Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 04 Oct 2010 17:49:34 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Oct/04/t1286214612xhkiesdkkx9bkj2.htm/, Retrieved Sat, 27 Apr 2024 21:11:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=80790, Retrieved Sat, 27 Apr 2024 21:11:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Central Tendency] [Time needed to su...] [2010-09-25 09:42:08] [b98453cac15ba1066b407e146608df68]
F R PD    [Central Tendency] [Measures of Centr...] [2010-10-04 17:49:34] [c6b3e187a4a1689d42fffda4bc860ab5] [Current]
Feedback Forum
2010-10-10 10:34:24 [37cb2a73da68cb48cd3975816b6b767a] [reply
Gegevens interpreteren, niet herberekenen.

Normaal neem je inderdaad het rekenkundig gemiddelde maar dit is niet de betere oplossing in deze oefening.

In deze oplossing nemen we de Median (241.17)

2010-10-12 14:11:36 [Tom Eysackers] [reply
Het gemiddelde(333) is veel gevoeliger voor outliers dan de mediaan(241) en bijgevolg is de mediaan een betere schatting.

Post a new message
Dataseries X:
8.95
57.47
86.58
137.55
171.26
236.71
239.89
252.64
259.7
308.16
324.04
388.3
392.25
440.31
694.87
756.46
4813
33999
37028
39047
59609
62156
64016
70939
72844
85094
103898
109215
131812
136452
136813
140321
150034
156187
158047
169861
171328
180818
183186
183613
184641
187881
190157
190379
191835
192797
193299
197549
198296
199297
199746
200156
203077
204386
206771
206893
207533
208108
211655
213361
213511
213923
216046
216548
216886
217465
218761
220553
221588
223166
226731
229641
232444
232669
235577
236302
238502
240755
241171
242205
242344
246542
249148
250407
251422
257102
257567
260642
261596
262517
262875
263906
265777
266793
274482
275562
278741
287069
289714
293671
295281
308174
308532
313906
315955
330563
348821
350089
356725
366936
380155
380531
383703
386688
401422
401915
403064
403556
406167
421403
426113
435956
438555
441437
449594
475834
506652
556277
601162
611281
645285
653641
662883
699645
947293
1030944
1305923
2763544
4202361




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=80790&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=80790&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=80790&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'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean234254.3076923087145.6682509782432.7827012764325
Geometric Mean223833.163772138
Harmonic Mean212038.924447132
Quadratic Mean243865.808181827
Winsorized Mean ( 1 / 30 )234227.0109890117072.5573500997833.1177252292916
Winsorized Mean ( 2 / 30 )234574.6813186816965.3684710469733.677282442952
Winsorized Mean ( 3 / 30 )234645.3956043966904.6926676108133.9834670274453
Winsorized Mean ( 4 / 30 )235622.1428571436715.0176297174935.0888345868804
Winsorized Mean ( 5 / 30 )235150.7692307696502.9121033166436.1608407886732
Winsorized Mean ( 6 / 30 )234501.3186813196351.0465296056436.9232562835403
Winsorized Mean ( 7 / 30 )234260.7032967036197.665168140737.7982186744983
Winsorized Mean ( 8 / 30 )235003.1208791216035.6598673543538.9357793586422
Winsorized Mean ( 9 / 30 )233805.9230769235577.1788872137841.9218977560404
Winsorized Mean ( 10 / 30 )232405.0439560445248.2139223806544.2826926251936
Winsorized Mean ( 11 / 30 )233585.4285714294990.1668868895846.8091416311378
Winsorized Mean ( 12 / 30 )233070.2197802204837.9181583771848.1757260355145
Winsorized Mean ( 13 / 30 )234374.7912087914645.8398832593450.448314427135
Winsorized Mean ( 14 / 30 )232755.5604395604261.676291780554.6159643538568
Winsorized Mean ( 15 / 30 )232560.5604395604209.545348296855.2460043062977
Winsorized Mean ( 16 / 30 )232045.5714285714075.3600174799256.9386681012936
Winsorized Mean ( 17 / 30 )232156.7252747253920.9552294214259.209226244846
Winsorized Mean ( 18 / 30 )230959.6263736263615.062772922963.8881371863117
Winsorized Mean ( 19 / 30 )230342.2307692313513.0047490442665.568437057165
Winsorized Mean ( 20 / 30 )230424.8681318683438.960147525167.0042275126964
Winsorized Mean ( 21 / 30 )228872.4835164843166.3940839829972.2817430319938
Winsorized Mean ( 22 / 30 )228748.2197802203118.5015703302073.3519655582533
Winsorized Mean ( 23 / 30 )229349.5054945052923.4011517594278.4529709022224
Winsorized Mean ( 24 / 30 )229274.6043956042864.0760186328480.0518571797715
Winsorized Mean ( 25 / 30 )229451.2527472532818.3832420027381.4123676750951
Winsorized Mean ( 26 / 30 )229316.3956043962768.9520424083482.8170340591903
Winsorized Mean ( 27 / 30 )229154.9890109892717.9736370943884.3109682461691
Winsorized Mean ( 28 / 30 )229107.6043956042491.511887673391.9552523626756
Winsorized Mean ( 29 / 30 )229376.5714285712424.5900088769694.6042714804452
Winsorized Mean ( 30 / 30 )228290.3076923082100.99689738144108.658088918092
Trimmed Mean ( 1 / 30 )234189.6179775286819.0853249107434.3432596629950
Trimmed Mean ( 2 / 30 )234150.5057471266526.548266628435.87662209508
Trimmed Mean ( 3 / 30 )233923.4470588246255.1488155681537.3969435349999
Trimmed Mean ( 4 / 30 )233659.6024096395966.8274601214839.1597719175344
Trimmed Mean ( 5 / 30 )233108.3950617285698.924740731240.9039258573924
Trimmed Mean ( 6 / 30 )232637.8734177225452.3696573167442.667296613966
Trimmed Mean ( 7 / 30 )232270.8311688315205.8711522007544.6170918138533
Trimmed Mean ( 8 / 30 )231925.924954.7645666110246.8086660591087
Trimmed Mean ( 9 / 30 )231446.4246575344695.1037508987949.2952737441059
Trimmed Mean ( 10 / 30 )231110.4084507044493.8403419732151.4282642158189
Trimmed Mean ( 11 / 30 )230939.6666666674326.5149605699153.3777575650047
Trimmed Mean ( 12 / 30 )230612.9850746274178.4895006187255.1905144288335
Trimmed Mean ( 13 / 30 )230326.3076923084031.5969162548157.1302916627566
Trimmed Mean ( 14 / 30 )229876.4761904763889.5271733576259.1013935485727
Trimmed Mean ( 15 / 30 )229569.688524593792.000544541660.5405209804214
Trimmed Mean ( 16 / 30 )229262.1525423733682.3598114145462.2595738286379
Trimmed Mean ( 17 / 30 )228984.4210526323573.0681234064664.086217543013
Trimmed Mean ( 18 / 30 )228675.6727272733466.1967262141865.9730796575517
Trimmed Mean ( 19 / 30 )228457.8113207553390.9714780026467.3723777397625
Trimmed Mean ( 20 / 30 )228280.8431372553314.8498478841768.8661187121233
Trimmed Mean ( 21 / 30 )228081.7551020413231.1197221109770.5890758368525
Trimmed Mean ( 22 / 30 )228008.8510638303176.2424993081771.7857188528563
Trimmed Mean ( 23 / 30 )227940.8888888893112.3700576862773.2370780672333
Trimmed Mean ( 24 / 30 )227811.2790697673064.6485125286374.3352061870877
Trimmed Mean ( 25 / 30 )227675.9512195123010.2175849059675.6343834947813
Trimmed Mean ( 26 / 30 )227510.2564102562943.5051632438377.292290583086
Trimmed Mean ( 27 / 30 )227339.4054054052861.4930896109379.4478261124568
Trimmed Mean ( 28 / 30 )227164.5714285712758.8719989087182.3396560327655
Trimmed Mean ( 29 / 30 )227164.5714285712674.1978288731784.9468087124625
Trimmed Mean ( 30 / 30 )226729.9354838712567.8006224043988.2973286576936
Median223166
Midrange237133
Midmean - Weighted Average at Xnp227187.804347826
Midmean - Weighted Average at X(n+1)p228008.851063830
Midmean - Empirical Distribution Function228008.851063830
Midmean - Empirical Distribution Function - Averaging228008.851063830
Midmean - Empirical Distribution Function - Interpolation227940.888888889
Midmean - Closest Observation227187.804347826
Midmean - True Basic - Statistics Graphics Toolkit228008.851063830
Midmean - MS Excel (old versions)228008.851063830
Number of observations91

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 234254.307692308 & 7145.66825097824 & 32.7827012764325 \tabularnewline
Geometric Mean & 223833.163772138 &  &  \tabularnewline
Harmonic Mean & 212038.924447132 &  &  \tabularnewline
Quadratic Mean & 243865.808181827 &  &  \tabularnewline
Winsorized Mean ( 1 / 30 ) & 234227.010989011 & 7072.55735009978 & 33.1177252292916 \tabularnewline
Winsorized Mean ( 2 / 30 ) & 234574.681318681 & 6965.36847104697 & 33.677282442952 \tabularnewline
Winsorized Mean ( 3 / 30 ) & 234645.395604396 & 6904.69266761081 & 33.9834670274453 \tabularnewline
Winsorized Mean ( 4 / 30 ) & 235622.142857143 & 6715.01762971749 & 35.0888345868804 \tabularnewline
Winsorized Mean ( 5 / 30 ) & 235150.769230769 & 6502.91210331664 & 36.1608407886732 \tabularnewline
Winsorized Mean ( 6 / 30 ) & 234501.318681319 & 6351.04652960564 & 36.9232562835403 \tabularnewline
Winsorized Mean ( 7 / 30 ) & 234260.703296703 & 6197.6651681407 & 37.7982186744983 \tabularnewline
Winsorized Mean ( 8 / 30 ) & 235003.120879121 & 6035.65986735435 & 38.9357793586422 \tabularnewline
Winsorized Mean ( 9 / 30 ) & 233805.923076923 & 5577.17888721378 & 41.9218977560404 \tabularnewline
Winsorized Mean ( 10 / 30 ) & 232405.043956044 & 5248.21392238065 & 44.2826926251936 \tabularnewline
Winsorized Mean ( 11 / 30 ) & 233585.428571429 & 4990.16688688958 & 46.8091416311378 \tabularnewline
Winsorized Mean ( 12 / 30 ) & 233070.219780220 & 4837.91815837718 & 48.1757260355145 \tabularnewline
Winsorized Mean ( 13 / 30 ) & 234374.791208791 & 4645.83988325934 & 50.448314427135 \tabularnewline
Winsorized Mean ( 14 / 30 ) & 232755.560439560 & 4261.6762917805 & 54.6159643538568 \tabularnewline
Winsorized Mean ( 15 / 30 ) & 232560.560439560 & 4209.5453482968 & 55.2460043062977 \tabularnewline
Winsorized Mean ( 16 / 30 ) & 232045.571428571 & 4075.36001747992 & 56.9386681012936 \tabularnewline
Winsorized Mean ( 17 / 30 ) & 232156.725274725 & 3920.95522942142 & 59.209226244846 \tabularnewline
Winsorized Mean ( 18 / 30 ) & 230959.626373626 & 3615.0627729229 & 63.8881371863117 \tabularnewline
Winsorized Mean ( 19 / 30 ) & 230342.230769231 & 3513.00474904426 & 65.568437057165 \tabularnewline
Winsorized Mean ( 20 / 30 ) & 230424.868131868 & 3438.9601475251 & 67.0042275126964 \tabularnewline
Winsorized Mean ( 21 / 30 ) & 228872.483516484 & 3166.39408398299 & 72.2817430319938 \tabularnewline
Winsorized Mean ( 22 / 30 ) & 228748.219780220 & 3118.50157033020 & 73.3519655582533 \tabularnewline
Winsorized Mean ( 23 / 30 ) & 229349.505494505 & 2923.40115175942 & 78.4529709022224 \tabularnewline
Winsorized Mean ( 24 / 30 ) & 229274.604395604 & 2864.07601863284 & 80.0518571797715 \tabularnewline
Winsorized Mean ( 25 / 30 ) & 229451.252747253 & 2818.38324200273 & 81.4123676750951 \tabularnewline
Winsorized Mean ( 26 / 30 ) & 229316.395604396 & 2768.95204240834 & 82.8170340591903 \tabularnewline
Winsorized Mean ( 27 / 30 ) & 229154.989010989 & 2717.97363709438 & 84.3109682461691 \tabularnewline
Winsorized Mean ( 28 / 30 ) & 229107.604395604 & 2491.5118876733 & 91.9552523626756 \tabularnewline
Winsorized Mean ( 29 / 30 ) & 229376.571428571 & 2424.59000887696 & 94.6042714804452 \tabularnewline
Winsorized Mean ( 30 / 30 ) & 228290.307692308 & 2100.99689738144 & 108.658088918092 \tabularnewline
Trimmed Mean ( 1 / 30 ) & 234189.617977528 & 6819.08532491074 & 34.3432596629950 \tabularnewline
Trimmed Mean ( 2 / 30 ) & 234150.505747126 & 6526.5482666284 & 35.87662209508 \tabularnewline
Trimmed Mean ( 3 / 30 ) & 233923.447058824 & 6255.14881556815 & 37.3969435349999 \tabularnewline
Trimmed Mean ( 4 / 30 ) & 233659.602409639 & 5966.82746012148 & 39.1597719175344 \tabularnewline
Trimmed Mean ( 5 / 30 ) & 233108.395061728 & 5698.9247407312 & 40.9039258573924 \tabularnewline
Trimmed Mean ( 6 / 30 ) & 232637.873417722 & 5452.36965731674 & 42.667296613966 \tabularnewline
Trimmed Mean ( 7 / 30 ) & 232270.831168831 & 5205.87115220075 & 44.6170918138533 \tabularnewline
Trimmed Mean ( 8 / 30 ) & 231925.92 & 4954.76456661102 & 46.8086660591087 \tabularnewline
Trimmed Mean ( 9 / 30 ) & 231446.424657534 & 4695.10375089879 & 49.2952737441059 \tabularnewline
Trimmed Mean ( 10 / 30 ) & 231110.408450704 & 4493.84034197321 & 51.4282642158189 \tabularnewline
Trimmed Mean ( 11 / 30 ) & 230939.666666667 & 4326.51496056991 & 53.3777575650047 \tabularnewline
Trimmed Mean ( 12 / 30 ) & 230612.985074627 & 4178.48950061872 & 55.1905144288335 \tabularnewline
Trimmed Mean ( 13 / 30 ) & 230326.307692308 & 4031.59691625481 & 57.1302916627566 \tabularnewline
Trimmed Mean ( 14 / 30 ) & 229876.476190476 & 3889.52717335762 & 59.1013935485727 \tabularnewline
Trimmed Mean ( 15 / 30 ) & 229569.68852459 & 3792.0005445416 & 60.5405209804214 \tabularnewline
Trimmed Mean ( 16 / 30 ) & 229262.152542373 & 3682.35981141454 & 62.2595738286379 \tabularnewline
Trimmed Mean ( 17 / 30 ) & 228984.421052632 & 3573.06812340646 & 64.086217543013 \tabularnewline
Trimmed Mean ( 18 / 30 ) & 228675.672727273 & 3466.19672621418 & 65.9730796575517 \tabularnewline
Trimmed Mean ( 19 / 30 ) & 228457.811320755 & 3390.97147800264 & 67.3723777397625 \tabularnewline
Trimmed Mean ( 20 / 30 ) & 228280.843137255 & 3314.84984788417 & 68.8661187121233 \tabularnewline
Trimmed Mean ( 21 / 30 ) & 228081.755102041 & 3231.11972211097 & 70.5890758368525 \tabularnewline
Trimmed Mean ( 22 / 30 ) & 228008.851063830 & 3176.24249930817 & 71.7857188528563 \tabularnewline
Trimmed Mean ( 23 / 30 ) & 227940.888888889 & 3112.37005768627 & 73.2370780672333 \tabularnewline
Trimmed Mean ( 24 / 30 ) & 227811.279069767 & 3064.64851252863 & 74.3352061870877 \tabularnewline
Trimmed Mean ( 25 / 30 ) & 227675.951219512 & 3010.21758490596 & 75.6343834947813 \tabularnewline
Trimmed Mean ( 26 / 30 ) & 227510.256410256 & 2943.50516324383 & 77.292290583086 \tabularnewline
Trimmed Mean ( 27 / 30 ) & 227339.405405405 & 2861.49308961093 & 79.4478261124568 \tabularnewline
Trimmed Mean ( 28 / 30 ) & 227164.571428571 & 2758.87199890871 & 82.3396560327655 \tabularnewline
Trimmed Mean ( 29 / 30 ) & 227164.571428571 & 2674.19782887317 & 84.9468087124625 \tabularnewline
Trimmed Mean ( 30 / 30 ) & 226729.935483871 & 2567.80062240439 & 88.2973286576936 \tabularnewline
Median & 223166 &  &  \tabularnewline
Midrange & 237133 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 227187.804347826 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 228008.851063830 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 228008.851063830 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 228008.851063830 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 227940.888888889 &  &  \tabularnewline
Midmean - Closest Observation & 227187.804347826 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 228008.851063830 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 228008.851063830 &  &  \tabularnewline
Number of observations & 91 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=80790&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]234254.307692308[/C][C]7145.66825097824[/C][C]32.7827012764325[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]223833.163772138[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]212038.924447132[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]243865.808181827[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 30 )[/C][C]234227.010989011[/C][C]7072.55735009978[/C][C]33.1177252292916[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 30 )[/C][C]234574.681318681[/C][C]6965.36847104697[/C][C]33.677282442952[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 30 )[/C][C]234645.395604396[/C][C]6904.69266761081[/C][C]33.9834670274453[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 30 )[/C][C]235622.142857143[/C][C]6715.01762971749[/C][C]35.0888345868804[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 30 )[/C][C]235150.769230769[/C][C]6502.91210331664[/C][C]36.1608407886732[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 30 )[/C][C]234501.318681319[/C][C]6351.04652960564[/C][C]36.9232562835403[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 30 )[/C][C]234260.703296703[/C][C]6197.6651681407[/C][C]37.7982186744983[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 30 )[/C][C]235003.120879121[/C][C]6035.65986735435[/C][C]38.9357793586422[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 30 )[/C][C]233805.923076923[/C][C]5577.17888721378[/C][C]41.9218977560404[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 30 )[/C][C]232405.043956044[/C][C]5248.21392238065[/C][C]44.2826926251936[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 30 )[/C][C]233585.428571429[/C][C]4990.16688688958[/C][C]46.8091416311378[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 30 )[/C][C]233070.219780220[/C][C]4837.91815837718[/C][C]48.1757260355145[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 30 )[/C][C]234374.791208791[/C][C]4645.83988325934[/C][C]50.448314427135[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 30 )[/C][C]232755.560439560[/C][C]4261.6762917805[/C][C]54.6159643538568[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 30 )[/C][C]232560.560439560[/C][C]4209.5453482968[/C][C]55.2460043062977[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 30 )[/C][C]232045.571428571[/C][C]4075.36001747992[/C][C]56.9386681012936[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 30 )[/C][C]232156.725274725[/C][C]3920.95522942142[/C][C]59.209226244846[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 30 )[/C][C]230959.626373626[/C][C]3615.0627729229[/C][C]63.8881371863117[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 30 )[/C][C]230342.230769231[/C][C]3513.00474904426[/C][C]65.568437057165[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 30 )[/C][C]230424.868131868[/C][C]3438.9601475251[/C][C]67.0042275126964[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 30 )[/C][C]228872.483516484[/C][C]3166.39408398299[/C][C]72.2817430319938[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 30 )[/C][C]228748.219780220[/C][C]3118.50157033020[/C][C]73.3519655582533[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 30 )[/C][C]229349.505494505[/C][C]2923.40115175942[/C][C]78.4529709022224[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 30 )[/C][C]229274.604395604[/C][C]2864.07601863284[/C][C]80.0518571797715[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 30 )[/C][C]229451.252747253[/C][C]2818.38324200273[/C][C]81.4123676750951[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 30 )[/C][C]229316.395604396[/C][C]2768.95204240834[/C][C]82.8170340591903[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 30 )[/C][C]229154.989010989[/C][C]2717.97363709438[/C][C]84.3109682461691[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 30 )[/C][C]229107.604395604[/C][C]2491.5118876733[/C][C]91.9552523626756[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 30 )[/C][C]229376.571428571[/C][C]2424.59000887696[/C][C]94.6042714804452[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 30 )[/C][C]228290.307692308[/C][C]2100.99689738144[/C][C]108.658088918092[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 30 )[/C][C]234189.617977528[/C][C]6819.08532491074[/C][C]34.3432596629950[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 30 )[/C][C]234150.505747126[/C][C]6526.5482666284[/C][C]35.87662209508[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 30 )[/C][C]233923.447058824[/C][C]6255.14881556815[/C][C]37.3969435349999[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 30 )[/C][C]233659.602409639[/C][C]5966.82746012148[/C][C]39.1597719175344[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 30 )[/C][C]233108.395061728[/C][C]5698.9247407312[/C][C]40.9039258573924[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 30 )[/C][C]232637.873417722[/C][C]5452.36965731674[/C][C]42.667296613966[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 30 )[/C][C]232270.831168831[/C][C]5205.87115220075[/C][C]44.6170918138533[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 30 )[/C][C]231925.92[/C][C]4954.76456661102[/C][C]46.8086660591087[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 30 )[/C][C]231446.424657534[/C][C]4695.10375089879[/C][C]49.2952737441059[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 30 )[/C][C]231110.408450704[/C][C]4493.84034197321[/C][C]51.4282642158189[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 30 )[/C][C]230939.666666667[/C][C]4326.51496056991[/C][C]53.3777575650047[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 30 )[/C][C]230612.985074627[/C][C]4178.48950061872[/C][C]55.1905144288335[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 30 )[/C][C]230326.307692308[/C][C]4031.59691625481[/C][C]57.1302916627566[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 30 )[/C][C]229876.476190476[/C][C]3889.52717335762[/C][C]59.1013935485727[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 30 )[/C][C]229569.68852459[/C][C]3792.0005445416[/C][C]60.5405209804214[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 30 )[/C][C]229262.152542373[/C][C]3682.35981141454[/C][C]62.2595738286379[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 30 )[/C][C]228984.421052632[/C][C]3573.06812340646[/C][C]64.086217543013[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 30 )[/C][C]228675.672727273[/C][C]3466.19672621418[/C][C]65.9730796575517[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 30 )[/C][C]228457.811320755[/C][C]3390.97147800264[/C][C]67.3723777397625[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 30 )[/C][C]228280.843137255[/C][C]3314.84984788417[/C][C]68.8661187121233[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 30 )[/C][C]228081.755102041[/C][C]3231.11972211097[/C][C]70.5890758368525[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 30 )[/C][C]228008.851063830[/C][C]3176.24249930817[/C][C]71.7857188528563[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 30 )[/C][C]227940.888888889[/C][C]3112.37005768627[/C][C]73.2370780672333[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 30 )[/C][C]227811.279069767[/C][C]3064.64851252863[/C][C]74.3352061870877[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 30 )[/C][C]227675.951219512[/C][C]3010.21758490596[/C][C]75.6343834947813[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 30 )[/C][C]227510.256410256[/C][C]2943.50516324383[/C][C]77.292290583086[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 30 )[/C][C]227339.405405405[/C][C]2861.49308961093[/C][C]79.4478261124568[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 30 )[/C][C]227164.571428571[/C][C]2758.87199890871[/C][C]82.3396560327655[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 30 )[/C][C]227164.571428571[/C][C]2674.19782887317[/C][C]84.9468087124625[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 30 )[/C][C]226729.935483871[/C][C]2567.80062240439[/C][C]88.2973286576936[/C][/ROW]
[ROW][C]Median[/C][C]223166[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]237133[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]227187.804347826[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]228008.851063830[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]228008.851063830[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]228008.851063830[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]227940.888888889[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]227187.804347826[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]228008.851063830[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]228008.851063830[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]91[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=80790&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=80790&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 Mean234254.3076923087145.6682509782432.7827012764325
Geometric Mean223833.163772138
Harmonic Mean212038.924447132
Quadratic Mean243865.808181827
Winsorized Mean ( 1 / 30 )234227.0109890117072.5573500997833.1177252292916
Winsorized Mean ( 2 / 30 )234574.6813186816965.3684710469733.677282442952
Winsorized Mean ( 3 / 30 )234645.3956043966904.6926676108133.9834670274453
Winsorized Mean ( 4 / 30 )235622.1428571436715.0176297174935.0888345868804
Winsorized Mean ( 5 / 30 )235150.7692307696502.9121033166436.1608407886732
Winsorized Mean ( 6 / 30 )234501.3186813196351.0465296056436.9232562835403
Winsorized Mean ( 7 / 30 )234260.7032967036197.665168140737.7982186744983
Winsorized Mean ( 8 / 30 )235003.1208791216035.6598673543538.9357793586422
Winsorized Mean ( 9 / 30 )233805.9230769235577.1788872137841.9218977560404
Winsorized Mean ( 10 / 30 )232405.0439560445248.2139223806544.2826926251936
Winsorized Mean ( 11 / 30 )233585.4285714294990.1668868895846.8091416311378
Winsorized Mean ( 12 / 30 )233070.2197802204837.9181583771848.1757260355145
Winsorized Mean ( 13 / 30 )234374.7912087914645.8398832593450.448314427135
Winsorized Mean ( 14 / 30 )232755.5604395604261.676291780554.6159643538568
Winsorized Mean ( 15 / 30 )232560.5604395604209.545348296855.2460043062977
Winsorized Mean ( 16 / 30 )232045.5714285714075.3600174799256.9386681012936
Winsorized Mean ( 17 / 30 )232156.7252747253920.9552294214259.209226244846
Winsorized Mean ( 18 / 30 )230959.6263736263615.062772922963.8881371863117
Winsorized Mean ( 19 / 30 )230342.2307692313513.0047490442665.568437057165
Winsorized Mean ( 20 / 30 )230424.8681318683438.960147525167.0042275126964
Winsorized Mean ( 21 / 30 )228872.4835164843166.3940839829972.2817430319938
Winsorized Mean ( 22 / 30 )228748.2197802203118.5015703302073.3519655582533
Winsorized Mean ( 23 / 30 )229349.5054945052923.4011517594278.4529709022224
Winsorized Mean ( 24 / 30 )229274.6043956042864.0760186328480.0518571797715
Winsorized Mean ( 25 / 30 )229451.2527472532818.3832420027381.4123676750951
Winsorized Mean ( 26 / 30 )229316.3956043962768.9520424083482.8170340591903
Winsorized Mean ( 27 / 30 )229154.9890109892717.9736370943884.3109682461691
Winsorized Mean ( 28 / 30 )229107.6043956042491.511887673391.9552523626756
Winsorized Mean ( 29 / 30 )229376.5714285712424.5900088769694.6042714804452
Winsorized Mean ( 30 / 30 )228290.3076923082100.99689738144108.658088918092
Trimmed Mean ( 1 / 30 )234189.6179775286819.0853249107434.3432596629950
Trimmed Mean ( 2 / 30 )234150.5057471266526.548266628435.87662209508
Trimmed Mean ( 3 / 30 )233923.4470588246255.1488155681537.3969435349999
Trimmed Mean ( 4 / 30 )233659.6024096395966.8274601214839.1597719175344
Trimmed Mean ( 5 / 30 )233108.3950617285698.924740731240.9039258573924
Trimmed Mean ( 6 / 30 )232637.8734177225452.3696573167442.667296613966
Trimmed Mean ( 7 / 30 )232270.8311688315205.8711522007544.6170918138533
Trimmed Mean ( 8 / 30 )231925.924954.7645666110246.8086660591087
Trimmed Mean ( 9 / 30 )231446.4246575344695.1037508987949.2952737441059
Trimmed Mean ( 10 / 30 )231110.4084507044493.8403419732151.4282642158189
Trimmed Mean ( 11 / 30 )230939.6666666674326.5149605699153.3777575650047
Trimmed Mean ( 12 / 30 )230612.9850746274178.4895006187255.1905144288335
Trimmed Mean ( 13 / 30 )230326.3076923084031.5969162548157.1302916627566
Trimmed Mean ( 14 / 30 )229876.4761904763889.5271733576259.1013935485727
Trimmed Mean ( 15 / 30 )229569.688524593792.000544541660.5405209804214
Trimmed Mean ( 16 / 30 )229262.1525423733682.3598114145462.2595738286379
Trimmed Mean ( 17 / 30 )228984.4210526323573.0681234064664.086217543013
Trimmed Mean ( 18 / 30 )228675.6727272733466.1967262141865.9730796575517
Trimmed Mean ( 19 / 30 )228457.8113207553390.9714780026467.3723777397625
Trimmed Mean ( 20 / 30 )228280.8431372553314.8498478841768.8661187121233
Trimmed Mean ( 21 / 30 )228081.7551020413231.1197221109770.5890758368525
Trimmed Mean ( 22 / 30 )228008.8510638303176.2424993081771.7857188528563
Trimmed Mean ( 23 / 30 )227940.8888888893112.3700576862773.2370780672333
Trimmed Mean ( 24 / 30 )227811.2790697673064.6485125286374.3352061870877
Trimmed Mean ( 25 / 30 )227675.9512195123010.2175849059675.6343834947813
Trimmed Mean ( 26 / 30 )227510.2564102562943.5051632438377.292290583086
Trimmed Mean ( 27 / 30 )227339.4054054052861.4930896109379.4478261124568
Trimmed Mean ( 28 / 30 )227164.5714285712758.8719989087182.3396560327655
Trimmed Mean ( 29 / 30 )227164.5714285712674.1978288731784.9468087124625
Trimmed Mean ( 30 / 30 )226729.9354838712567.8006224043988.2973286576936
Median223166
Midrange237133
Midmean - Weighted Average at Xnp227187.804347826
Midmean - Weighted Average at X(n+1)p228008.851063830
Midmean - Empirical Distribution Function228008.851063830
Midmean - Empirical Distribution Function - Averaging228008.851063830
Midmean - Empirical Distribution Function - Interpolation227940.888888889
Midmean - Closest Observation227187.804347826
Midmean - True Basic - Statistics Graphics Toolkit228008.851063830
Midmean - MS Excel (old versions)228008.851063830
Number of observations91



Parameters (Session):
par1 = 15 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
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')