Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 16 Mar 2009 07:57:33 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Mar/16/t1237211908j2c7grbi51r55jb.htm/, Retrieved Wed, 24 Apr 2024 13:50:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=39115, Retrieved Wed, 24 Apr 2024 13:50:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact198
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Ben Eysackers, op...] [2009-03-16 13:57:33] [2b08e9b5345c911f5a04c663d4ad43d5] [Current]
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Dataseries X:
-46
-33
-34
-25
-33
-18
-26
-21
-23
-24
-26
-32
-47
-45
-47
-43
-48
-48
-43
-44
-46
-36
-32
-18
-31
-37
-32
-29
-29
-40
-26
-29
-19
-30
-12
-24
-40
-43
-49
-49
-48
-33
-46
-46
-43
-44
-38
-38
-39
-47
-41
-36
-38
-11
-24
-30
-18
-21
-22
-15
-15
-16
-26
-39
-28
-25
-25
-13
-20
-13
-10
-19
-31
-36
-26
-33
-42
-44
-45
-42
-60
-42
-63
-71




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=39115&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=39115&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=39115&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'George Udny Yule' @ 72.249.76.132







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-33.55952380952381.3582741055279-24.7074752238472
Geometric MeanNaN
Harmonic Mean-28.2368648279735
Quadratic Mean35.7682687254925
Winsorized Mean ( 1 / 28 )-33.47619047619051.32720293823686-25.2231135960733
Winsorized Mean ( 2 / 28 )-33.42857142857141.30406990288627-25.6340333862354
Winsorized Mean ( 3 / 28 )-33.07142857142861.21720145363841-27.1700534636834
Winsorized Mean ( 4 / 28 )-33.07142857142861.21720145363841-27.1700534636834
Winsorized Mean ( 5 / 28 )-33.13095238095241.18519986790427-27.9538947633668
Winsorized Mean ( 6 / 28 )-33.13095238095241.18519986790427-27.9538947633668
Winsorized Mean ( 7 / 28 )-33.21428571428571.17013312919415-28.3850485774723
Winsorized Mean ( 8 / 28 )-33.30952380952381.12334230395882-29.6521582888281
Winsorized Mean ( 9 / 28 )-33.30952380952381.12334230395882-29.6521582888281
Winsorized Mean ( 10 / 28 )-33.30952380952381.12334230395882-29.6521582888281
Winsorized Mean ( 11 / 28 )-33.30952380952381.08330259771169-30.7481251128587
Winsorized Mean ( 12 / 28 )-33.30952380952381.08330259771169-30.7481251128587
Winsorized Mean ( 13 / 28 )-33.46428571428571.05913051033143-31.5959982153792
Winsorized Mean ( 14 / 28 )-33.63095238095241.03409736554082-32.5220366105118
Winsorized Mean ( 15 / 28 )-33.45238095238091.00891106551831-33.1569174882579
Winsorized Mean ( 16 / 28 )-33.64285714285710.981124622123696-34.2900956557745
Winsorized Mean ( 17 / 28 )-33.64285714285710.924834707463007-36.3771567733933
Winsorized Mean ( 18 / 28 )-33.85714285714290.895764057358414-37.7969428210669
Winsorized Mean ( 19 / 28 )-33.85714285714290.895764057358414-37.7969428210669
Winsorized Mean ( 20 / 28 )-33.61904761904760.863936865851276-38.9137782492026
Winsorized Mean ( 21 / 28 )-33.86904761904760.831083554359753-40.7528791074918
Winsorized Mean ( 22 / 28 )-33.86904761904760.831083554359753-40.7528791074918
Winsorized Mean ( 23 / 28 )-33.86904761904760.831083554359753-40.7528791074918
Winsorized Mean ( 24 / 28 )-33.86904761904760.757403648927133-44.717301886548
Winsorized Mean ( 25 / 28 )-33.86904761904760.757403648927133-44.717301886548
Winsorized Mean ( 26 / 28 )-33.86904761904760.757403648927133-44.717301886548
Winsorized Mean ( 27 / 28 )-33.54761904761910.716457779916565-46.8242790964261
Winsorized Mean ( 28 / 28 )-33.21428571428570.675374448013171-49.1790677186501
Trimmed Mean ( 1 / 28 )-33.3902439024391.28124968372713-26.0606846007621
Trimmed Mean ( 2 / 28 )-33.31.22763537241110-27.1253181102123
Trimmed Mean ( 3 / 28 )-33.23076923076921.17965366790349-28.1699367661254
Trimmed Mean ( 4 / 28 )-33.28947368421051.16224462042638-28.6423985959151
Trimmed Mean ( 5 / 28 )-33.35135135135141.14165718589775-29.2131050925986
Trimmed Mean ( 6 / 28 )-33.40277777777781.12668925898644-29.6468414084523
Trimmed Mean ( 7 / 28 )-33.45714285714291.10872424295187-30.1762526343489
Trimmed Mean ( 8 / 28 )-33.51.09080682336512-30.7112123635723
Trimmed Mean ( 9 / 28 )-33.5303030303031.07941529906920-31.0633942831982
Trimmed Mean ( 10 / 28 )-33.56251.06529743778551-31.5052855752362
Trimmed Mean ( 11 / 28 )-33.59677419354841.04789070134070-32.0613344030669
Trimmed Mean ( 12 / 28 )-33.63333333333331.03415312842539-32.5225853008285
Trimmed Mean ( 13 / 28 )-33.67241379310341.01691321211035-33.1123771351388
Trimmed Mean ( 14 / 28 )-33.69642857142860.9999739096782-33.6973077450314
Trimmed Mean ( 15 / 28 )-33.70370370370370.98330921678476-34.2757935432647
Trimmed Mean ( 16 / 28 )-33.73076923076920.966683069742527-34.8933071102128
Trimmed Mean ( 17 / 28 )-33.740.950535831700699-35.4957686756873
Trimmed Mean ( 18 / 28 )-33.750.939905306834472-35.9078725852367
Trimmed Mean ( 19 / 28 )-33.73913043478260.930655985263595-36.2530633972407
Trimmed Mean ( 20 / 28 )-33.72727272727270.91750859710107-36.7596258322116
Trimmed Mean ( 21 / 28 )-33.73809523809520.905563860001424-37.2564506251853
Trimmed Mean ( 22 / 28 )-33.7250.895134641068608-37.6758963989364
Trimmed Mean ( 23 / 28 )-33.71052631578950.879599591060016-38.3248544660696
Trimmed Mean ( 24 / 28 )-33.69444444444440.857107950494397-39.3117861350006
Trimmed Mean ( 25 / 28 )-33.67647058823530.843049160095319-39.9460342080498
Trimmed Mean ( 26 / 28 )-33.656250.821349910454263-40.9767500691463
Trimmed Mean ( 27 / 28 )-33.63333333333330.788543446034221-42.652479711148
Trimmed Mean ( 28 / 28 )-33.64285714285710.752797754753295-44.6904323643772
Median-33
Midrange-40.5
Midmean - Weighted Average at Xnp-33.953488372093
Midmean - Weighted Average at X(n+1)p-33.953488372093
Midmean - Empirical Distribution Function-33.953488372093
Midmean - Empirical Distribution Function - Averaging-33.953488372093
Midmean - Empirical Distribution Function - Interpolation-33.953488372093
Midmean - Closest Observation-33.953488372093
Midmean - True Basic - Statistics Graphics Toolkit-33.953488372093
Midmean - MS Excel (old versions)-33.3043478260870
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -33.5595238095238 & 1.3582741055279 & -24.7074752238472 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & -28.2368648279735 &  &  \tabularnewline
Quadratic Mean & 35.7682687254925 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & -33.4761904761905 & 1.32720293823686 & -25.2231135960733 \tabularnewline
Winsorized Mean ( 2 / 28 ) & -33.4285714285714 & 1.30406990288627 & -25.6340333862354 \tabularnewline
Winsorized Mean ( 3 / 28 ) & -33.0714285714286 & 1.21720145363841 & -27.1700534636834 \tabularnewline
Winsorized Mean ( 4 / 28 ) & -33.0714285714286 & 1.21720145363841 & -27.1700534636834 \tabularnewline
Winsorized Mean ( 5 / 28 ) & -33.1309523809524 & 1.18519986790427 & -27.9538947633668 \tabularnewline
Winsorized Mean ( 6 / 28 ) & -33.1309523809524 & 1.18519986790427 & -27.9538947633668 \tabularnewline
Winsorized Mean ( 7 / 28 ) & -33.2142857142857 & 1.17013312919415 & -28.3850485774723 \tabularnewline
Winsorized Mean ( 8 / 28 ) & -33.3095238095238 & 1.12334230395882 & -29.6521582888281 \tabularnewline
Winsorized Mean ( 9 / 28 ) & -33.3095238095238 & 1.12334230395882 & -29.6521582888281 \tabularnewline
Winsorized Mean ( 10 / 28 ) & -33.3095238095238 & 1.12334230395882 & -29.6521582888281 \tabularnewline
Winsorized Mean ( 11 / 28 ) & -33.3095238095238 & 1.08330259771169 & -30.7481251128587 \tabularnewline
Winsorized Mean ( 12 / 28 ) & -33.3095238095238 & 1.08330259771169 & -30.7481251128587 \tabularnewline
Winsorized Mean ( 13 / 28 ) & -33.4642857142857 & 1.05913051033143 & -31.5959982153792 \tabularnewline
Winsorized Mean ( 14 / 28 ) & -33.6309523809524 & 1.03409736554082 & -32.5220366105118 \tabularnewline
Winsorized Mean ( 15 / 28 ) & -33.4523809523809 & 1.00891106551831 & -33.1569174882579 \tabularnewline
Winsorized Mean ( 16 / 28 ) & -33.6428571428571 & 0.981124622123696 & -34.2900956557745 \tabularnewline
Winsorized Mean ( 17 / 28 ) & -33.6428571428571 & 0.924834707463007 & -36.3771567733933 \tabularnewline
Winsorized Mean ( 18 / 28 ) & -33.8571428571429 & 0.895764057358414 & -37.7969428210669 \tabularnewline
Winsorized Mean ( 19 / 28 ) & -33.8571428571429 & 0.895764057358414 & -37.7969428210669 \tabularnewline
Winsorized Mean ( 20 / 28 ) & -33.6190476190476 & 0.863936865851276 & -38.9137782492026 \tabularnewline
Winsorized Mean ( 21 / 28 ) & -33.8690476190476 & 0.831083554359753 & -40.7528791074918 \tabularnewline
Winsorized Mean ( 22 / 28 ) & -33.8690476190476 & 0.831083554359753 & -40.7528791074918 \tabularnewline
Winsorized Mean ( 23 / 28 ) & -33.8690476190476 & 0.831083554359753 & -40.7528791074918 \tabularnewline
Winsorized Mean ( 24 / 28 ) & -33.8690476190476 & 0.757403648927133 & -44.717301886548 \tabularnewline
Winsorized Mean ( 25 / 28 ) & -33.8690476190476 & 0.757403648927133 & -44.717301886548 \tabularnewline
Winsorized Mean ( 26 / 28 ) & -33.8690476190476 & 0.757403648927133 & -44.717301886548 \tabularnewline
Winsorized Mean ( 27 / 28 ) & -33.5476190476191 & 0.716457779916565 & -46.8242790964261 \tabularnewline
Winsorized Mean ( 28 / 28 ) & -33.2142857142857 & 0.675374448013171 & -49.1790677186501 \tabularnewline
Trimmed Mean ( 1 / 28 ) & -33.390243902439 & 1.28124968372713 & -26.0606846007621 \tabularnewline
Trimmed Mean ( 2 / 28 ) & -33.3 & 1.22763537241110 & -27.1253181102123 \tabularnewline
Trimmed Mean ( 3 / 28 ) & -33.2307692307692 & 1.17965366790349 & -28.1699367661254 \tabularnewline
Trimmed Mean ( 4 / 28 ) & -33.2894736842105 & 1.16224462042638 & -28.6423985959151 \tabularnewline
Trimmed Mean ( 5 / 28 ) & -33.3513513513514 & 1.14165718589775 & -29.2131050925986 \tabularnewline
Trimmed Mean ( 6 / 28 ) & -33.4027777777778 & 1.12668925898644 & -29.6468414084523 \tabularnewline
Trimmed Mean ( 7 / 28 ) & -33.4571428571429 & 1.10872424295187 & -30.1762526343489 \tabularnewline
Trimmed Mean ( 8 / 28 ) & -33.5 & 1.09080682336512 & -30.7112123635723 \tabularnewline
Trimmed Mean ( 9 / 28 ) & -33.530303030303 & 1.07941529906920 & -31.0633942831982 \tabularnewline
Trimmed Mean ( 10 / 28 ) & -33.5625 & 1.06529743778551 & -31.5052855752362 \tabularnewline
Trimmed Mean ( 11 / 28 ) & -33.5967741935484 & 1.04789070134070 & -32.0613344030669 \tabularnewline
Trimmed Mean ( 12 / 28 ) & -33.6333333333333 & 1.03415312842539 & -32.5225853008285 \tabularnewline
Trimmed Mean ( 13 / 28 ) & -33.6724137931034 & 1.01691321211035 & -33.1123771351388 \tabularnewline
Trimmed Mean ( 14 / 28 ) & -33.6964285714286 & 0.9999739096782 & -33.6973077450314 \tabularnewline
Trimmed Mean ( 15 / 28 ) & -33.7037037037037 & 0.98330921678476 & -34.2757935432647 \tabularnewline
Trimmed Mean ( 16 / 28 ) & -33.7307692307692 & 0.966683069742527 & -34.8933071102128 \tabularnewline
Trimmed Mean ( 17 / 28 ) & -33.74 & 0.950535831700699 & -35.4957686756873 \tabularnewline
Trimmed Mean ( 18 / 28 ) & -33.75 & 0.939905306834472 & -35.9078725852367 \tabularnewline
Trimmed Mean ( 19 / 28 ) & -33.7391304347826 & 0.930655985263595 & -36.2530633972407 \tabularnewline
Trimmed Mean ( 20 / 28 ) & -33.7272727272727 & 0.91750859710107 & -36.7596258322116 \tabularnewline
Trimmed Mean ( 21 / 28 ) & -33.7380952380952 & 0.905563860001424 & -37.2564506251853 \tabularnewline
Trimmed Mean ( 22 / 28 ) & -33.725 & 0.895134641068608 & -37.6758963989364 \tabularnewline
Trimmed Mean ( 23 / 28 ) & -33.7105263157895 & 0.879599591060016 & -38.3248544660696 \tabularnewline
Trimmed Mean ( 24 / 28 ) & -33.6944444444444 & 0.857107950494397 & -39.3117861350006 \tabularnewline
Trimmed Mean ( 25 / 28 ) & -33.6764705882353 & 0.843049160095319 & -39.9460342080498 \tabularnewline
Trimmed Mean ( 26 / 28 ) & -33.65625 & 0.821349910454263 & -40.9767500691463 \tabularnewline
Trimmed Mean ( 27 / 28 ) & -33.6333333333333 & 0.788543446034221 & -42.652479711148 \tabularnewline
Trimmed Mean ( 28 / 28 ) & -33.6428571428571 & 0.752797754753295 & -44.6904323643772 \tabularnewline
Median & -33 &  &  \tabularnewline
Midrange & -40.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -33.953488372093 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -33.953488372093 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -33.953488372093 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -33.953488372093 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -33.953488372093 &  &  \tabularnewline
Midmean - Closest Observation & -33.953488372093 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -33.953488372093 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -33.3043478260870 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=39115&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]-33.5595238095238[/C][C]1.3582741055279[/C][C]-24.7074752238472[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]-28.2368648279735[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]35.7682687254925[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]-33.4761904761905[/C][C]1.32720293823686[/C][C]-25.2231135960733[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]-33.4285714285714[/C][C]1.30406990288627[/C][C]-25.6340333862354[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]-33.0714285714286[/C][C]1.21720145363841[/C][C]-27.1700534636834[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]-33.0714285714286[/C][C]1.21720145363841[/C][C]-27.1700534636834[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]-33.1309523809524[/C][C]1.18519986790427[/C][C]-27.9538947633668[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]-33.1309523809524[/C][C]1.18519986790427[/C][C]-27.9538947633668[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]-33.2142857142857[/C][C]1.17013312919415[/C][C]-28.3850485774723[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]-33.3095238095238[/C][C]1.12334230395882[/C][C]-29.6521582888281[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]-33.3095238095238[/C][C]1.12334230395882[/C][C]-29.6521582888281[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]-33.3095238095238[/C][C]1.12334230395882[/C][C]-29.6521582888281[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]-33.3095238095238[/C][C]1.08330259771169[/C][C]-30.7481251128587[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]-33.3095238095238[/C][C]1.08330259771169[/C][C]-30.7481251128587[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]-33.4642857142857[/C][C]1.05913051033143[/C][C]-31.5959982153792[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]-33.6309523809524[/C][C]1.03409736554082[/C][C]-32.5220366105118[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]-33.4523809523809[/C][C]1.00891106551831[/C][C]-33.1569174882579[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]-33.6428571428571[/C][C]0.981124622123696[/C][C]-34.2900956557745[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]-33.6428571428571[/C][C]0.924834707463007[/C][C]-36.3771567733933[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]-33.8571428571429[/C][C]0.895764057358414[/C][C]-37.7969428210669[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]-33.8571428571429[/C][C]0.895764057358414[/C][C]-37.7969428210669[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]-33.6190476190476[/C][C]0.863936865851276[/C][C]-38.9137782492026[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]-33.8690476190476[/C][C]0.831083554359753[/C][C]-40.7528791074918[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]-33.8690476190476[/C][C]0.831083554359753[/C][C]-40.7528791074918[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]-33.8690476190476[/C][C]0.831083554359753[/C][C]-40.7528791074918[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]-33.8690476190476[/C][C]0.757403648927133[/C][C]-44.717301886548[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]-33.8690476190476[/C][C]0.757403648927133[/C][C]-44.717301886548[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]-33.8690476190476[/C][C]0.757403648927133[/C][C]-44.717301886548[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]-33.5476190476191[/C][C]0.716457779916565[/C][C]-46.8242790964261[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]-33.2142857142857[/C][C]0.675374448013171[/C][C]-49.1790677186501[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]-33.390243902439[/C][C]1.28124968372713[/C][C]-26.0606846007621[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]-33.3[/C][C]1.22763537241110[/C][C]-27.1253181102123[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]-33.2307692307692[/C][C]1.17965366790349[/C][C]-28.1699367661254[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]-33.2894736842105[/C][C]1.16224462042638[/C][C]-28.6423985959151[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]-33.3513513513514[/C][C]1.14165718589775[/C][C]-29.2131050925986[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]-33.4027777777778[/C][C]1.12668925898644[/C][C]-29.6468414084523[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]-33.4571428571429[/C][C]1.10872424295187[/C][C]-30.1762526343489[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]-33.5[/C][C]1.09080682336512[/C][C]-30.7112123635723[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]-33.530303030303[/C][C]1.07941529906920[/C][C]-31.0633942831982[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]-33.5625[/C][C]1.06529743778551[/C][C]-31.5052855752362[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]-33.5967741935484[/C][C]1.04789070134070[/C][C]-32.0613344030669[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]-33.6333333333333[/C][C]1.03415312842539[/C][C]-32.5225853008285[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]-33.6724137931034[/C][C]1.01691321211035[/C][C]-33.1123771351388[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]-33.6964285714286[/C][C]0.9999739096782[/C][C]-33.6973077450314[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]-33.7037037037037[/C][C]0.98330921678476[/C][C]-34.2757935432647[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]-33.7307692307692[/C][C]0.966683069742527[/C][C]-34.8933071102128[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]-33.74[/C][C]0.950535831700699[/C][C]-35.4957686756873[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]-33.75[/C][C]0.939905306834472[/C][C]-35.9078725852367[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]-33.7391304347826[/C][C]0.930655985263595[/C][C]-36.2530633972407[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]-33.7272727272727[/C][C]0.91750859710107[/C][C]-36.7596258322116[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]-33.7380952380952[/C][C]0.905563860001424[/C][C]-37.2564506251853[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]-33.725[/C][C]0.895134641068608[/C][C]-37.6758963989364[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]-33.7105263157895[/C][C]0.879599591060016[/C][C]-38.3248544660696[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]-33.6944444444444[/C][C]0.857107950494397[/C][C]-39.3117861350006[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]-33.6764705882353[/C][C]0.843049160095319[/C][C]-39.9460342080498[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]-33.65625[/C][C]0.821349910454263[/C][C]-40.9767500691463[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]-33.6333333333333[/C][C]0.788543446034221[/C][C]-42.652479711148[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]-33.6428571428571[/C][C]0.752797754753295[/C][C]-44.6904323643772[/C][/ROW]
[ROW][C]Median[/C][C]-33[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-40.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-33.953488372093[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-33.953488372093[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-33.953488372093[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-33.953488372093[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-33.953488372093[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-33.953488372093[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-33.953488372093[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-33.3043478260870[/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=39115&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=39115&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 Mean-33.55952380952381.3582741055279-24.7074752238472
Geometric MeanNaN
Harmonic Mean-28.2368648279735
Quadratic Mean35.7682687254925
Winsorized Mean ( 1 / 28 )-33.47619047619051.32720293823686-25.2231135960733
Winsorized Mean ( 2 / 28 )-33.42857142857141.30406990288627-25.6340333862354
Winsorized Mean ( 3 / 28 )-33.07142857142861.21720145363841-27.1700534636834
Winsorized Mean ( 4 / 28 )-33.07142857142861.21720145363841-27.1700534636834
Winsorized Mean ( 5 / 28 )-33.13095238095241.18519986790427-27.9538947633668
Winsorized Mean ( 6 / 28 )-33.13095238095241.18519986790427-27.9538947633668
Winsorized Mean ( 7 / 28 )-33.21428571428571.17013312919415-28.3850485774723
Winsorized Mean ( 8 / 28 )-33.30952380952381.12334230395882-29.6521582888281
Winsorized Mean ( 9 / 28 )-33.30952380952381.12334230395882-29.6521582888281
Winsorized Mean ( 10 / 28 )-33.30952380952381.12334230395882-29.6521582888281
Winsorized Mean ( 11 / 28 )-33.30952380952381.08330259771169-30.7481251128587
Winsorized Mean ( 12 / 28 )-33.30952380952381.08330259771169-30.7481251128587
Winsorized Mean ( 13 / 28 )-33.46428571428571.05913051033143-31.5959982153792
Winsorized Mean ( 14 / 28 )-33.63095238095241.03409736554082-32.5220366105118
Winsorized Mean ( 15 / 28 )-33.45238095238091.00891106551831-33.1569174882579
Winsorized Mean ( 16 / 28 )-33.64285714285710.981124622123696-34.2900956557745
Winsorized Mean ( 17 / 28 )-33.64285714285710.924834707463007-36.3771567733933
Winsorized Mean ( 18 / 28 )-33.85714285714290.895764057358414-37.7969428210669
Winsorized Mean ( 19 / 28 )-33.85714285714290.895764057358414-37.7969428210669
Winsorized Mean ( 20 / 28 )-33.61904761904760.863936865851276-38.9137782492026
Winsorized Mean ( 21 / 28 )-33.86904761904760.831083554359753-40.7528791074918
Winsorized Mean ( 22 / 28 )-33.86904761904760.831083554359753-40.7528791074918
Winsorized Mean ( 23 / 28 )-33.86904761904760.831083554359753-40.7528791074918
Winsorized Mean ( 24 / 28 )-33.86904761904760.757403648927133-44.717301886548
Winsorized Mean ( 25 / 28 )-33.86904761904760.757403648927133-44.717301886548
Winsorized Mean ( 26 / 28 )-33.86904761904760.757403648927133-44.717301886548
Winsorized Mean ( 27 / 28 )-33.54761904761910.716457779916565-46.8242790964261
Winsorized Mean ( 28 / 28 )-33.21428571428570.675374448013171-49.1790677186501
Trimmed Mean ( 1 / 28 )-33.3902439024391.28124968372713-26.0606846007621
Trimmed Mean ( 2 / 28 )-33.31.22763537241110-27.1253181102123
Trimmed Mean ( 3 / 28 )-33.23076923076921.17965366790349-28.1699367661254
Trimmed Mean ( 4 / 28 )-33.28947368421051.16224462042638-28.6423985959151
Trimmed Mean ( 5 / 28 )-33.35135135135141.14165718589775-29.2131050925986
Trimmed Mean ( 6 / 28 )-33.40277777777781.12668925898644-29.6468414084523
Trimmed Mean ( 7 / 28 )-33.45714285714291.10872424295187-30.1762526343489
Trimmed Mean ( 8 / 28 )-33.51.09080682336512-30.7112123635723
Trimmed Mean ( 9 / 28 )-33.5303030303031.07941529906920-31.0633942831982
Trimmed Mean ( 10 / 28 )-33.56251.06529743778551-31.5052855752362
Trimmed Mean ( 11 / 28 )-33.59677419354841.04789070134070-32.0613344030669
Trimmed Mean ( 12 / 28 )-33.63333333333331.03415312842539-32.5225853008285
Trimmed Mean ( 13 / 28 )-33.67241379310341.01691321211035-33.1123771351388
Trimmed Mean ( 14 / 28 )-33.69642857142860.9999739096782-33.6973077450314
Trimmed Mean ( 15 / 28 )-33.70370370370370.98330921678476-34.2757935432647
Trimmed Mean ( 16 / 28 )-33.73076923076920.966683069742527-34.8933071102128
Trimmed Mean ( 17 / 28 )-33.740.950535831700699-35.4957686756873
Trimmed Mean ( 18 / 28 )-33.750.939905306834472-35.9078725852367
Trimmed Mean ( 19 / 28 )-33.73913043478260.930655985263595-36.2530633972407
Trimmed Mean ( 20 / 28 )-33.72727272727270.91750859710107-36.7596258322116
Trimmed Mean ( 21 / 28 )-33.73809523809520.905563860001424-37.2564506251853
Trimmed Mean ( 22 / 28 )-33.7250.895134641068608-37.6758963989364
Trimmed Mean ( 23 / 28 )-33.71052631578950.879599591060016-38.3248544660696
Trimmed Mean ( 24 / 28 )-33.69444444444440.857107950494397-39.3117861350006
Trimmed Mean ( 25 / 28 )-33.67647058823530.843049160095319-39.9460342080498
Trimmed Mean ( 26 / 28 )-33.656250.821349910454263-40.9767500691463
Trimmed Mean ( 27 / 28 )-33.63333333333330.788543446034221-42.652479711148
Trimmed Mean ( 28 / 28 )-33.64285714285710.752797754753295-44.6904323643772
Median-33
Midrange-40.5
Midmean - Weighted Average at Xnp-33.953488372093
Midmean - Weighted Average at X(n+1)p-33.953488372093
Midmean - Empirical Distribution Function-33.953488372093
Midmean - Empirical Distribution Function - Averaging-33.953488372093
Midmean - Empirical Distribution Function - Interpolation-33.953488372093
Midmean - Closest Observation-33.953488372093
Midmean - True Basic - Statistics Graphics Toolkit-33.953488372093
Midmean - MS Excel (old versions)-33.3043478260870
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')