401814493 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 1016503.7037037 & 11487.2959405976 & 88.489380700226 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 1016503.7037037 & 11487.2959405976 & 88.489380700226 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 1021222.22222222 & 10952.1165343708 & 93.2442801368428 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 1021222.22222222 & 10952.1165343708 & 93.2442801368428 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 1016166.66666667 & 10344.1930340548 & 98.2354702122514 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 1016166.66666667 & 10344.1930340548 & 98.2354702122514 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 1010774.07407407 & 9721.14312691468 & 103.976874003179 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 1016335.18518519 & 9098.93539533681 & 111.698252710537 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 1016335.18518519 & 9098.93539533681 & 111.698252710537 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 1010437.03703704 & 8432.91575772372 & 119.820601327788 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 1016503.7037037 & 7772.57227441693 & 130.780862218481 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 1021775.47169811 & 20526.1520042847 & 49.7792022335615 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 1021475 & 19897.4920054462 & 51.3368719897165 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 1020805.88235294 & 19267.7172196399 & 52.9801154291603 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 1020292 & 18687.6610120424 & 54.5970948072377 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 1019385.71428571 & 18195.2031489338 & 56.024970204603 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 1018441.66666667 & 17636.3241378006 & 57.7468217701785 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 1017651.06382979 & 17228.1600406534 & 59.0690509856206 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 1017023.91304348 & 16811.9434152886 & 60.4941313399025 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 1017177.77777778 & 16519.2580670437 & 61.5752701271174 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 1017545.45454545 & 16225.9617967825 & 62.7109484965771 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 1017930.23255814 & 15889.1966214258 & 64.0642983286839 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 1018116.66666667 & 15551.8318716776 & 65.4660283796421 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 1018312.19512195 & 15260.5898279769 & 66.7282330893331 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 1018517.5 & 14922.805032817 & 68.2524162019245 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 1018266.66666667 & 14733.1276552214 & 69.1140870082526 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 1018002.63157895 & 14509.3651515373 & 70.161762485596 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 1017724.32432432 & 14245.4501541917 & 71.4420613816027 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 1017177.77777778 & 13986.7081747011 & 72.7246014625251 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 1016600 & 13679.3507770347 & 74.3163923909824 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 1015988.23529412 & 13438.3219420157 & 75.6038022959975 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 1015615.15151515 & 13216.9491456965 & 76.8418748017838 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 1015218.75 & 12948.6943317013 & 78.4031751768607 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 1014796.77419355 & 12623.2521066473 & 80.3910724130407 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 1014346.66666667 & 12227.0561028246 & 82.9591896967204 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 1014179.31034483 & 11993.186904033 & 84.5629538220395 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 1014000 & 11702.6259679379 & 86.6472194170857 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 1013807.40740741 & 11512.9993225996 & 88.0576276433317 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 1013600 & 11270.9760873131 & 89.930099411792 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 1013012 & 11050.5811611879 & 91.6704728216401 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 1012375 & 10764.8785787673 & 94.0442562907132 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 1012078.26086957 & 10515.0556486928 & 96.2503951175366 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 1011754.54545455 & 10186.0304447518 & 99.3276577114332 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 1011833.33333333 & 9886.3857554838 & 102.346131170543 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 1011465 & 9619.22857267324 & 105.150323891192 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 1011057.89473684 & 9252.69068672589 & 109.271770663136 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 1011111.11111111 & 8923.34709942352 & 113.310745378988 \tabularnewline
Median & 1001000 &  &  \tabularnewline
Midrange & 1019200 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 1014000 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 1014000 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 1014000 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 1014000 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 1014000 &  &  \tabularnewline
Midmean - Closest Observation & 1014000 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 1014000 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 1014000 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279937&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]1021727.77777778[/C][C]21307.3950664078[/C][C]47.9517920700022[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]997178.462810999[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]971564.293486488[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]1045230.21192746[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]1022064.81481481[/C][C]21085.2161503911[/C][C]48.473053703832[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]1022738.88888889[/C][C]20953.3417382251[/C][C]48.8102996489152[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]1022233.33333333[/C][C]20646.0848674286[/C][C]49.5122121165944[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]1023581.48148148[/C][C]20160.5217137459[/C][C]50.771577046222[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]1023581.48148148[/C][C]20160.5217137459[/C][C]50.771577046222[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]1022570.37037037[/C][C]19259.2660089985[/C][C]53.094981391949[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]1021390.74074074[/C][C]19046.1045230425[/C][C]53.6272779299848[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]1015998.14814815[/C][C]18157.1564264269[/C][C]55.9557963971389[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]1014481.48148148[/C][C]17932.4520115729[/C][C]56.5723795511497[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]1014481.48148148[/C][C]17932.4520115729[/C][C]56.5723795511497[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]1016335.18518519[/C][C]17643.673555599[/C][C]57.6033773228968[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]1016335.18518519[/C][C]17048.7891155359[/C][C]59.6133354866265[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]1016335.18518519[/C][C]17048.7891155359[/C][C]59.6133354866265[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]1021053.7037037[/C][C]15727.8728856437[/C][C]64.9200124598993[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]1021053.7037037[/C][C]15727.8728856437[/C][C]64.9200124598993[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]1021053.7037037[/C][C]15727.8728856437[/C][C]64.9200124598993[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]1023918.51851852[/C][C]15361.719860932[/C][C]66.6538986381696[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]1023918.51851852[/C][C]15361.719860932[/C][C]66.6538986381696[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]1023918.51851852[/C][C]14523.4359100625[/C][C]70.5011214191471[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]1020548.14814815[/C][C]14068.9690601149[/C][C]72.538943243636[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]1020548.14814815[/C][C]14068.9690601149[/C][C]72.538943243636[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]1020548.14814815[/C][C]14068.9690601149[/C][C]72.538943243636[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]1020548.14814815[/C][C]14068.9690601149[/C][C]72.538943243636[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]1016503.7037037[/C][C]12541.8042344136[/C][C]81.0492401814493[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]1016503.7037037[/C][C]12541.8042344136[/C][C]81.0492401814493[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]1016503.7037037[/C][C]11487.2959405976[/C][C]88.489380700226[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]1016503.7037037[/C][C]11487.2959405976[/C][C]88.489380700226[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]1021222.22222222[/C][C]10952.1165343708[/C][C]93.2442801368428[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]1021222.22222222[/C][C]10952.1165343708[/C][C]93.2442801368428[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]1016166.66666667[/C][C]10344.1930340548[/C][C]98.2354702122514[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]1016166.66666667[/C][C]10344.1930340548[/C][C]98.2354702122514[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]1010774.07407407[/C][C]9721.14312691468[/C][C]103.976874003179[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]1016335.18518519[/C][C]9098.93539533681[/C][C]111.698252710537[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]1016335.18518519[/C][C]9098.93539533681[/C][C]111.698252710537[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]1010437.03703704[/C][C]8432.91575772372[/C][C]119.820601327788[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]1016503.7037037[/C][C]7772.57227441693[/C][C]130.780862218481[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]1021775.47169811[/C][C]20526.1520042847[/C][C]49.7792022335615[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]1021475[/C][C]19897.4920054462[/C][C]51.3368719897165[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]1020805.88235294[/C][C]19267.7172196399[/C][C]52.9801154291603[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]1020292[/C][C]18687.6610120424[/C][C]54.5970948072377[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]1019385.71428571[/C][C]18195.2031489338[/C][C]56.024970204603[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]1018441.66666667[/C][C]17636.3241378006[/C][C]57.7468217701785[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]1017651.06382979[/C][C]17228.1600406534[/C][C]59.0690509856206[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]1017023.91304348[/C][C]16811.9434152886[/C][C]60.4941313399025[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]1017177.77777778[/C][C]16519.2580670437[/C][C]61.5752701271174[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]1017545.45454545[/C][C]16225.9617967825[/C][C]62.7109484965771[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]1017930.23255814[/C][C]15889.1966214258[/C][C]64.0642983286839[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]1018116.66666667[/C][C]15551.8318716776[/C][C]65.4660283796421[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]1018312.19512195[/C][C]15260.5898279769[/C][C]66.7282330893331[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]1018517.5[/C][C]14922.805032817[/C][C]68.2524162019245[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]1018266.66666667[/C][C]14733.1276552214[/C][C]69.1140870082526[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]1018002.63157895[/C][C]14509.3651515373[/C][C]70.161762485596[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]1017724.32432432[/C][C]14245.4501541917[/C][C]71.4420613816027[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]1017177.77777778[/C][C]13986.7081747011[/C][C]72.7246014625251[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]1016600[/C][C]13679.3507770347[/C][C]74.3163923909824[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]1015988.23529412[/C][C]13438.3219420157[/C][C]75.6038022959975[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]1015615.15151515[/C][C]13216.9491456965[/C][C]76.8418748017838[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]1015218.75[/C][C]12948.6943317013[/C][C]78.4031751768607[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]1014796.77419355[/C][C]12623.2521066473[/C][C]80.3910724130407[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]1014346.66666667[/C][C]12227.0561028246[/C][C]82.9591896967204[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]1014179.31034483[/C][C]11993.186904033[/C][C]84.5629538220395[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]1014000[/C][C]11702.6259679379[/C][C]86.6472194170857[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]1013807.40740741[/C][C]11512.9993225996[/C][C]88.0576276433317[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]1013600[/C][C]11270.9760873131[/C][C]89.930099411792[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]1013012[/C][C]11050.5811611879[/C][C]91.6704728216401[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]1012375[/C][C]10764.8785787673[/C][C]94.0442562907132[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]1012078.26086957[/C][C]10515.0556486928[/C][C]96.2503951175366[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]1011754.54545455[/C][C]10186.0304447518[/C][C]99.3276577114332[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]1011833.33333333[/C][C]9886.3857554838[/C][C]102.346131170543[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]1011465[/C][C]9619.22857267324[/C][C]105.150323891192[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]1011057.89473684[/C][C]9252.69068672589[/C][C]109.271770663136[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]1011111.11111111[/C][C]8923.34709942352[/C][C]113.310745378988[/C][/ROW]
[ROW][C]Median[/C][C]1001000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]1019200[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]1014000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]1014000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]1014000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]1014000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]1014000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]1014000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]1014000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]1014000[/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=279937&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279937&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 Mean1021727.7777777821307.395066407847.9517920700022
Geometric Mean997178.462810999
Harmonic Mean971564.293486488
Quadratic Mean1045230.21192746
Winsorized Mean ( 1 / 36 )1022064.8148148121085.216150391148.473053703832
Winsorized Mean ( 2 / 36 )1022738.8888888920953.341738225148.8102996489152
Winsorized Mean ( 3 / 36 )1022233.3333333320646.084867428649.5122121165944
Winsorized Mean ( 4 / 36 )1023581.4814814820160.521713745950.771577046222
Winsorized Mean ( 5 / 36 )1023581.4814814820160.521713745950.771577046222
Winsorized Mean ( 6 / 36 )1022570.3703703719259.266008998553.094981391949
Winsorized Mean ( 7 / 36 )1021390.7407407419046.104523042553.6272779299848
Winsorized Mean ( 8 / 36 )1015998.1481481518157.156426426955.9557963971389
Winsorized Mean ( 9 / 36 )1014481.4814814817932.452011572956.5723795511497
Winsorized Mean ( 10 / 36 )1014481.4814814817932.452011572956.5723795511497
Winsorized Mean ( 11 / 36 )1016335.1851851917643.67355559957.6033773228968
Winsorized Mean ( 12 / 36 )1016335.1851851917048.789115535959.6133354866265
Winsorized Mean ( 13 / 36 )1016335.1851851917048.789115535959.6133354866265
Winsorized Mean ( 14 / 36 )1021053.703703715727.872885643764.9200124598993
Winsorized Mean ( 15 / 36 )1021053.703703715727.872885643764.9200124598993
Winsorized Mean ( 16 / 36 )1021053.703703715727.872885643764.9200124598993
Winsorized Mean ( 17 / 36 )1023918.5185185215361.71986093266.6538986381696
Winsorized Mean ( 18 / 36 )1023918.5185185215361.71986093266.6538986381696
Winsorized Mean ( 19 / 36 )1023918.5185185214523.435910062570.5011214191471
Winsorized Mean ( 20 / 36 )1020548.1481481514068.969060114972.538943243636
Winsorized Mean ( 21 / 36 )1020548.1481481514068.969060114972.538943243636
Winsorized Mean ( 22 / 36 )1020548.1481481514068.969060114972.538943243636
Winsorized Mean ( 23 / 36 )1020548.1481481514068.969060114972.538943243636
Winsorized Mean ( 24 / 36 )1016503.703703712541.804234413681.0492401814493
Winsorized Mean ( 25 / 36 )1016503.703703712541.804234413681.0492401814493
Winsorized Mean ( 26 / 36 )1016503.703703711487.295940597688.489380700226
Winsorized Mean ( 27 / 36 )1016503.703703711487.295940597688.489380700226
Winsorized Mean ( 28 / 36 )1021222.2222222210952.116534370893.2442801368428
Winsorized Mean ( 29 / 36 )1021222.2222222210952.116534370893.2442801368428
Winsorized Mean ( 30 / 36 )1016166.6666666710344.193034054898.2354702122514
Winsorized Mean ( 31 / 36 )1016166.6666666710344.193034054898.2354702122514
Winsorized Mean ( 32 / 36 )1010774.074074079721.14312691468103.976874003179
Winsorized Mean ( 33 / 36 )1016335.185185199098.93539533681111.698252710537
Winsorized Mean ( 34 / 36 )1016335.185185199098.93539533681111.698252710537
Winsorized Mean ( 35 / 36 )1010437.037037048432.91575772372119.820601327788
Winsorized Mean ( 36 / 36 )1016503.70370377772.57227441693130.780862218481
Trimmed Mean ( 1 / 36 )1021775.4716981120526.152004284749.7792022335615
Trimmed Mean ( 2 / 36 )102147519897.492005446251.3368719897165
Trimmed Mean ( 3 / 36 )1020805.8823529419267.717219639952.9801154291603
Trimmed Mean ( 4 / 36 )102029218687.661012042454.5970948072377
Trimmed Mean ( 5 / 36 )1019385.7142857118195.203148933856.024970204603
Trimmed Mean ( 6 / 36 )1018441.6666666717636.324137800657.7468217701785
Trimmed Mean ( 7 / 36 )1017651.0638297917228.160040653459.0690509856206
Trimmed Mean ( 8 / 36 )1017023.9130434816811.943415288660.4941313399025
Trimmed Mean ( 9 / 36 )1017177.7777777816519.258067043761.5752701271174
Trimmed Mean ( 10 / 36 )1017545.4545454516225.961796782562.7109484965771
Trimmed Mean ( 11 / 36 )1017930.2325581415889.196621425864.0642983286839
Trimmed Mean ( 12 / 36 )1018116.6666666715551.831871677665.4660283796421
Trimmed Mean ( 13 / 36 )1018312.1951219515260.589827976966.7282330893331
Trimmed Mean ( 14 / 36 )1018517.514922.80503281768.2524162019245
Trimmed Mean ( 15 / 36 )1018266.6666666714733.127655221469.1140870082526
Trimmed Mean ( 16 / 36 )1018002.6315789514509.365151537370.161762485596
Trimmed Mean ( 17 / 36 )1017724.3243243214245.450154191771.4420613816027
Trimmed Mean ( 18 / 36 )1017177.7777777813986.708174701172.7246014625251
Trimmed Mean ( 19 / 36 )101660013679.350777034774.3163923909824
Trimmed Mean ( 20 / 36 )1015988.2352941213438.321942015775.6038022959975
Trimmed Mean ( 21 / 36 )1015615.1515151513216.949145696576.8418748017838
Trimmed Mean ( 22 / 36 )1015218.7512948.694331701378.4031751768607
Trimmed Mean ( 23 / 36 )1014796.7741935512623.252106647380.3910724130407
Trimmed Mean ( 24 / 36 )1014346.6666666712227.056102824682.9591896967204
Trimmed Mean ( 25 / 36 )1014179.3103448311993.18690403384.5629538220395
Trimmed Mean ( 26 / 36 )101400011702.625967937986.6472194170857
Trimmed Mean ( 27 / 36 )1013807.4074074111512.999322599688.0576276433317
Trimmed Mean ( 28 / 36 )101360011270.976087313189.930099411792
Trimmed Mean ( 29 / 36 )101301211050.581161187991.6704728216401
Trimmed Mean ( 30 / 36 )101237510764.878578767394.0442562907132
Trimmed Mean ( 31 / 36 )1012078.2608695710515.055648692896.2503951175366
Trimmed Mean ( 32 / 36 )1011754.5454545510186.030444751899.3276577114332
Trimmed Mean ( 33 / 36 )1011833.333333339886.3857554838102.346131170543
Trimmed Mean ( 34 / 36 )10114659619.22857267324105.150323891192
Trimmed Mean ( 35 / 36 )1011057.894736849252.69068672589109.271770663136
Trimmed Mean ( 36 / 36 )1011111.111111118923.34709942352113.310745378988
Median1001000
Midrange1019200
Midmean - Weighted Average at Xnp1014000
Midmean - Weighted Average at X(n+1)p1014000
Midmean - Empirical Distribution Function1014000
Midmean - Empirical Distribution Function - Averaging1014000
Midmean - Empirical Distribution Function - Interpolation1014000
Midmean - Closest Observation1014000
Midmean - True Basic - Statistics Graphics Toolkit1014000
Midmean - MS Excel (old versions)1014000
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')