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Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 12 Dec 2011 05:18:36 -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/Dec/12/t1323685165xan80drjw1b0ala.htm/, Retrieved Fri, 03 May 2024 17:57:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=153896, Retrieved Fri, 03 May 2024 17:57:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact104
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] [74be16979710d4c4e7c6647856088456]
-    D      [Central Tendency] [paper] [2011-12-12 10:18:36] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
68897
38683
44720
39525
45315
50380
40600
36279
42438
38064
31879
11379
70249
39253
47060
41697
38708
49267
39018
32228
40870
39383
34571
12066
70938
34077
45409
40809
37013
44953
37848
32745
39401
34931
33008
8620
68906
39556
50669
36432
40891
48428
36222
33425
39401
37967
34801
12657
69116
41519
51321
38529
41547
52073
38401
40898
40439
41888
37898
8771
68184
50530
47221
41756
45633
48138
39486
39341
41117
41629
29722
7054
56676
34870
35117
30169
30936
35699
33228
27733
33666
35429
27438
8170




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153896&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153896&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153896&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' @ jenkins.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean39321.16666666671425.1383081347127.591123220968
Geometric Mean36345.5042756572
Harmonic Mean31567.954927996
Quadratic Mean41409.2832756709
Winsorized Mean ( 1 / 28 )39326.251419.3965903464227.7063156748898
Winsorized Mean ( 2 / 28 )39309.98809523811409.5975909713327.8873831418441
Winsorized Mean ( 3 / 28 )39307.8809523811406.2785497737927.9517034222729
Winsorized Mean ( 4 / 28 )39431.64285714291374.6448963712728.6849665402555
Winsorized Mean ( 5 / 28 )39430.09523809521353.7268108571529.1270697469078
Winsorized Mean ( 6 / 28 )38650.30952380951158.5125439086233.3620121137489
Winsorized Mean ( 7 / 28 )39498.4761904762797.49665818441949.5280773720086
Winsorized Mean ( 8 / 28 )39454.9523809524779.01306810028350.6473562467547
Winsorized Mean ( 9 / 28 )39598.2023809524729.45324776245154.2847708231024
Winsorized Mean ( 10 / 28 )39634.869047619717.85919217326655.2125952829654
Winsorized Mean ( 11 / 28 )39715.6666666667698.67026255682356.8446501806517
Winsorized Mean ( 12 / 28 )39691.380952381649.95174054149761.0681970315407
Winsorized Mean ( 13 / 28 )39615.5476190476619.49952974679663.947663745991
Winsorized Mean ( 14 / 28 )39653.380952381599.05402093269466.1933307627963
Winsorized Mean ( 15 / 28 )39536.5952380952565.12200539930469.9611674299596
Winsorized Mean ( 16 / 28 )39547.8333333333554.31147556496671.3458679400879
Winsorized Mean ( 17 / 28 )39298.9047619048503.21568821307178.0955476596049
Winsorized Mean ( 18 / 28 )39302.5476190476488.74293464856780.4155821655168
Winsorized Mean ( 19 / 28 )39374.25472.79714066760783.2793742034947
Winsorized Mean ( 20 / 28 )39405.6785714286444.12784670949288.7259802855916
Winsorized Mean ( 21 / 28 )39404.9285714286427.8871864023992.0918639857837
Winsorized Mean ( 22 / 28 )38825.3333333333341.960476780936113.537487427839
Winsorized Mean ( 23 / 28 )38691.4404761905320.982292882336120.540731791625
Winsorized Mean ( 24 / 28 )38706.869047619309.007179712871125.262037871047
Winsorized Mean ( 25 / 28 )38782.1666666667294.034184727057131.89679527456
Winsorized Mean ( 26 / 28 )38844.6904761905280.120118063563138.671548279785
Winsorized Mean ( 27 / 28 )38986.4404761905254.557815995149153.153578584024
Winsorized Mean ( 28 / 28 )38996.1071428571250.944687887969155.397221081111
Trimmed Mean ( 1 / 28 )39329.09756097561350.803930011729.1153265749196
Trimmed Mean ( 2 / 28 )39332.08751269.9382054379430.9716546297907
Trimmed Mean ( 3 / 28 )39343.98717948721179.9616790107833.3434448587104
Trimmed Mean ( 4 / 28 )39357.28947368421072.2641764723336.7048441394048
Trimmed Mean ( 5 / 28 )39336.1891891892952.22469100163441.3097765274412
Trimmed Mean ( 6 / 28 )39314.2777777778806.16166151714748.7672382035518
Trimmed Mean ( 7 / 28 )39447.0714285714691.41396465971957.0527548543012
Trimmed Mean ( 8 / 28 )39438663.44404171576359.4443502695534
Trimmed Mean ( 9 / 28 )39435.303030303634.50633086042362.1511576989732
Trimmed Mean ( 10 / 28 )39411.546875611.27110195409264.4747424653487
Trimmed Mean ( 11 / 28 )39381.2903225806585.71594105872767.2361593085479
Trimmed Mean ( 12 / 28 )39338.7333333333558.716668069770.4090920882027
Trimmed Mean ( 13 / 28 )39296.1724137931536.2645870113773.2775823083764
Trimmed Mean ( 14 / 28 )39259.3214285714515.13241527240276.2120966660797
Trimmed Mean ( 15 / 28 )39215.537037037493.11907120675779.5254925774197
Trimmed Mean ( 16 / 28 )39180.9615384615472.97204305908982.8399101245961
Trimmed Mean ( 17 / 28 )39142.44449.79268617750587.0232914026373
Trimmed Mean ( 18 / 28 )39126.3333333333431.90522824114290.5900896191241
Trimmed Mean ( 19 / 28 )39108.4565217391412.09796418278594.9008729011645
Trimmed Mean ( 20 / 28 )39081.75389.929437598005100.227749514749
Trimmed Mean ( 21 / 28 )39049.3571428571367.689337987862106.202038265647
Trimmed Mean ( 22 / 28 )39013.8342.081920013321114.048120398999
Trimmed Mean ( 23 / 28 )39032.7368421053330.568512586745118.077600726907
Trimmed Mean ( 24 / 28 )39067.3611111111319.500453716492122.276386955549
Trimmed Mean ( 25 / 28 )39104.4705882353306.990054346305127.380252339129
Trimmed Mean ( 26 / 28 )39138.3125293.535156291083133.334326949201
Trimmed Mean ( 27 / 28 )39169.9333333333278.359714903623140.71696167276
Trimmed Mean ( 28 / 28 )39190.3214285714264.921866556573147.931622021101
Median39362
Midrange38996
Midmean - Weighted Average at Xnp38945.2093023256
Midmean - Weighted Average at X(n+1)p39049.3571428571
Midmean - Empirical Distribution Function38945.2093023256
Midmean - Empirical Distribution Function - Averaging39049.3571428571
Midmean - Empirical Distribution Function - Interpolation39049.3571428571
Midmean - Closest Observation38945.2093023256
Midmean - True Basic - Statistics Graphics Toolkit39049.3571428571
Midmean - MS Excel (old versions)39081.75
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 39321.1666666667 & 1425.13830813471 & 27.591123220968 \tabularnewline
Geometric Mean & 36345.5042756572 &  &  \tabularnewline
Harmonic Mean & 31567.954927996 &  &  \tabularnewline
Quadratic Mean & 41409.2832756709 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 39326.25 & 1419.39659034642 & 27.7063156748898 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 39309.9880952381 & 1409.59759097133 & 27.8873831418441 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 39307.880952381 & 1406.27854977379 & 27.9517034222729 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 39431.6428571429 & 1374.64489637127 & 28.6849665402555 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 39430.0952380952 & 1353.72681085715 & 29.1270697469078 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 38650.3095238095 & 1158.51254390862 & 33.3620121137489 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 39498.4761904762 & 797.496658184419 & 49.5280773720086 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 39454.9523809524 & 779.013068100283 & 50.6473562467547 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 39598.2023809524 & 729.453247762451 & 54.2847708231024 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 39634.869047619 & 717.859192173266 & 55.2125952829654 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 39715.6666666667 & 698.670262556823 & 56.8446501806517 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 39691.380952381 & 649.951740541497 & 61.0681970315407 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 39615.5476190476 & 619.499529746796 & 63.947663745991 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 39653.380952381 & 599.054020932694 & 66.1933307627963 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 39536.5952380952 & 565.122005399304 & 69.9611674299596 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 39547.8333333333 & 554.311475564966 & 71.3458679400879 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 39298.9047619048 & 503.215688213071 & 78.0955476596049 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 39302.5476190476 & 488.742934648567 & 80.4155821655168 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 39374.25 & 472.797140667607 & 83.2793742034947 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 39405.6785714286 & 444.127846709492 & 88.7259802855916 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 39404.9285714286 & 427.88718640239 & 92.0918639857837 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 38825.3333333333 & 341.960476780936 & 113.537487427839 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 38691.4404761905 & 320.982292882336 & 120.540731791625 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 38706.869047619 & 309.007179712871 & 125.262037871047 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 38782.1666666667 & 294.034184727057 & 131.89679527456 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 38844.6904761905 & 280.120118063563 & 138.671548279785 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 38986.4404761905 & 254.557815995149 & 153.153578584024 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 38996.1071428571 & 250.944687887969 & 155.397221081111 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 39329.0975609756 & 1350.8039300117 & 29.1153265749196 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 39332.0875 & 1269.93820543794 & 30.9716546297907 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 39343.9871794872 & 1179.96167901078 & 33.3434448587104 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 39357.2894736842 & 1072.26417647233 & 36.7048441394048 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 39336.1891891892 & 952.224691001634 & 41.3097765274412 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 39314.2777777778 & 806.161661517147 & 48.7672382035518 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 39447.0714285714 & 691.413964659719 & 57.0527548543012 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 39438 & 663.444041715763 & 59.4443502695534 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 39435.303030303 & 634.506330860423 & 62.1511576989732 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 39411.546875 & 611.271101954092 & 64.4747424653487 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 39381.2903225806 & 585.715941058727 & 67.2361593085479 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 39338.7333333333 & 558.7166680697 & 70.4090920882027 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 39296.1724137931 & 536.26458701137 & 73.2775823083764 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 39259.3214285714 & 515.132415272402 & 76.2120966660797 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 39215.537037037 & 493.119071206757 & 79.5254925774197 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 39180.9615384615 & 472.972043059089 & 82.8399101245961 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 39142.44 & 449.792686177505 & 87.0232914026373 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 39126.3333333333 & 431.905228241142 & 90.5900896191241 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 39108.4565217391 & 412.097964182785 & 94.9008729011645 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 39081.75 & 389.929437598005 & 100.227749514749 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 39049.3571428571 & 367.689337987862 & 106.202038265647 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 39013.8 & 342.081920013321 & 114.048120398999 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 39032.7368421053 & 330.568512586745 & 118.077600726907 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 39067.3611111111 & 319.500453716492 & 122.276386955549 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 39104.4705882353 & 306.990054346305 & 127.380252339129 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 39138.3125 & 293.535156291083 & 133.334326949201 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 39169.9333333333 & 278.359714903623 & 140.71696167276 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 39190.3214285714 & 264.921866556573 & 147.931622021101 \tabularnewline
Median & 39362 &  &  \tabularnewline
Midrange & 38996 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 38945.2093023256 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 39049.3571428571 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 38945.2093023256 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 39049.3571428571 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 39049.3571428571 &  &  \tabularnewline
Midmean - Closest Observation & 38945.2093023256 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 39049.3571428571 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 39081.75 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153896&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]39321.1666666667[/C][C]1425.13830813471[/C][C]27.591123220968[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]36345.5042756572[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]31567.954927996[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]41409.2832756709[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]39326.25[/C][C]1419.39659034642[/C][C]27.7063156748898[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]39309.9880952381[/C][C]1409.59759097133[/C][C]27.8873831418441[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]39307.880952381[/C][C]1406.27854977379[/C][C]27.9517034222729[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]39431.6428571429[/C][C]1374.64489637127[/C][C]28.6849665402555[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]39430.0952380952[/C][C]1353.72681085715[/C][C]29.1270697469078[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]38650.3095238095[/C][C]1158.51254390862[/C][C]33.3620121137489[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]39498.4761904762[/C][C]797.496658184419[/C][C]49.5280773720086[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]39454.9523809524[/C][C]779.013068100283[/C][C]50.6473562467547[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]39598.2023809524[/C][C]729.453247762451[/C][C]54.2847708231024[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]39634.869047619[/C][C]717.859192173266[/C][C]55.2125952829654[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]39715.6666666667[/C][C]698.670262556823[/C][C]56.8446501806517[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]39691.380952381[/C][C]649.951740541497[/C][C]61.0681970315407[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]39615.5476190476[/C][C]619.499529746796[/C][C]63.947663745991[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]39653.380952381[/C][C]599.054020932694[/C][C]66.1933307627963[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]39536.5952380952[/C][C]565.122005399304[/C][C]69.9611674299596[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]39547.8333333333[/C][C]554.311475564966[/C][C]71.3458679400879[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]39298.9047619048[/C][C]503.215688213071[/C][C]78.0955476596049[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]39302.5476190476[/C][C]488.742934648567[/C][C]80.4155821655168[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]39374.25[/C][C]472.797140667607[/C][C]83.2793742034947[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]39405.6785714286[/C][C]444.127846709492[/C][C]88.7259802855916[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]39404.9285714286[/C][C]427.88718640239[/C][C]92.0918639857837[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]38825.3333333333[/C][C]341.960476780936[/C][C]113.537487427839[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]38691.4404761905[/C][C]320.982292882336[/C][C]120.540731791625[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]38706.869047619[/C][C]309.007179712871[/C][C]125.262037871047[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]38782.1666666667[/C][C]294.034184727057[/C][C]131.89679527456[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]38844.6904761905[/C][C]280.120118063563[/C][C]138.671548279785[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]38986.4404761905[/C][C]254.557815995149[/C][C]153.153578584024[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]38996.1071428571[/C][C]250.944687887969[/C][C]155.397221081111[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]39329.0975609756[/C][C]1350.8039300117[/C][C]29.1153265749196[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]39332.0875[/C][C]1269.93820543794[/C][C]30.9716546297907[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]39343.9871794872[/C][C]1179.96167901078[/C][C]33.3434448587104[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]39357.2894736842[/C][C]1072.26417647233[/C][C]36.7048441394048[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]39336.1891891892[/C][C]952.224691001634[/C][C]41.3097765274412[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]39314.2777777778[/C][C]806.161661517147[/C][C]48.7672382035518[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]39447.0714285714[/C][C]691.413964659719[/C][C]57.0527548543012[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]39438[/C][C]663.444041715763[/C][C]59.4443502695534[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]39435.303030303[/C][C]634.506330860423[/C][C]62.1511576989732[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]39411.546875[/C][C]611.271101954092[/C][C]64.4747424653487[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]39381.2903225806[/C][C]585.715941058727[/C][C]67.2361593085479[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]39338.7333333333[/C][C]558.7166680697[/C][C]70.4090920882027[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]39296.1724137931[/C][C]536.26458701137[/C][C]73.2775823083764[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]39259.3214285714[/C][C]515.132415272402[/C][C]76.2120966660797[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]39215.537037037[/C][C]493.119071206757[/C][C]79.5254925774197[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]39180.9615384615[/C][C]472.972043059089[/C][C]82.8399101245961[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]39142.44[/C][C]449.792686177505[/C][C]87.0232914026373[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]39126.3333333333[/C][C]431.905228241142[/C][C]90.5900896191241[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]39108.4565217391[/C][C]412.097964182785[/C][C]94.9008729011645[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]39081.75[/C][C]389.929437598005[/C][C]100.227749514749[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]39049.3571428571[/C][C]367.689337987862[/C][C]106.202038265647[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]39013.8[/C][C]342.081920013321[/C][C]114.048120398999[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]39032.7368421053[/C][C]330.568512586745[/C][C]118.077600726907[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]39067.3611111111[/C][C]319.500453716492[/C][C]122.276386955549[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]39104.4705882353[/C][C]306.990054346305[/C][C]127.380252339129[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]39138.3125[/C][C]293.535156291083[/C][C]133.334326949201[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]39169.9333333333[/C][C]278.359714903623[/C][C]140.71696167276[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]39190.3214285714[/C][C]264.921866556573[/C][C]147.931622021101[/C][/ROW]
[ROW][C]Median[/C][C]39362[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]38996[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]38945.2093023256[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]39049.3571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]38945.2093023256[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]39049.3571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]39049.3571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]38945.2093023256[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]39049.3571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]39081.75[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]84[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153896&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153896&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 Mean39321.16666666671425.1383081347127.591123220968
Geometric Mean36345.5042756572
Harmonic Mean31567.954927996
Quadratic Mean41409.2832756709
Winsorized Mean ( 1 / 28 )39326.251419.3965903464227.7063156748898
Winsorized Mean ( 2 / 28 )39309.98809523811409.5975909713327.8873831418441
Winsorized Mean ( 3 / 28 )39307.8809523811406.2785497737927.9517034222729
Winsorized Mean ( 4 / 28 )39431.64285714291374.6448963712728.6849665402555
Winsorized Mean ( 5 / 28 )39430.09523809521353.7268108571529.1270697469078
Winsorized Mean ( 6 / 28 )38650.30952380951158.5125439086233.3620121137489
Winsorized Mean ( 7 / 28 )39498.4761904762797.49665818441949.5280773720086
Winsorized Mean ( 8 / 28 )39454.9523809524779.01306810028350.6473562467547
Winsorized Mean ( 9 / 28 )39598.2023809524729.45324776245154.2847708231024
Winsorized Mean ( 10 / 28 )39634.869047619717.85919217326655.2125952829654
Winsorized Mean ( 11 / 28 )39715.6666666667698.67026255682356.8446501806517
Winsorized Mean ( 12 / 28 )39691.380952381649.95174054149761.0681970315407
Winsorized Mean ( 13 / 28 )39615.5476190476619.49952974679663.947663745991
Winsorized Mean ( 14 / 28 )39653.380952381599.05402093269466.1933307627963
Winsorized Mean ( 15 / 28 )39536.5952380952565.12200539930469.9611674299596
Winsorized Mean ( 16 / 28 )39547.8333333333554.31147556496671.3458679400879
Winsorized Mean ( 17 / 28 )39298.9047619048503.21568821307178.0955476596049
Winsorized Mean ( 18 / 28 )39302.5476190476488.74293464856780.4155821655168
Winsorized Mean ( 19 / 28 )39374.25472.79714066760783.2793742034947
Winsorized Mean ( 20 / 28 )39405.6785714286444.12784670949288.7259802855916
Winsorized Mean ( 21 / 28 )39404.9285714286427.8871864023992.0918639857837
Winsorized Mean ( 22 / 28 )38825.3333333333341.960476780936113.537487427839
Winsorized Mean ( 23 / 28 )38691.4404761905320.982292882336120.540731791625
Winsorized Mean ( 24 / 28 )38706.869047619309.007179712871125.262037871047
Winsorized Mean ( 25 / 28 )38782.1666666667294.034184727057131.89679527456
Winsorized Mean ( 26 / 28 )38844.6904761905280.120118063563138.671548279785
Winsorized Mean ( 27 / 28 )38986.4404761905254.557815995149153.153578584024
Winsorized Mean ( 28 / 28 )38996.1071428571250.944687887969155.397221081111
Trimmed Mean ( 1 / 28 )39329.09756097561350.803930011729.1153265749196
Trimmed Mean ( 2 / 28 )39332.08751269.9382054379430.9716546297907
Trimmed Mean ( 3 / 28 )39343.98717948721179.9616790107833.3434448587104
Trimmed Mean ( 4 / 28 )39357.28947368421072.2641764723336.7048441394048
Trimmed Mean ( 5 / 28 )39336.1891891892952.22469100163441.3097765274412
Trimmed Mean ( 6 / 28 )39314.2777777778806.16166151714748.7672382035518
Trimmed Mean ( 7 / 28 )39447.0714285714691.41396465971957.0527548543012
Trimmed Mean ( 8 / 28 )39438663.44404171576359.4443502695534
Trimmed Mean ( 9 / 28 )39435.303030303634.50633086042362.1511576989732
Trimmed Mean ( 10 / 28 )39411.546875611.27110195409264.4747424653487
Trimmed Mean ( 11 / 28 )39381.2903225806585.71594105872767.2361593085479
Trimmed Mean ( 12 / 28 )39338.7333333333558.716668069770.4090920882027
Trimmed Mean ( 13 / 28 )39296.1724137931536.2645870113773.2775823083764
Trimmed Mean ( 14 / 28 )39259.3214285714515.13241527240276.2120966660797
Trimmed Mean ( 15 / 28 )39215.537037037493.11907120675779.5254925774197
Trimmed Mean ( 16 / 28 )39180.9615384615472.97204305908982.8399101245961
Trimmed Mean ( 17 / 28 )39142.44449.79268617750587.0232914026373
Trimmed Mean ( 18 / 28 )39126.3333333333431.90522824114290.5900896191241
Trimmed Mean ( 19 / 28 )39108.4565217391412.09796418278594.9008729011645
Trimmed Mean ( 20 / 28 )39081.75389.929437598005100.227749514749
Trimmed Mean ( 21 / 28 )39049.3571428571367.689337987862106.202038265647
Trimmed Mean ( 22 / 28 )39013.8342.081920013321114.048120398999
Trimmed Mean ( 23 / 28 )39032.7368421053330.568512586745118.077600726907
Trimmed Mean ( 24 / 28 )39067.3611111111319.500453716492122.276386955549
Trimmed Mean ( 25 / 28 )39104.4705882353306.990054346305127.380252339129
Trimmed Mean ( 26 / 28 )39138.3125293.535156291083133.334326949201
Trimmed Mean ( 27 / 28 )39169.9333333333278.359714903623140.71696167276
Trimmed Mean ( 28 / 28 )39190.3214285714264.921866556573147.931622021101
Median39362
Midrange38996
Midmean - Weighted Average at Xnp38945.2093023256
Midmean - Weighted Average at X(n+1)p39049.3571428571
Midmean - Empirical Distribution Function38945.2093023256
Midmean - Empirical Distribution Function - Averaging39049.3571428571
Midmean - Empirical Distribution Function - Interpolation39049.3571428571
Midmean - Closest Observation38945.2093023256
Midmean - True Basic - Statistics Graphics Toolkit39049.3571428571
Midmean - MS Excel (old versions)39081.75
Number of observations84



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')