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Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 21 Nov 2011 05:54:08 -0500
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/Nov/21/t132187288683sgtxwgopzpdcn.htm/, Retrieved Sat, 20 Apr 2024 13:10:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=145696, Retrieved Sat, 20 Apr 2024 13:10:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [Arabica Price in ...] [2008-01-06 21:28:17] [74be16979710d4c4e7c6647856088456]
- RM D    [Central Tendency] [Paper] [2011-11-21 10:54:08] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-    D      [Central Tendency] [paper] [2011-12-12 10:00:36] [74be16979710d4c4e7c6647856088456]
-    D        [Central Tendency] [paper] [2011-12-12 10:05:55] [74be16979710d4c4e7c6647856088456]
-    D      [Central Tendency] [paper] [2011-12-12 10:18:36] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
 68.897 
 38.683 
 44.720 
 39.525 
 45.315 
 50.380 
 40.600 
 36.279 
 42.438 
 38.064 
 31.879 
 11.379 
 70.249 
 39.253 
 47.060 
 41.697 
 38.708 
 49.267 
 39.018 
 32.228 
 40.870 
 39.383 
 34.571 
 12.066 
 70.938 
 34.077 
 45.409 
 40.809 
 37.013 
 44.953 
 37.848 
 32.745 
 39.401 
 34.931 
 33.008 
 8.620 
 68.906 
 39.556 
 50.669 
 36.432 
 40.891 
 48.428 
 36.222 
 33.425 
 39.401 
 37.967 
 34.801 
 12.657 
 69.116 
 41.519 
 51.321 
 38.529 
 41.547 
 52.073 
 38.401 
 40.898 
 40.439 
 41.888 
 37.898 
 8.771 
 68.184 
 50.530 
 47.221 
 41.756 
 45.633 
 48.138 
 39.486 
 39.341 
 41.117 
 41.629 
 29.722 
 7.054 
 56.676 
 34.870 
 35.117 
 30.169 
 30.936 
 35.699 
 33.228 
 27.733 
 33.666 
 35.429 
 27.438 
 8.170 
 63.410 
 38.040 
 45.389 
 37.353 
 37.024 
 50.957 
 37.994 
 36.454 
 46.080 
 43.373 
 37.395 




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145696&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145696&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145696&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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean39.75207368421051.2952533133062930.6905786503942
Geometric Mean37.0009525427231
Harmonic Mean32.4933788270028
Quadratic Mean41.6884803019277
Winsorized Mean ( 1 / 31 )39.75656842105261.2903055959505230.8117461055924
Winsorized Mean ( 2 / 31 )39.74218947368421.2819428055170631.0015308816015
Winsorized Mean ( 3 / 31 )39.74032631578951.279100347983331.0689668550605
Winsorized Mean ( 4 / 31 )39.84975789473681.2515691311189931.8398376117733
Winsorized Mean ( 5 / 31 )39.84838947368421.2336445521871532.3013540675361
Winsorized Mean ( 6 / 31 )39.58421.1544871687267734.2872585094692
Winsorized Mean ( 7 / 31 )40.17713684210530.81264405495096749.4400181694917
Winsorized Mean ( 8 / 31 )39.81435789473680.73160480874154354.4205798253607
Winsorized Mean ( 9 / 31 )39.93154736842110.68748721853429658.0833305578452
Winsorized Mean ( 10 / 31 )39.94028421052630.67342704648286759.3089992733792
Winsorized Mean ( 11 / 31 )39.9957473684210.65423072885448761.1340091567555
Winsorized Mean ( 12 / 31 )40.09730526315790.63417740903529963.2272684139811
Winsorized Mean ( 13 / 31 )40.12453684210530.62408017506340764.2938815321743
Winsorized Mean ( 14 / 31 )40.03670526315790.58580269904751368.3450337942376
Winsorized Mean ( 15 / 31 )39.94575789473680.55849483525935671.5239521887193
Winsorized Mean ( 16 / 31 )39.93396842105260.54577312442887373.1695399307941
Winsorized Mean ( 17 / 31 )39.80512631578950.51545432340480877.223382380147
Winsorized Mean ( 18 / 31 )39.82028421052630.50482484442901578.8794066891959
Winsorized Mean ( 19 / 31 )39.70648421052630.46492855159481685.4034110710637
Winsorized Mean ( 20 / 31 )39.71637894736840.43810219503987590.6555123371467
Winsorized Mean ( 21 / 31 )39.71770526315790.42470765252969893.5177528038081
Winsorized Mean ( 22 / 31 )39.72905263157890.42208473204223294.1257752663838
Winsorized Mean ( 23 / 31 )39.72590526315790.41772572940974595.1004510047571
Winsorized Mean ( 24 / 31 )39.68144210526320.39906118179052199.4369884016761
Winsorized Mean ( 25 / 31 )39.70223157894740.380550637313065104.328380210505
Winsorized Mean ( 26 / 31 )39.40747368421050.321423773691158122.60285924611
Winsorized Mean ( 27 / 31 )39.29037894736840.269236386966832145.932648220423
Winsorized Mean ( 28 / 31 )39.14507368421050.247526192011501158.145177955114
Winsorized Mean ( 29 / 31 )39.15148421052630.237068926933009165.148105730405
Winsorized Mean ( 30 / 31 )39.13980.234049325110214167.228852215528
Winsorized Mean ( 31 / 31 )39.30002105263160.209703881758064187.407217850035
Trimmed Mean ( 1 / 31 )39.76833333333331.2297894902599232.3375127599507
Trimmed Mean ( 2 / 31 )39.78061538461541.1595756551712134.3061836519341
Trimmed Mean ( 3 / 31 )39.80112359550561.082690464861436.7613134937886
Trimmed Mean ( 4 / 31 )39.82325287356320.99254178147624940.1224952105617
Trimmed Mean ( 5 / 31 )39.81584705882350.89477540873365444.4981463171564
Trimmed Mean ( 6 / 31 )39.80839759036140.78008168550998851.0310629384104
Trimmed Mean ( 7 / 31 )39.80839759036140.66286510251770160.055051079263
Trimmed Mean ( 8 / 31 )39.79640506329110.62536579273427263.6370033757208
Trimmed Mean ( 9 / 31 )39.79363636363640.60098012874239966.2145626127571
Trimmed Mean ( 10 / 31 )39.77422666666670.58189845421466668.3525216102288
Trimmed Mean ( 11 / 31 )39.75261643835620.56231091211500970.6950827058209
Trimmed Mean ( 12 / 31 )39.72304225352110.54291691262914373.1659694688039
Trimmed Mean ( 13 / 31 )39.68010144927540.52363258007825275.7785190588133
Trimmed Mean ( 14 / 31 )39.68010144927540.50244212775144978.974471402017
Trimmed Mean ( 15 / 31 )39.58933846153850.48435702238445681.7358614243744
Trimmed Mean ( 16 / 31 )39.55350793650790.46770411940045684.5695094309007
Trimmed Mean ( 17 / 31 )39.51647540983610.4498442751843787.8447889408842
Trimmed Mean ( 18 / 31 )39.48913559322030.43385622853133591.0189435954318
Trimmed Mean ( 19 / 31 )39.45847368421050.41617017068527494.8133154743826
Trimmed Mean ( 20 / 31 )39.43592727272730.40202096604668398.0942055349122
Trimmed Mean ( 21 / 31 )39.41079245283020.389404868907977101.207754703611
Trimmed Mean ( 22 / 31 )39.3835686274510.376069849847909104.724078900179
Trimmed Mean ( 23 / 31 )39.35312244897960.359610420385081109.432653277508
Trimmed Mean ( 24 / 31 )39.32036170212770.339375707563068115.860861063017
Trimmed Mean ( 25 / 31 )39.28860.317479000180414123.751807135821
Trimmed Mean ( 26 / 31 )39.25204651162790.293068597100234133.934672291768
Trimmed Mean ( 27 / 31 )39.23819512195120.276632225296649141.842459170741
Trimmed Mean ( 28 / 31 )39.23819512195120.267649068966215146.603144458927
Trimmed Mean ( 29 / 31 )39.24159459459460.26049548957569150.642126888698
Trimmed Mean ( 30 / 31 )39.25002857142860.252995793254674155.141032451548
Trimmed Mean ( 31 / 31 )39.26060606060610.243006421926123161.562010375766
Median39.341
Midrange38.996
Midmean - Weighted Average at Xnp39.2289166666667
Midmean - Weighted Average at X(n+1)p39.3531224489796
Midmean - Empirical Distribution Function39.3531224489796
Midmean - Empirical Distribution Function - Averaging39.3531224489796
Midmean - Empirical Distribution Function - Interpolation39.3203617021277
Midmean - Closest Observation39.2289166666667
Midmean - True Basic - Statistics Graphics Toolkit39.3531224489796
Midmean - MS Excel (old versions)39.3531224489796
Number of observations95

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 39.7520736842105 & 1.29525331330629 & 30.6905786503942 \tabularnewline
Geometric Mean & 37.0009525427231 &  &  \tabularnewline
Harmonic Mean & 32.4933788270028 &  &  \tabularnewline
Quadratic Mean & 41.6884803019277 &  &  \tabularnewline
Winsorized Mean ( 1 / 31 ) & 39.7565684210526 & 1.29030559595052 & 30.8117461055924 \tabularnewline
Winsorized Mean ( 2 / 31 ) & 39.7421894736842 & 1.28194280551706 & 31.0015308816015 \tabularnewline
Winsorized Mean ( 3 / 31 ) & 39.7403263157895 & 1.2791003479833 & 31.0689668550605 \tabularnewline
Winsorized Mean ( 4 / 31 ) & 39.8497578947368 & 1.25156913111899 & 31.8398376117733 \tabularnewline
Winsorized Mean ( 5 / 31 ) & 39.8483894736842 & 1.23364455218715 & 32.3013540675361 \tabularnewline
Winsorized Mean ( 6 / 31 ) & 39.5842 & 1.15448716872677 & 34.2872585094692 \tabularnewline
Winsorized Mean ( 7 / 31 ) & 40.1771368421053 & 0.812644054950967 & 49.4400181694917 \tabularnewline
Winsorized Mean ( 8 / 31 ) & 39.8143578947368 & 0.731604808741543 & 54.4205798253607 \tabularnewline
Winsorized Mean ( 9 / 31 ) & 39.9315473684211 & 0.687487218534296 & 58.0833305578452 \tabularnewline
Winsorized Mean ( 10 / 31 ) & 39.9402842105263 & 0.673427046482867 & 59.3089992733792 \tabularnewline
Winsorized Mean ( 11 / 31 ) & 39.995747368421 & 0.654230728854487 & 61.1340091567555 \tabularnewline
Winsorized Mean ( 12 / 31 ) & 40.0973052631579 & 0.634177409035299 & 63.2272684139811 \tabularnewline
Winsorized Mean ( 13 / 31 ) & 40.1245368421053 & 0.624080175063407 & 64.2938815321743 \tabularnewline
Winsorized Mean ( 14 / 31 ) & 40.0367052631579 & 0.585802699047513 & 68.3450337942376 \tabularnewline
Winsorized Mean ( 15 / 31 ) & 39.9457578947368 & 0.558494835259356 & 71.5239521887193 \tabularnewline
Winsorized Mean ( 16 / 31 ) & 39.9339684210526 & 0.545773124428873 & 73.1695399307941 \tabularnewline
Winsorized Mean ( 17 / 31 ) & 39.8051263157895 & 0.515454323404808 & 77.223382380147 \tabularnewline
Winsorized Mean ( 18 / 31 ) & 39.8202842105263 & 0.504824844429015 & 78.8794066891959 \tabularnewline
Winsorized Mean ( 19 / 31 ) & 39.7064842105263 & 0.464928551594816 & 85.4034110710637 \tabularnewline
Winsorized Mean ( 20 / 31 ) & 39.7163789473684 & 0.438102195039875 & 90.6555123371467 \tabularnewline
Winsorized Mean ( 21 / 31 ) & 39.7177052631579 & 0.424707652529698 & 93.5177528038081 \tabularnewline
Winsorized Mean ( 22 / 31 ) & 39.7290526315789 & 0.422084732042232 & 94.1257752663838 \tabularnewline
Winsorized Mean ( 23 / 31 ) & 39.7259052631579 & 0.417725729409745 & 95.1004510047571 \tabularnewline
Winsorized Mean ( 24 / 31 ) & 39.6814421052632 & 0.399061181790521 & 99.4369884016761 \tabularnewline
Winsorized Mean ( 25 / 31 ) & 39.7022315789474 & 0.380550637313065 & 104.328380210505 \tabularnewline
Winsorized Mean ( 26 / 31 ) & 39.4074736842105 & 0.321423773691158 & 122.60285924611 \tabularnewline
Winsorized Mean ( 27 / 31 ) & 39.2903789473684 & 0.269236386966832 & 145.932648220423 \tabularnewline
Winsorized Mean ( 28 / 31 ) & 39.1450736842105 & 0.247526192011501 & 158.145177955114 \tabularnewline
Winsorized Mean ( 29 / 31 ) & 39.1514842105263 & 0.237068926933009 & 165.148105730405 \tabularnewline
Winsorized Mean ( 30 / 31 ) & 39.1398 & 0.234049325110214 & 167.228852215528 \tabularnewline
Winsorized Mean ( 31 / 31 ) & 39.3000210526316 & 0.209703881758064 & 187.407217850035 \tabularnewline
Trimmed Mean ( 1 / 31 ) & 39.7683333333333 & 1.22978949025992 & 32.3375127599507 \tabularnewline
Trimmed Mean ( 2 / 31 ) & 39.7806153846154 & 1.15957565517121 & 34.3061836519341 \tabularnewline
Trimmed Mean ( 3 / 31 ) & 39.8011235955056 & 1.0826904648614 & 36.7613134937886 \tabularnewline
Trimmed Mean ( 4 / 31 ) & 39.8232528735632 & 0.992541781476249 & 40.1224952105617 \tabularnewline
Trimmed Mean ( 5 / 31 ) & 39.8158470588235 & 0.894775408733654 & 44.4981463171564 \tabularnewline
Trimmed Mean ( 6 / 31 ) & 39.8083975903614 & 0.780081685509988 & 51.0310629384104 \tabularnewline
Trimmed Mean ( 7 / 31 ) & 39.8083975903614 & 0.662865102517701 & 60.055051079263 \tabularnewline
Trimmed Mean ( 8 / 31 ) & 39.7964050632911 & 0.625365792734272 & 63.6370033757208 \tabularnewline
Trimmed Mean ( 9 / 31 ) & 39.7936363636364 & 0.600980128742399 & 66.2145626127571 \tabularnewline
Trimmed Mean ( 10 / 31 ) & 39.7742266666667 & 0.581898454214666 & 68.3525216102288 \tabularnewline
Trimmed Mean ( 11 / 31 ) & 39.7526164383562 & 0.562310912115009 & 70.6950827058209 \tabularnewline
Trimmed Mean ( 12 / 31 ) & 39.7230422535211 & 0.542916912629143 & 73.1659694688039 \tabularnewline
Trimmed Mean ( 13 / 31 ) & 39.6801014492754 & 0.523632580078252 & 75.7785190588133 \tabularnewline
Trimmed Mean ( 14 / 31 ) & 39.6801014492754 & 0.502442127751449 & 78.974471402017 \tabularnewline
Trimmed Mean ( 15 / 31 ) & 39.5893384615385 & 0.484357022384456 & 81.7358614243744 \tabularnewline
Trimmed Mean ( 16 / 31 ) & 39.5535079365079 & 0.467704119400456 & 84.5695094309007 \tabularnewline
Trimmed Mean ( 17 / 31 ) & 39.5164754098361 & 0.44984427518437 & 87.8447889408842 \tabularnewline
Trimmed Mean ( 18 / 31 ) & 39.4891355932203 & 0.433856228531335 & 91.0189435954318 \tabularnewline
Trimmed Mean ( 19 / 31 ) & 39.4584736842105 & 0.416170170685274 & 94.8133154743826 \tabularnewline
Trimmed Mean ( 20 / 31 ) & 39.4359272727273 & 0.402020966046683 & 98.0942055349122 \tabularnewline
Trimmed Mean ( 21 / 31 ) & 39.4107924528302 & 0.389404868907977 & 101.207754703611 \tabularnewline
Trimmed Mean ( 22 / 31 ) & 39.383568627451 & 0.376069849847909 & 104.724078900179 \tabularnewline
Trimmed Mean ( 23 / 31 ) & 39.3531224489796 & 0.359610420385081 & 109.432653277508 \tabularnewline
Trimmed Mean ( 24 / 31 ) & 39.3203617021277 & 0.339375707563068 & 115.860861063017 \tabularnewline
Trimmed Mean ( 25 / 31 ) & 39.2886 & 0.317479000180414 & 123.751807135821 \tabularnewline
Trimmed Mean ( 26 / 31 ) & 39.2520465116279 & 0.293068597100234 & 133.934672291768 \tabularnewline
Trimmed Mean ( 27 / 31 ) & 39.2381951219512 & 0.276632225296649 & 141.842459170741 \tabularnewline
Trimmed Mean ( 28 / 31 ) & 39.2381951219512 & 0.267649068966215 & 146.603144458927 \tabularnewline
Trimmed Mean ( 29 / 31 ) & 39.2415945945946 & 0.26049548957569 & 150.642126888698 \tabularnewline
Trimmed Mean ( 30 / 31 ) & 39.2500285714286 & 0.252995793254674 & 155.141032451548 \tabularnewline
Trimmed Mean ( 31 / 31 ) & 39.2606060606061 & 0.243006421926123 & 161.562010375766 \tabularnewline
Median & 39.341 &  &  \tabularnewline
Midrange & 38.996 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 39.2289166666667 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 39.3531224489796 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 39.3531224489796 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 39.3531224489796 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 39.3203617021277 &  &  \tabularnewline
Midmean - Closest Observation & 39.2289166666667 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 39.3531224489796 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 39.3531224489796 &  &  \tabularnewline
Number of observations & 95 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145696&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]39.7520736842105[/C][C]1.29525331330629[/C][C]30.6905786503942[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]37.0009525427231[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]32.4933788270028[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]41.6884803019277[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 31 )[/C][C]39.7565684210526[/C][C]1.29030559595052[/C][C]30.8117461055924[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 31 )[/C][C]39.7421894736842[/C][C]1.28194280551706[/C][C]31.0015308816015[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 31 )[/C][C]39.7403263157895[/C][C]1.2791003479833[/C][C]31.0689668550605[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 31 )[/C][C]39.8497578947368[/C][C]1.25156913111899[/C][C]31.8398376117733[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 31 )[/C][C]39.8483894736842[/C][C]1.23364455218715[/C][C]32.3013540675361[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 31 )[/C][C]39.5842[/C][C]1.15448716872677[/C][C]34.2872585094692[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 31 )[/C][C]40.1771368421053[/C][C]0.812644054950967[/C][C]49.4400181694917[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 31 )[/C][C]39.8143578947368[/C][C]0.731604808741543[/C][C]54.4205798253607[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 31 )[/C][C]39.9315473684211[/C][C]0.687487218534296[/C][C]58.0833305578452[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 31 )[/C][C]39.9402842105263[/C][C]0.673427046482867[/C][C]59.3089992733792[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 31 )[/C][C]39.995747368421[/C][C]0.654230728854487[/C][C]61.1340091567555[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 31 )[/C][C]40.0973052631579[/C][C]0.634177409035299[/C][C]63.2272684139811[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 31 )[/C][C]40.1245368421053[/C][C]0.624080175063407[/C][C]64.2938815321743[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 31 )[/C][C]40.0367052631579[/C][C]0.585802699047513[/C][C]68.3450337942376[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 31 )[/C][C]39.9457578947368[/C][C]0.558494835259356[/C][C]71.5239521887193[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 31 )[/C][C]39.9339684210526[/C][C]0.545773124428873[/C][C]73.1695399307941[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 31 )[/C][C]39.8051263157895[/C][C]0.515454323404808[/C][C]77.223382380147[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 31 )[/C][C]39.8202842105263[/C][C]0.504824844429015[/C][C]78.8794066891959[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 31 )[/C][C]39.7064842105263[/C][C]0.464928551594816[/C][C]85.4034110710637[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 31 )[/C][C]39.7163789473684[/C][C]0.438102195039875[/C][C]90.6555123371467[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 31 )[/C][C]39.7177052631579[/C][C]0.424707652529698[/C][C]93.5177528038081[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 31 )[/C][C]39.7290526315789[/C][C]0.422084732042232[/C][C]94.1257752663838[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 31 )[/C][C]39.7259052631579[/C][C]0.417725729409745[/C][C]95.1004510047571[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 31 )[/C][C]39.6814421052632[/C][C]0.399061181790521[/C][C]99.4369884016761[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 31 )[/C][C]39.7022315789474[/C][C]0.380550637313065[/C][C]104.328380210505[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 31 )[/C][C]39.4074736842105[/C][C]0.321423773691158[/C][C]122.60285924611[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 31 )[/C][C]39.2903789473684[/C][C]0.269236386966832[/C][C]145.932648220423[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 31 )[/C][C]39.1450736842105[/C][C]0.247526192011501[/C][C]158.145177955114[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 31 )[/C][C]39.1514842105263[/C][C]0.237068926933009[/C][C]165.148105730405[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 31 )[/C][C]39.1398[/C][C]0.234049325110214[/C][C]167.228852215528[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 31 )[/C][C]39.3000210526316[/C][C]0.209703881758064[/C][C]187.407217850035[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 31 )[/C][C]39.7683333333333[/C][C]1.22978949025992[/C][C]32.3375127599507[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 31 )[/C][C]39.7806153846154[/C][C]1.15957565517121[/C][C]34.3061836519341[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 31 )[/C][C]39.8011235955056[/C][C]1.0826904648614[/C][C]36.7613134937886[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 31 )[/C][C]39.8232528735632[/C][C]0.992541781476249[/C][C]40.1224952105617[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 31 )[/C][C]39.8158470588235[/C][C]0.894775408733654[/C][C]44.4981463171564[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 31 )[/C][C]39.8083975903614[/C][C]0.780081685509988[/C][C]51.0310629384104[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 31 )[/C][C]39.8083975903614[/C][C]0.662865102517701[/C][C]60.055051079263[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 31 )[/C][C]39.7964050632911[/C][C]0.625365792734272[/C][C]63.6370033757208[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 31 )[/C][C]39.7936363636364[/C][C]0.600980128742399[/C][C]66.2145626127571[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 31 )[/C][C]39.7742266666667[/C][C]0.581898454214666[/C][C]68.3525216102288[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 31 )[/C][C]39.7526164383562[/C][C]0.562310912115009[/C][C]70.6950827058209[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 31 )[/C][C]39.7230422535211[/C][C]0.542916912629143[/C][C]73.1659694688039[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 31 )[/C][C]39.6801014492754[/C][C]0.523632580078252[/C][C]75.7785190588133[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 31 )[/C][C]39.6801014492754[/C][C]0.502442127751449[/C][C]78.974471402017[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 31 )[/C][C]39.5893384615385[/C][C]0.484357022384456[/C][C]81.7358614243744[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 31 )[/C][C]39.5535079365079[/C][C]0.467704119400456[/C][C]84.5695094309007[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 31 )[/C][C]39.5164754098361[/C][C]0.44984427518437[/C][C]87.8447889408842[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 31 )[/C][C]39.4891355932203[/C][C]0.433856228531335[/C][C]91.0189435954318[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 31 )[/C][C]39.4584736842105[/C][C]0.416170170685274[/C][C]94.8133154743826[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 31 )[/C][C]39.4359272727273[/C][C]0.402020966046683[/C][C]98.0942055349122[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 31 )[/C][C]39.4107924528302[/C][C]0.389404868907977[/C][C]101.207754703611[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 31 )[/C][C]39.383568627451[/C][C]0.376069849847909[/C][C]104.724078900179[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 31 )[/C][C]39.3531224489796[/C][C]0.359610420385081[/C][C]109.432653277508[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 31 )[/C][C]39.3203617021277[/C][C]0.339375707563068[/C][C]115.860861063017[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 31 )[/C][C]39.2886[/C][C]0.317479000180414[/C][C]123.751807135821[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 31 )[/C][C]39.2520465116279[/C][C]0.293068597100234[/C][C]133.934672291768[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 31 )[/C][C]39.2381951219512[/C][C]0.276632225296649[/C][C]141.842459170741[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 31 )[/C][C]39.2381951219512[/C][C]0.267649068966215[/C][C]146.603144458927[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 31 )[/C][C]39.2415945945946[/C][C]0.26049548957569[/C][C]150.642126888698[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 31 )[/C][C]39.2500285714286[/C][C]0.252995793254674[/C][C]155.141032451548[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 31 )[/C][C]39.2606060606061[/C][C]0.243006421926123[/C][C]161.562010375766[/C][/ROW]
[ROW][C]Median[/C][C]39.341[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]38.996[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]39.2289166666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]39.3531224489796[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]39.3531224489796[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]39.3531224489796[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]39.3203617021277[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]39.2289166666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]39.3531224489796[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]39.3531224489796[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]95[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145696&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145696&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 Mean39.75207368421051.2952533133062930.6905786503942
Geometric Mean37.0009525427231
Harmonic Mean32.4933788270028
Quadratic Mean41.6884803019277
Winsorized Mean ( 1 / 31 )39.75656842105261.2903055959505230.8117461055924
Winsorized Mean ( 2 / 31 )39.74218947368421.2819428055170631.0015308816015
Winsorized Mean ( 3 / 31 )39.74032631578951.279100347983331.0689668550605
Winsorized Mean ( 4 / 31 )39.84975789473681.2515691311189931.8398376117733
Winsorized Mean ( 5 / 31 )39.84838947368421.2336445521871532.3013540675361
Winsorized Mean ( 6 / 31 )39.58421.1544871687267734.2872585094692
Winsorized Mean ( 7 / 31 )40.17713684210530.81264405495096749.4400181694917
Winsorized Mean ( 8 / 31 )39.81435789473680.73160480874154354.4205798253607
Winsorized Mean ( 9 / 31 )39.93154736842110.68748721853429658.0833305578452
Winsorized Mean ( 10 / 31 )39.94028421052630.67342704648286759.3089992733792
Winsorized Mean ( 11 / 31 )39.9957473684210.65423072885448761.1340091567555
Winsorized Mean ( 12 / 31 )40.09730526315790.63417740903529963.2272684139811
Winsorized Mean ( 13 / 31 )40.12453684210530.62408017506340764.2938815321743
Winsorized Mean ( 14 / 31 )40.03670526315790.58580269904751368.3450337942376
Winsorized Mean ( 15 / 31 )39.94575789473680.55849483525935671.5239521887193
Winsorized Mean ( 16 / 31 )39.93396842105260.54577312442887373.1695399307941
Winsorized Mean ( 17 / 31 )39.80512631578950.51545432340480877.223382380147
Winsorized Mean ( 18 / 31 )39.82028421052630.50482484442901578.8794066891959
Winsorized Mean ( 19 / 31 )39.70648421052630.46492855159481685.4034110710637
Winsorized Mean ( 20 / 31 )39.71637894736840.43810219503987590.6555123371467
Winsorized Mean ( 21 / 31 )39.71770526315790.42470765252969893.5177528038081
Winsorized Mean ( 22 / 31 )39.72905263157890.42208473204223294.1257752663838
Winsorized Mean ( 23 / 31 )39.72590526315790.41772572940974595.1004510047571
Winsorized Mean ( 24 / 31 )39.68144210526320.39906118179052199.4369884016761
Winsorized Mean ( 25 / 31 )39.70223157894740.380550637313065104.328380210505
Winsorized Mean ( 26 / 31 )39.40747368421050.321423773691158122.60285924611
Winsorized Mean ( 27 / 31 )39.29037894736840.269236386966832145.932648220423
Winsorized Mean ( 28 / 31 )39.14507368421050.247526192011501158.145177955114
Winsorized Mean ( 29 / 31 )39.15148421052630.237068926933009165.148105730405
Winsorized Mean ( 30 / 31 )39.13980.234049325110214167.228852215528
Winsorized Mean ( 31 / 31 )39.30002105263160.209703881758064187.407217850035
Trimmed Mean ( 1 / 31 )39.76833333333331.2297894902599232.3375127599507
Trimmed Mean ( 2 / 31 )39.78061538461541.1595756551712134.3061836519341
Trimmed Mean ( 3 / 31 )39.80112359550561.082690464861436.7613134937886
Trimmed Mean ( 4 / 31 )39.82325287356320.99254178147624940.1224952105617
Trimmed Mean ( 5 / 31 )39.81584705882350.89477540873365444.4981463171564
Trimmed Mean ( 6 / 31 )39.80839759036140.78008168550998851.0310629384104
Trimmed Mean ( 7 / 31 )39.80839759036140.66286510251770160.055051079263
Trimmed Mean ( 8 / 31 )39.79640506329110.62536579273427263.6370033757208
Trimmed Mean ( 9 / 31 )39.79363636363640.60098012874239966.2145626127571
Trimmed Mean ( 10 / 31 )39.77422666666670.58189845421466668.3525216102288
Trimmed Mean ( 11 / 31 )39.75261643835620.56231091211500970.6950827058209
Trimmed Mean ( 12 / 31 )39.72304225352110.54291691262914373.1659694688039
Trimmed Mean ( 13 / 31 )39.68010144927540.52363258007825275.7785190588133
Trimmed Mean ( 14 / 31 )39.68010144927540.50244212775144978.974471402017
Trimmed Mean ( 15 / 31 )39.58933846153850.48435702238445681.7358614243744
Trimmed Mean ( 16 / 31 )39.55350793650790.46770411940045684.5695094309007
Trimmed Mean ( 17 / 31 )39.51647540983610.4498442751843787.8447889408842
Trimmed Mean ( 18 / 31 )39.48913559322030.43385622853133591.0189435954318
Trimmed Mean ( 19 / 31 )39.45847368421050.41617017068527494.8133154743826
Trimmed Mean ( 20 / 31 )39.43592727272730.40202096604668398.0942055349122
Trimmed Mean ( 21 / 31 )39.41079245283020.389404868907977101.207754703611
Trimmed Mean ( 22 / 31 )39.3835686274510.376069849847909104.724078900179
Trimmed Mean ( 23 / 31 )39.35312244897960.359610420385081109.432653277508
Trimmed Mean ( 24 / 31 )39.32036170212770.339375707563068115.860861063017
Trimmed Mean ( 25 / 31 )39.28860.317479000180414123.751807135821
Trimmed Mean ( 26 / 31 )39.25204651162790.293068597100234133.934672291768
Trimmed Mean ( 27 / 31 )39.23819512195120.276632225296649141.842459170741
Trimmed Mean ( 28 / 31 )39.23819512195120.267649068966215146.603144458927
Trimmed Mean ( 29 / 31 )39.24159459459460.26049548957569150.642126888698
Trimmed Mean ( 30 / 31 )39.25002857142860.252995793254674155.141032451548
Trimmed Mean ( 31 / 31 )39.26060606060610.243006421926123161.562010375766
Median39.341
Midrange38.996
Midmean - Weighted Average at Xnp39.2289166666667
Midmean - Weighted Average at X(n+1)p39.3531224489796
Midmean - Empirical Distribution Function39.3531224489796
Midmean - Empirical Distribution Function - Averaging39.3531224489796
Midmean - Empirical Distribution Function - Interpolation39.3203617021277
Midmean - Closest Observation39.2289166666667
Midmean - True Basic - Statistics Graphics Toolkit39.3531224489796
Midmean - MS Excel (old versions)39.3531224489796
Number of observations95



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')