Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSun, 31 Jul 2011 07:32:49 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Jul/31/t1312111984851nmrp6p1fws1h.htm/, Retrieved Wed, 15 May 2024 17:41:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=123208, Retrieved Wed, 15 May 2024 17:41:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKatrien Monnens
Estimated Impact182
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Tijdreeks B stap 9] [2011-07-31 11:32:49] [3f9379635061ebc5737ab9ab2503b0b0] [Current]
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Dataseries X:
740
730
740
820
820
850
870
930
890
790
840
880
730
730
770
880
820
900
940
1080
920
710
880
910
680
740
740
810
800
900
920
1030
910
720
930
900
680
770
770
810
810
910
820
980
830
760
930
910
640
780
690
820
800
910
850
980
830
820
1010
930
630
760
670
850
780
900
840
1050
810
860
1020
820
670
780
690
800
810
910
870
1010
810
960
990
780
700
810
760
810
840
900
920
1050
860
870
880
860
650
830
730
810
840
940
870
940
770
870
860
760




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=123208&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=123208&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123208&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 Mean837.870370370379.2258787361926290.8174055099435
Geometric Mean832.414155394679
Harmonic Mean826.928677014415
Quadratic Mean843.287767763329
Winsorized Mean ( 1 / 36 )837.6851851851859.142544946437991.6249457993162
Winsorized Mean ( 2 / 36 )837.870370370379.105978589367792.0132155097183
Winsorized Mean ( 3 / 36 )837.870370370378.8866666412766894.2839879329602
Winsorized Mean ( 4 / 36 )837.58.8134045065566195.0257076453206
Winsorized Mean ( 5 / 36 )837.58.6448773539717196.8781818073137
Winsorized Mean ( 6 / 36 )837.58.6448773539717196.8781818073137
Winsorized Mean ( 7 / 36 )836.8518518518528.30331889520457100.78522364535
Winsorized Mean ( 8 / 36 )836.1111111111118.17855571043636102.232122726043
Winsorized Mean ( 9 / 36 )836.9444444444448.04265447404078104.063210367404
Winsorized Mean ( 10 / 36 )836.0185185185187.60178402529073109.976620716549
Winsorized Mean ( 11 / 36 )8357.15077689805519116.770528839614
Winsorized Mean ( 12 / 36 )836.1111111111116.98838641675021119.64294205413
Winsorized Mean ( 13 / 36 )836.1111111111116.98838641675021119.64294205413
Winsorized Mean ( 14 / 36 )834.8148148148156.81364649036761122.521004867949
Winsorized Mean ( 15 / 36 )834.8148148148156.81364649036761122.521004867949
Winsorized Mean ( 16 / 36 )836.2962962962966.60615396486913126.593521850026
Winsorized Mean ( 17 / 36 )836.2962962962966.60615396486913126.593521850026
Winsorized Mean ( 18 / 36 )834.629629629636.39155336455934130.583221640233
Winsorized Mean ( 19 / 36 )834.629629629636.39155336455934130.583221640233
Winsorized Mean ( 20 / 36 )838.3333333333335.90465961695575141.978265931873
Winsorized Mean ( 21 / 36 )836.3888888888895.66067475850606147.754273928578
Winsorized Mean ( 22 / 36 )836.3888888888895.66067475850606147.754273928578
Winsorized Mean ( 23 / 36 )836.3888888888895.66067475850606147.754273928578
Winsorized Mean ( 24 / 36 )838.6111111111115.38811804659074155.640820015391
Winsorized Mean ( 25 / 36 )838.6111111111115.38811804659074155.640820015391
Winsorized Mean ( 26 / 36 )838.6111111111115.38811804659074155.640820015391
Winsorized Mean ( 27 / 36 )836.1111111111115.08636612342499164.382801163378
Winsorized Mean ( 28 / 36 )838.7037037037044.77984075929226175.466871374997
Winsorized Mean ( 29 / 36 )838.7037037037044.77984075929226175.466871374997
Winsorized Mean ( 30 / 36 )838.7037037037044.77984075929226175.466871374997
Winsorized Mean ( 31 / 36 )838.7037037037044.77984075929226175.466871374997
Winsorized Mean ( 32 / 36 )838.7037037037044.09326328280977204.898548115866
Winsorized Mean ( 33 / 36 )838.7037037037043.40802250381519246.096879573065
Winsorized Mean ( 34 / 36 )838.7037037037043.40802250381519246.096879573065
Winsorized Mean ( 35 / 36 )838.7037037037043.40802250381519246.096879573065
Winsorized Mean ( 36 / 36 )842.0370370370373.06771184968834274.483744984909
Trimmed Mean ( 1 / 36 )837.5471698113218.9007821625016594.0981539060518
Trimmed Mean ( 2 / 36 )837.4038461538468.6289316485206497.0460632049869
Trimmed Mean ( 3 / 36 )837.1568627450988.34415230641704100.328569278546
Trimmed Mean ( 4 / 36 )836.98.11619530707747103.114817760757
Trimmed Mean ( 5 / 36 )836.7346938775517.88324157914513106.140942844008
Trimmed Mean ( 6 / 36 )836.56257.66746962566702109.105420802658
Trimmed Mean ( 7 / 36 )836.3829787234047.42205907859373112.688806417029
Trimmed Mean ( 8 / 36 )836.3043478260877.22102988543951115.815106860645
Trimmed Mean ( 9 / 36 )836.3333333333337.01781218686688119.172943228439
Trimmed Mean ( 10 / 36 )836.256.81198560317689122.76156303237
Trimmed Mean ( 11 / 36 )836.2790697674426.65763606433964125.612013286039
Trimmed Mean ( 12 / 36 )836.4285714285716.55670105019171127.568508160688
Trimmed Mean ( 13 / 36 )836.4634146341466.46574358795045129.368479163476
Trimmed Mean ( 14 / 36 )836.56.35973289782248131.530681152727
Trimmed Mean ( 15 / 36 )836.6666666666676.26229504385886133.603840254564
Trimmed Mean ( 16 / 36 )836.8421052631586.14791514031251136.118031261671
Trimmed Mean ( 17 / 36 )836.8918918918926.0447720999171138.448874177303
Trimmed Mean ( 18 / 36 )836.9444444444445.92281763486535141.308494713339
Trimmed Mean ( 19 / 36 )837.1428571428575.80976139079082144.092467974645
Trimmed Mean ( 20 / 36 )837.3529411764715.67489754255294147.553843024939
Trimmed Mean ( 21 / 36 )837.2727272727275.5869705838808149.861667374512
Trimmed Mean ( 22 / 36 )837.343755.5153204168566151.821415024376
Trimmed Mean ( 23 / 36 )837.419354838715.42696074259714154.307243880661
Trimmed Mean ( 24 / 36 )837.55.31826083462298157.476292728574
Trimmed Mean ( 25 / 36 )837.4137931034485.22662656179202160.220705115065
Trimmed Mean ( 26 / 36 )837.3214285714295.11231687779603163.785119073528
Trimmed Mean ( 27 / 36 )837.2222222222224.96962588714561168.467856783299
Trimmed Mean ( 28 / 36 )837.3076923076924.8438309930202172.860633146414
Trimmed Mean ( 29 / 36 )837.24.7383799866578176.684859035655
Trimmed Mean ( 30 / 36 )837.0833333333334.60263505059694181.870455539326
Trimmed Mean ( 31 / 36 )836.956521739134.42729309799943189.044751095727
Trimmed Mean ( 32 / 36 )836.8181818181824.19872032343319199.303148901791
Trimmed Mean ( 33 / 36 )836.6666666666674.05632049595826206.26246557695
Trimmed Mean ( 34 / 36 )836.54.01200122708778208.499437725047
Trimmed Mean ( 35 / 36 )836.3157894736843.94523413140158211.981282129022
Trimmed Mean ( 36 / 36 )836.1111111111113.84785608783166217.292718861083
Median830
Midrange855
Midmean - Weighted Average at Xnp833.684210526316
Midmean - Weighted Average at X(n+1)p833.684210526316
Midmean - Empirical Distribution Function833.684210526316
Midmean - Empirical Distribution Function - Averaging833.684210526316
Midmean - Empirical Distribution Function - Interpolation833.684210526316
Midmean - Closest Observation833.684210526316
Midmean - True Basic - Statistics Graphics Toolkit833.684210526316
Midmean - MS Excel (old versions)840.952380952381
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 837.87037037037 & 9.22587873619262 & 90.8174055099435 \tabularnewline
Geometric Mean & 832.414155394679 &  &  \tabularnewline
Harmonic Mean & 826.928677014415 &  &  \tabularnewline
Quadratic Mean & 843.287767763329 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 837.685185185185 & 9.1425449464379 & 91.6249457993162 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 837.87037037037 & 9.1059785893677 & 92.0132155097183 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 837.87037037037 & 8.88666664127668 & 94.2839879329602 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 837.5 & 8.81340450655661 & 95.0257076453206 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 837.5 & 8.64487735397171 & 96.8781818073137 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 837.5 & 8.64487735397171 & 96.8781818073137 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 836.851851851852 & 8.30331889520457 & 100.78522364535 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 836.111111111111 & 8.17855571043636 & 102.232122726043 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 836.944444444444 & 8.04265447404078 & 104.063210367404 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 836.018518518518 & 7.60178402529073 & 109.976620716549 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 835 & 7.15077689805519 & 116.770528839614 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 836.111111111111 & 6.98838641675021 & 119.64294205413 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 836.111111111111 & 6.98838641675021 & 119.64294205413 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 834.814814814815 & 6.81364649036761 & 122.521004867949 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 834.814814814815 & 6.81364649036761 & 122.521004867949 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 836.296296296296 & 6.60615396486913 & 126.593521850026 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 836.296296296296 & 6.60615396486913 & 126.593521850026 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 834.62962962963 & 6.39155336455934 & 130.583221640233 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 834.62962962963 & 6.39155336455934 & 130.583221640233 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 838.333333333333 & 5.90465961695575 & 141.978265931873 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 836.388888888889 & 5.66067475850606 & 147.754273928578 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 836.388888888889 & 5.66067475850606 & 147.754273928578 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 836.388888888889 & 5.66067475850606 & 147.754273928578 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 838.611111111111 & 5.38811804659074 & 155.640820015391 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 838.611111111111 & 5.38811804659074 & 155.640820015391 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 838.611111111111 & 5.38811804659074 & 155.640820015391 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 836.111111111111 & 5.08636612342499 & 164.382801163378 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 838.703703703704 & 4.77984075929226 & 175.466871374997 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 838.703703703704 & 4.77984075929226 & 175.466871374997 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 838.703703703704 & 4.77984075929226 & 175.466871374997 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 838.703703703704 & 4.77984075929226 & 175.466871374997 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 838.703703703704 & 4.09326328280977 & 204.898548115866 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 838.703703703704 & 3.40802250381519 & 246.096879573065 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 838.703703703704 & 3.40802250381519 & 246.096879573065 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 838.703703703704 & 3.40802250381519 & 246.096879573065 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 842.037037037037 & 3.06771184968834 & 274.483744984909 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 837.547169811321 & 8.90078216250165 & 94.0981539060518 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 837.403846153846 & 8.62893164852064 & 97.0460632049869 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 837.156862745098 & 8.34415230641704 & 100.328569278546 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 836.9 & 8.11619530707747 & 103.114817760757 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 836.734693877551 & 7.88324157914513 & 106.140942844008 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 836.5625 & 7.66746962566702 & 109.105420802658 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 836.382978723404 & 7.42205907859373 & 112.688806417029 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 836.304347826087 & 7.22102988543951 & 115.815106860645 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 836.333333333333 & 7.01781218686688 & 119.172943228439 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 836.25 & 6.81198560317689 & 122.76156303237 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 836.279069767442 & 6.65763606433964 & 125.612013286039 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 836.428571428571 & 6.55670105019171 & 127.568508160688 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 836.463414634146 & 6.46574358795045 & 129.368479163476 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 836.5 & 6.35973289782248 & 131.530681152727 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 836.666666666667 & 6.26229504385886 & 133.603840254564 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 836.842105263158 & 6.14791514031251 & 136.118031261671 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 836.891891891892 & 6.0447720999171 & 138.448874177303 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 836.944444444444 & 5.92281763486535 & 141.308494713339 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 837.142857142857 & 5.80976139079082 & 144.092467974645 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 837.352941176471 & 5.67489754255294 & 147.553843024939 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 837.272727272727 & 5.5869705838808 & 149.861667374512 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 837.34375 & 5.5153204168566 & 151.821415024376 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 837.41935483871 & 5.42696074259714 & 154.307243880661 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 837.5 & 5.31826083462298 & 157.476292728574 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 837.413793103448 & 5.22662656179202 & 160.220705115065 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 837.321428571429 & 5.11231687779603 & 163.785119073528 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 837.222222222222 & 4.96962588714561 & 168.467856783299 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 837.307692307692 & 4.8438309930202 & 172.860633146414 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 837.2 & 4.7383799866578 & 176.684859035655 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 837.083333333333 & 4.60263505059694 & 181.870455539326 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 836.95652173913 & 4.42729309799943 & 189.044751095727 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 836.818181818182 & 4.19872032343319 & 199.303148901791 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 836.666666666667 & 4.05632049595826 & 206.26246557695 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 836.5 & 4.01200122708778 & 208.499437725047 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 836.315789473684 & 3.94523413140158 & 211.981282129022 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 836.111111111111 & 3.84785608783166 & 217.292718861083 \tabularnewline
Median & 830 &  &  \tabularnewline
Midrange & 855 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 833.684210526316 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 833.684210526316 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 833.684210526316 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 833.684210526316 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 833.684210526316 &  &  \tabularnewline
Midmean - Closest Observation & 833.684210526316 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 833.684210526316 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 840.952380952381 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123208&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]837.87037037037[/C][C]9.22587873619262[/C][C]90.8174055099435[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]832.414155394679[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]826.928677014415[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]843.287767763329[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]837.685185185185[/C][C]9.1425449464379[/C][C]91.6249457993162[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]837.87037037037[/C][C]9.1059785893677[/C][C]92.0132155097183[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]837.87037037037[/C][C]8.88666664127668[/C][C]94.2839879329602[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]837.5[/C][C]8.81340450655661[/C][C]95.0257076453206[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]837.5[/C][C]8.64487735397171[/C][C]96.8781818073137[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]837.5[/C][C]8.64487735397171[/C][C]96.8781818073137[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]836.851851851852[/C][C]8.30331889520457[/C][C]100.78522364535[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]836.111111111111[/C][C]8.17855571043636[/C][C]102.232122726043[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]836.944444444444[/C][C]8.04265447404078[/C][C]104.063210367404[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]836.018518518518[/C][C]7.60178402529073[/C][C]109.976620716549[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]835[/C][C]7.15077689805519[/C][C]116.770528839614[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]836.111111111111[/C][C]6.98838641675021[/C][C]119.64294205413[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]836.111111111111[/C][C]6.98838641675021[/C][C]119.64294205413[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]834.814814814815[/C][C]6.81364649036761[/C][C]122.521004867949[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]834.814814814815[/C][C]6.81364649036761[/C][C]122.521004867949[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]836.296296296296[/C][C]6.60615396486913[/C][C]126.593521850026[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]836.296296296296[/C][C]6.60615396486913[/C][C]126.593521850026[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]834.62962962963[/C][C]6.39155336455934[/C][C]130.583221640233[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]834.62962962963[/C][C]6.39155336455934[/C][C]130.583221640233[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]838.333333333333[/C][C]5.90465961695575[/C][C]141.978265931873[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]836.388888888889[/C][C]5.66067475850606[/C][C]147.754273928578[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]836.388888888889[/C][C]5.66067475850606[/C][C]147.754273928578[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]836.388888888889[/C][C]5.66067475850606[/C][C]147.754273928578[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]838.611111111111[/C][C]5.38811804659074[/C][C]155.640820015391[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]838.611111111111[/C][C]5.38811804659074[/C][C]155.640820015391[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]838.611111111111[/C][C]5.38811804659074[/C][C]155.640820015391[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]836.111111111111[/C][C]5.08636612342499[/C][C]164.382801163378[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]838.703703703704[/C][C]4.77984075929226[/C][C]175.466871374997[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]838.703703703704[/C][C]4.77984075929226[/C][C]175.466871374997[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]838.703703703704[/C][C]4.77984075929226[/C][C]175.466871374997[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]838.703703703704[/C][C]4.77984075929226[/C][C]175.466871374997[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]838.703703703704[/C][C]4.09326328280977[/C][C]204.898548115866[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]838.703703703704[/C][C]3.40802250381519[/C][C]246.096879573065[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]838.703703703704[/C][C]3.40802250381519[/C][C]246.096879573065[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]838.703703703704[/C][C]3.40802250381519[/C][C]246.096879573065[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]842.037037037037[/C][C]3.06771184968834[/C][C]274.483744984909[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]837.547169811321[/C][C]8.90078216250165[/C][C]94.0981539060518[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]837.403846153846[/C][C]8.62893164852064[/C][C]97.0460632049869[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]837.156862745098[/C][C]8.34415230641704[/C][C]100.328569278546[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]836.9[/C][C]8.11619530707747[/C][C]103.114817760757[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]836.734693877551[/C][C]7.88324157914513[/C][C]106.140942844008[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]836.5625[/C][C]7.66746962566702[/C][C]109.105420802658[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]836.382978723404[/C][C]7.42205907859373[/C][C]112.688806417029[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]836.304347826087[/C][C]7.22102988543951[/C][C]115.815106860645[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]836.333333333333[/C][C]7.01781218686688[/C][C]119.172943228439[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]836.25[/C][C]6.81198560317689[/C][C]122.76156303237[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]836.279069767442[/C][C]6.65763606433964[/C][C]125.612013286039[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]836.428571428571[/C][C]6.55670105019171[/C][C]127.568508160688[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]836.463414634146[/C][C]6.46574358795045[/C][C]129.368479163476[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]836.5[/C][C]6.35973289782248[/C][C]131.530681152727[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]836.666666666667[/C][C]6.26229504385886[/C][C]133.603840254564[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]836.842105263158[/C][C]6.14791514031251[/C][C]136.118031261671[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]836.891891891892[/C][C]6.0447720999171[/C][C]138.448874177303[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]836.944444444444[/C][C]5.92281763486535[/C][C]141.308494713339[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]837.142857142857[/C][C]5.80976139079082[/C][C]144.092467974645[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]837.352941176471[/C][C]5.67489754255294[/C][C]147.553843024939[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]837.272727272727[/C][C]5.5869705838808[/C][C]149.861667374512[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]837.34375[/C][C]5.5153204168566[/C][C]151.821415024376[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]837.41935483871[/C][C]5.42696074259714[/C][C]154.307243880661[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]837.5[/C][C]5.31826083462298[/C][C]157.476292728574[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]837.413793103448[/C][C]5.22662656179202[/C][C]160.220705115065[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]837.321428571429[/C][C]5.11231687779603[/C][C]163.785119073528[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]837.222222222222[/C][C]4.96962588714561[/C][C]168.467856783299[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]837.307692307692[/C][C]4.8438309930202[/C][C]172.860633146414[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]837.2[/C][C]4.7383799866578[/C][C]176.684859035655[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]837.083333333333[/C][C]4.60263505059694[/C][C]181.870455539326[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]836.95652173913[/C][C]4.42729309799943[/C][C]189.044751095727[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]836.818181818182[/C][C]4.19872032343319[/C][C]199.303148901791[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]836.666666666667[/C][C]4.05632049595826[/C][C]206.26246557695[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]836.5[/C][C]4.01200122708778[/C][C]208.499437725047[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]836.315789473684[/C][C]3.94523413140158[/C][C]211.981282129022[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]836.111111111111[/C][C]3.84785608783166[/C][C]217.292718861083[/C][/ROW]
[ROW][C]Median[/C][C]830[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]855[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]833.684210526316[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]833.684210526316[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]833.684210526316[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]833.684210526316[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]833.684210526316[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]833.684210526316[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]833.684210526316[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]840.952380952381[/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=123208&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123208&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 Mean837.870370370379.2258787361926290.8174055099435
Geometric Mean832.414155394679
Harmonic Mean826.928677014415
Quadratic Mean843.287767763329
Winsorized Mean ( 1 / 36 )837.6851851851859.142544946437991.6249457993162
Winsorized Mean ( 2 / 36 )837.870370370379.105978589367792.0132155097183
Winsorized Mean ( 3 / 36 )837.870370370378.8866666412766894.2839879329602
Winsorized Mean ( 4 / 36 )837.58.8134045065566195.0257076453206
Winsorized Mean ( 5 / 36 )837.58.6448773539717196.8781818073137
Winsorized Mean ( 6 / 36 )837.58.6448773539717196.8781818073137
Winsorized Mean ( 7 / 36 )836.8518518518528.30331889520457100.78522364535
Winsorized Mean ( 8 / 36 )836.1111111111118.17855571043636102.232122726043
Winsorized Mean ( 9 / 36 )836.9444444444448.04265447404078104.063210367404
Winsorized Mean ( 10 / 36 )836.0185185185187.60178402529073109.976620716549
Winsorized Mean ( 11 / 36 )8357.15077689805519116.770528839614
Winsorized Mean ( 12 / 36 )836.1111111111116.98838641675021119.64294205413
Winsorized Mean ( 13 / 36 )836.1111111111116.98838641675021119.64294205413
Winsorized Mean ( 14 / 36 )834.8148148148156.81364649036761122.521004867949
Winsorized Mean ( 15 / 36 )834.8148148148156.81364649036761122.521004867949
Winsorized Mean ( 16 / 36 )836.2962962962966.60615396486913126.593521850026
Winsorized Mean ( 17 / 36 )836.2962962962966.60615396486913126.593521850026
Winsorized Mean ( 18 / 36 )834.629629629636.39155336455934130.583221640233
Winsorized Mean ( 19 / 36 )834.629629629636.39155336455934130.583221640233
Winsorized Mean ( 20 / 36 )838.3333333333335.90465961695575141.978265931873
Winsorized Mean ( 21 / 36 )836.3888888888895.66067475850606147.754273928578
Winsorized Mean ( 22 / 36 )836.3888888888895.66067475850606147.754273928578
Winsorized Mean ( 23 / 36 )836.3888888888895.66067475850606147.754273928578
Winsorized Mean ( 24 / 36 )838.6111111111115.38811804659074155.640820015391
Winsorized Mean ( 25 / 36 )838.6111111111115.38811804659074155.640820015391
Winsorized Mean ( 26 / 36 )838.6111111111115.38811804659074155.640820015391
Winsorized Mean ( 27 / 36 )836.1111111111115.08636612342499164.382801163378
Winsorized Mean ( 28 / 36 )838.7037037037044.77984075929226175.466871374997
Winsorized Mean ( 29 / 36 )838.7037037037044.77984075929226175.466871374997
Winsorized Mean ( 30 / 36 )838.7037037037044.77984075929226175.466871374997
Winsorized Mean ( 31 / 36 )838.7037037037044.77984075929226175.466871374997
Winsorized Mean ( 32 / 36 )838.7037037037044.09326328280977204.898548115866
Winsorized Mean ( 33 / 36 )838.7037037037043.40802250381519246.096879573065
Winsorized Mean ( 34 / 36 )838.7037037037043.40802250381519246.096879573065
Winsorized Mean ( 35 / 36 )838.7037037037043.40802250381519246.096879573065
Winsorized Mean ( 36 / 36 )842.0370370370373.06771184968834274.483744984909
Trimmed Mean ( 1 / 36 )837.5471698113218.9007821625016594.0981539060518
Trimmed Mean ( 2 / 36 )837.4038461538468.6289316485206497.0460632049869
Trimmed Mean ( 3 / 36 )837.1568627450988.34415230641704100.328569278546
Trimmed Mean ( 4 / 36 )836.98.11619530707747103.114817760757
Trimmed Mean ( 5 / 36 )836.7346938775517.88324157914513106.140942844008
Trimmed Mean ( 6 / 36 )836.56257.66746962566702109.105420802658
Trimmed Mean ( 7 / 36 )836.3829787234047.42205907859373112.688806417029
Trimmed Mean ( 8 / 36 )836.3043478260877.22102988543951115.815106860645
Trimmed Mean ( 9 / 36 )836.3333333333337.01781218686688119.172943228439
Trimmed Mean ( 10 / 36 )836.256.81198560317689122.76156303237
Trimmed Mean ( 11 / 36 )836.2790697674426.65763606433964125.612013286039
Trimmed Mean ( 12 / 36 )836.4285714285716.55670105019171127.568508160688
Trimmed Mean ( 13 / 36 )836.4634146341466.46574358795045129.368479163476
Trimmed Mean ( 14 / 36 )836.56.35973289782248131.530681152727
Trimmed Mean ( 15 / 36 )836.6666666666676.26229504385886133.603840254564
Trimmed Mean ( 16 / 36 )836.8421052631586.14791514031251136.118031261671
Trimmed Mean ( 17 / 36 )836.8918918918926.0447720999171138.448874177303
Trimmed Mean ( 18 / 36 )836.9444444444445.92281763486535141.308494713339
Trimmed Mean ( 19 / 36 )837.1428571428575.80976139079082144.092467974645
Trimmed Mean ( 20 / 36 )837.3529411764715.67489754255294147.553843024939
Trimmed Mean ( 21 / 36 )837.2727272727275.5869705838808149.861667374512
Trimmed Mean ( 22 / 36 )837.343755.5153204168566151.821415024376
Trimmed Mean ( 23 / 36 )837.419354838715.42696074259714154.307243880661
Trimmed Mean ( 24 / 36 )837.55.31826083462298157.476292728574
Trimmed Mean ( 25 / 36 )837.4137931034485.22662656179202160.220705115065
Trimmed Mean ( 26 / 36 )837.3214285714295.11231687779603163.785119073528
Trimmed Mean ( 27 / 36 )837.2222222222224.96962588714561168.467856783299
Trimmed Mean ( 28 / 36 )837.3076923076924.8438309930202172.860633146414
Trimmed Mean ( 29 / 36 )837.24.7383799866578176.684859035655
Trimmed Mean ( 30 / 36 )837.0833333333334.60263505059694181.870455539326
Trimmed Mean ( 31 / 36 )836.956521739134.42729309799943189.044751095727
Trimmed Mean ( 32 / 36 )836.8181818181824.19872032343319199.303148901791
Trimmed Mean ( 33 / 36 )836.6666666666674.05632049595826206.26246557695
Trimmed Mean ( 34 / 36 )836.54.01200122708778208.499437725047
Trimmed Mean ( 35 / 36 )836.3157894736843.94523413140158211.981282129022
Trimmed Mean ( 36 / 36 )836.1111111111113.84785608783166217.292718861083
Median830
Midrange855
Midmean - Weighted Average at Xnp833.684210526316
Midmean - Weighted Average at X(n+1)p833.684210526316
Midmean - Empirical Distribution Function833.684210526316
Midmean - Empirical Distribution Function - Averaging833.684210526316
Midmean - Empirical Distribution Function - Interpolation833.684210526316
Midmean - Closest Observation833.684210526316
Midmean - True Basic - Statistics Graphics Toolkit833.684210526316
Midmean - MS Excel (old versions)840.952380952381
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')