Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 22 Oct 2007 13:20:47 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Oct/22/tdxeadfgc8neuac1193084146.htm/, Retrieved Thu, 31 Oct 2024 23:01:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=1597, Retrieved Thu, 31 Oct 2024 23:01:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact187
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Central Tendency ...] [2007-10-22 20:20:47] [d9ccf6bb4f7743d5d52b9a9a992ccbd5] [Current]
Feedback Forum

Post a new message
Dataseries X:
89.28
89.47
89.53
90.72
90.91
91.38
91.49
90.9
90.93
90.57
91.28
90.83
91.5
91.58
92.49
94.16
95.46
95.8
95.32
95.41
95.35
95.68
95.59
94.96
96.92
96.06
96.59
96.67
97.27
96.38
96.47
96.05
96.76
96.51
96.55
95.97
97
97.46
97.9
98.42
98.54
99
98.94
99.02
100.07
98.72
98.73
98.04
99.08
99.22
99.57
100.44
100.84
100.75
100.49
99.98
99.96
99.76
100.11
99.79
100.29
101.12
102.65
102.71
103.39
102.8
102.07
102.15
101.21
101.27
101.86
101.65
101.94
102.62
102.71
103.39
104.51
104.09
104.29
104.57
105.39
105.15
106.13
105.46
106.47
106.62
106.52
108.04
107.15
107.32
107.76
107.26
107.89




Summary of compuational 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 compuational 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=1597&T=0

[TABLE]
[ROW][C]Summary of compuational 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=1597&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=1597&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 compuational 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 Mean98.91473118279570.517967956453865190.966892739833
Geometric Mean98.7893062182587
Harmonic Mean98.6632614652913
Quadratic Mean99.0394204290632
Winsorized Mean ( 1 / 31 )98.91516129032260.517252144096835191.231998589463
Winsorized Mean ( 2 / 31 )98.91365591397850.516472798045321191.517648728711
Winsorized Mean ( 3 / 31 )98.93301075268820.507556890252771194.920042762927
Winsorized Mean ( 4 / 31 )98.93688172043010.505947215445985195.547833252168
Winsorized Mean ( 5 / 31 )98.93688172043010.503855401853514196.359672549852
Winsorized Mean ( 6 / 31 )98.90720430107530.497151972084148198.947625383922
Winsorized Mean ( 7 / 31 )98.90043010752690.495756794505365199.493846990445
Winsorized Mean ( 8 / 31 )98.89784946236560.494738465139702199.899252697967
Winsorized Mean ( 9 / 31 )98.8988172043010.483459822467888204.56470756858
Winsorized Mean ( 10 / 31 )98.83752688172040.470237018009980210.186614614043
Winsorized Mean ( 11 / 31 )98.84225806451610.466736732427108211.773042911193
Winsorized Mean ( 12 / 31 )98.81258064516130.461844430780293213.952088754683
Winsorized Mean ( 13 / 31 )98.7426881720430.448130085608533220.343804942166
Winsorized Mean ( 14 / 31 )98.87064516129030.423708162508617233.346095047861
Winsorized Mean ( 15 / 31 )99.10451612903220.377088930652432262.814705161362
Winsorized Mean ( 16 / 31 )99.20774193548390.353098855166872280.963080122701
Winsorized Mean ( 17 / 31 )99.14559139784950.325899283121018304.221569462714
Winsorized Mean ( 18 / 31 )99.15139784946240.325159923662194304.931175812644
Winsorized Mean ( 19 / 31 )99.04311827956990.307022451697045322.592428443315
Winsorized Mean ( 20 / 31 )99.03451612903230.303078814102781326.761593093232
Winsorized Mean ( 21 / 31 )99.0638709677420.299345633241366330.934745548352
Winsorized Mean ( 22 / 31 )99.07096774193550.294795674301086336.066558564053
Winsorized Mean ( 23 / 31 )99.09322580645160.2901297110122341.548011269638
Winsorized Mean ( 24 / 31 )99.0158064516130.269018193212127368.063606662976
Winsorized Mean ( 25 / 31 )99.0158064516130.26366453757117375.53706449767
Winsorized Mean ( 26 / 31 )98.98225806451610.258776119754184382.501515822021
Winsorized Mean ( 27 / 31 )99.0519354838710.244663772019033404.849212723514
Winsorized Mean ( 28 / 31 )99.0158064516130.233631029083967423.81273942866
Winsorized Mean ( 29 / 31 )98.90978494623660.217899572971656453.923720901934
Winsorized Mean ( 30 / 31 )98.90333333333330.214083570067225461.98469738839
Winsorized Mean ( 31 / 31 )98.88666666666670.208991452329137473.161297099041
Trimmed Mean ( 1 / 31 )98.92032967032970.508702614934077194.456106114471
Trimmed Mean ( 2 / 31 )98.92573033707860.498929955301597198.275788586956
Trimmed Mean ( 3 / 31 )98.9321839080460.488206363911166202.644191516618
Trimmed Mean ( 4 / 31 )98.93188235294120.479702741000282206.23580792273
Trimmed Mean ( 5 / 31 )98.93048192771080.470434487700026210.295980661167
Trimmed Mean ( 6 / 31 )98.9290123456790.460315230318884214.915792113039
Trimmed Mean ( 7 / 31 )98.93329113924050.450292945201795219.708730046624
Trimmed Mean ( 8 / 31 )98.9389610389610.438940250552251225.40416586194
Trimmed Mean ( 9 / 31 )98.94533333333330.425881865501882232.330468489732
Trimmed Mean ( 10 / 31 )98.95191780821920.412940722430023239.627414864582
Trimmed Mean ( 11 / 31 )98.96690140845070.400338970636677247.207763089012
Trimmed Mean ( 12 / 31 )98.98217391304350.386078049654179256.378662298218
Trimmed Mean ( 13 / 31 )98.98217391304350.3699845318911267.530573256986
Trimmed Mean ( 14 / 31 )99.03030769230770.353274651354921280.321011746795
Trimmed Mean ( 15 / 31 )99.04714285714290.33804651214189292.998564693279
Trimmed Mean ( 16 / 31 )99.04131147540980.328511336349032301.485216845551
Trimmed Mean ( 17 / 31 )99.02491525423730.321099019822177308.393701447848
Trimmed Mean ( 18 / 31 )99.01333333333330.316641537058565312.698498918101
Trimmed Mean ( 19 / 31 )99.00036363636360.311102845882601318.223908738279
Trimmed Mean ( 20 / 31 )98.99641509433960.307219976967902322.233000833415
Trimmed Mean ( 21 / 31 )98.99294117647060.302813641534564326.910441269441
Trimmed Mean ( 22 / 31 )98.9865306122450.297685595086735332.520391466721
Trimmed Mean ( 23 / 31 )98.97893617021280.291785189897833339.218505931948
Trimmed Mean ( 24 / 31 )98.96866666666670.284890480463258347.391974999427
Trimmed Mean ( 25 / 31 )98.96441860465120.279997884489236353.447022591543
Trimmed Mean ( 26 / 31 )98.96441860465120.27436056208024360.709344864616
Trimmed Mean ( 27 / 31 )98.95769230769230.267641133210176369.740223114292
Trimmed Mean ( 28 / 31 )98.9489189189190.261503444755871378.384762813713
Trimmed Mean ( 29 / 31 )98.94257142857140.255437125042426387.346089226998
Trimmed Mean ( 30 / 31 )98.94575757575760.250587578557057394.854996985529
Trimmed Mean ( 31 / 31 )98.950.244165464784740405.257967531304
Median99.02
Midrange98.66
Midmean - Weighted Average at Xnp98.8997826086956
Midmean - Weighted Average at X(n+1)p98.9789361702127
Midmean - Empirical Distribution Function98.9789361702127
Midmean - Empirical Distribution Function - Averaging98.9789361702127
Midmean - Empirical Distribution Function - Interpolation98.9789361702127
Midmean - Closest Observation98.9102083333333
Midmean - True Basic - Statistics Graphics Toolkit98.9789361702127
Midmean - MS Excel (old versions)98.9789361702127
Number of observations93

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 98.9147311827957 & 0.517967956453865 & 190.966892739833 \tabularnewline
Geometric Mean & 98.7893062182587 &  &  \tabularnewline
Harmonic Mean & 98.6632614652913 &  &  \tabularnewline
Quadratic Mean & 99.0394204290632 &  &  \tabularnewline
Winsorized Mean ( 1 / 31 ) & 98.9151612903226 & 0.517252144096835 & 191.231998589463 \tabularnewline
Winsorized Mean ( 2 / 31 ) & 98.9136559139785 & 0.516472798045321 & 191.517648728711 \tabularnewline
Winsorized Mean ( 3 / 31 ) & 98.9330107526882 & 0.507556890252771 & 194.920042762927 \tabularnewline
Winsorized Mean ( 4 / 31 ) & 98.9368817204301 & 0.505947215445985 & 195.547833252168 \tabularnewline
Winsorized Mean ( 5 / 31 ) & 98.9368817204301 & 0.503855401853514 & 196.359672549852 \tabularnewline
Winsorized Mean ( 6 / 31 ) & 98.9072043010753 & 0.497151972084148 & 198.947625383922 \tabularnewline
Winsorized Mean ( 7 / 31 ) & 98.9004301075269 & 0.495756794505365 & 199.493846990445 \tabularnewline
Winsorized Mean ( 8 / 31 ) & 98.8978494623656 & 0.494738465139702 & 199.899252697967 \tabularnewline
Winsorized Mean ( 9 / 31 ) & 98.898817204301 & 0.483459822467888 & 204.56470756858 \tabularnewline
Winsorized Mean ( 10 / 31 ) & 98.8375268817204 & 0.470237018009980 & 210.186614614043 \tabularnewline
Winsorized Mean ( 11 / 31 ) & 98.8422580645161 & 0.466736732427108 & 211.773042911193 \tabularnewline
Winsorized Mean ( 12 / 31 ) & 98.8125806451613 & 0.461844430780293 & 213.952088754683 \tabularnewline
Winsorized Mean ( 13 / 31 ) & 98.742688172043 & 0.448130085608533 & 220.343804942166 \tabularnewline
Winsorized Mean ( 14 / 31 ) & 98.8706451612903 & 0.423708162508617 & 233.346095047861 \tabularnewline
Winsorized Mean ( 15 / 31 ) & 99.1045161290322 & 0.377088930652432 & 262.814705161362 \tabularnewline
Winsorized Mean ( 16 / 31 ) & 99.2077419354839 & 0.353098855166872 & 280.963080122701 \tabularnewline
Winsorized Mean ( 17 / 31 ) & 99.1455913978495 & 0.325899283121018 & 304.221569462714 \tabularnewline
Winsorized Mean ( 18 / 31 ) & 99.1513978494624 & 0.325159923662194 & 304.931175812644 \tabularnewline
Winsorized Mean ( 19 / 31 ) & 99.0431182795699 & 0.307022451697045 & 322.592428443315 \tabularnewline
Winsorized Mean ( 20 / 31 ) & 99.0345161290323 & 0.303078814102781 & 326.761593093232 \tabularnewline
Winsorized Mean ( 21 / 31 ) & 99.063870967742 & 0.299345633241366 & 330.934745548352 \tabularnewline
Winsorized Mean ( 22 / 31 ) & 99.0709677419355 & 0.294795674301086 & 336.066558564053 \tabularnewline
Winsorized Mean ( 23 / 31 ) & 99.0932258064516 & 0.2901297110122 & 341.548011269638 \tabularnewline
Winsorized Mean ( 24 / 31 ) & 99.015806451613 & 0.269018193212127 & 368.063606662976 \tabularnewline
Winsorized Mean ( 25 / 31 ) & 99.015806451613 & 0.26366453757117 & 375.53706449767 \tabularnewline
Winsorized Mean ( 26 / 31 ) & 98.9822580645161 & 0.258776119754184 & 382.501515822021 \tabularnewline
Winsorized Mean ( 27 / 31 ) & 99.051935483871 & 0.244663772019033 & 404.849212723514 \tabularnewline
Winsorized Mean ( 28 / 31 ) & 99.015806451613 & 0.233631029083967 & 423.81273942866 \tabularnewline
Winsorized Mean ( 29 / 31 ) & 98.9097849462366 & 0.217899572971656 & 453.923720901934 \tabularnewline
Winsorized Mean ( 30 / 31 ) & 98.9033333333333 & 0.214083570067225 & 461.98469738839 \tabularnewline
Winsorized Mean ( 31 / 31 ) & 98.8866666666667 & 0.208991452329137 & 473.161297099041 \tabularnewline
Trimmed Mean ( 1 / 31 ) & 98.9203296703297 & 0.508702614934077 & 194.456106114471 \tabularnewline
Trimmed Mean ( 2 / 31 ) & 98.9257303370786 & 0.498929955301597 & 198.275788586956 \tabularnewline
Trimmed Mean ( 3 / 31 ) & 98.932183908046 & 0.488206363911166 & 202.644191516618 \tabularnewline
Trimmed Mean ( 4 / 31 ) & 98.9318823529412 & 0.479702741000282 & 206.23580792273 \tabularnewline
Trimmed Mean ( 5 / 31 ) & 98.9304819277108 & 0.470434487700026 & 210.295980661167 \tabularnewline
Trimmed Mean ( 6 / 31 ) & 98.929012345679 & 0.460315230318884 & 214.915792113039 \tabularnewline
Trimmed Mean ( 7 / 31 ) & 98.9332911392405 & 0.450292945201795 & 219.708730046624 \tabularnewline
Trimmed Mean ( 8 / 31 ) & 98.938961038961 & 0.438940250552251 & 225.40416586194 \tabularnewline
Trimmed Mean ( 9 / 31 ) & 98.9453333333333 & 0.425881865501882 & 232.330468489732 \tabularnewline
Trimmed Mean ( 10 / 31 ) & 98.9519178082192 & 0.412940722430023 & 239.627414864582 \tabularnewline
Trimmed Mean ( 11 / 31 ) & 98.9669014084507 & 0.400338970636677 & 247.207763089012 \tabularnewline
Trimmed Mean ( 12 / 31 ) & 98.9821739130435 & 0.386078049654179 & 256.378662298218 \tabularnewline
Trimmed Mean ( 13 / 31 ) & 98.9821739130435 & 0.3699845318911 & 267.530573256986 \tabularnewline
Trimmed Mean ( 14 / 31 ) & 99.0303076923077 & 0.353274651354921 & 280.321011746795 \tabularnewline
Trimmed Mean ( 15 / 31 ) & 99.0471428571429 & 0.33804651214189 & 292.998564693279 \tabularnewline
Trimmed Mean ( 16 / 31 ) & 99.0413114754098 & 0.328511336349032 & 301.485216845551 \tabularnewline
Trimmed Mean ( 17 / 31 ) & 99.0249152542373 & 0.321099019822177 & 308.393701447848 \tabularnewline
Trimmed Mean ( 18 / 31 ) & 99.0133333333333 & 0.316641537058565 & 312.698498918101 \tabularnewline
Trimmed Mean ( 19 / 31 ) & 99.0003636363636 & 0.311102845882601 & 318.223908738279 \tabularnewline
Trimmed Mean ( 20 / 31 ) & 98.9964150943396 & 0.307219976967902 & 322.233000833415 \tabularnewline
Trimmed Mean ( 21 / 31 ) & 98.9929411764706 & 0.302813641534564 & 326.910441269441 \tabularnewline
Trimmed Mean ( 22 / 31 ) & 98.986530612245 & 0.297685595086735 & 332.520391466721 \tabularnewline
Trimmed Mean ( 23 / 31 ) & 98.9789361702128 & 0.291785189897833 & 339.218505931948 \tabularnewline
Trimmed Mean ( 24 / 31 ) & 98.9686666666667 & 0.284890480463258 & 347.391974999427 \tabularnewline
Trimmed Mean ( 25 / 31 ) & 98.9644186046512 & 0.279997884489236 & 353.447022591543 \tabularnewline
Trimmed Mean ( 26 / 31 ) & 98.9644186046512 & 0.27436056208024 & 360.709344864616 \tabularnewline
Trimmed Mean ( 27 / 31 ) & 98.9576923076923 & 0.267641133210176 & 369.740223114292 \tabularnewline
Trimmed Mean ( 28 / 31 ) & 98.948918918919 & 0.261503444755871 & 378.384762813713 \tabularnewline
Trimmed Mean ( 29 / 31 ) & 98.9425714285714 & 0.255437125042426 & 387.346089226998 \tabularnewline
Trimmed Mean ( 30 / 31 ) & 98.9457575757576 & 0.250587578557057 & 394.854996985529 \tabularnewline
Trimmed Mean ( 31 / 31 ) & 98.95 & 0.244165464784740 & 405.257967531304 \tabularnewline
Median & 99.02 &  &  \tabularnewline
Midrange & 98.66 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 98.8997826086956 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 98.9789361702127 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 98.9789361702127 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 98.9789361702127 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 98.9789361702127 &  &  \tabularnewline
Midmean - Closest Observation & 98.9102083333333 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 98.9789361702127 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 98.9789361702127 &  &  \tabularnewline
Number of observations & 93 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=1597&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]98.9147311827957[/C][C]0.517967956453865[/C][C]190.966892739833[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]98.7893062182587[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]98.6632614652913[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]99.0394204290632[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 31 )[/C][C]98.9151612903226[/C][C]0.517252144096835[/C][C]191.231998589463[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 31 )[/C][C]98.9136559139785[/C][C]0.516472798045321[/C][C]191.517648728711[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 31 )[/C][C]98.9330107526882[/C][C]0.507556890252771[/C][C]194.920042762927[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 31 )[/C][C]98.9368817204301[/C][C]0.505947215445985[/C][C]195.547833252168[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 31 )[/C][C]98.9368817204301[/C][C]0.503855401853514[/C][C]196.359672549852[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 31 )[/C][C]98.9072043010753[/C][C]0.497151972084148[/C][C]198.947625383922[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 31 )[/C][C]98.9004301075269[/C][C]0.495756794505365[/C][C]199.493846990445[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 31 )[/C][C]98.8978494623656[/C][C]0.494738465139702[/C][C]199.899252697967[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 31 )[/C][C]98.898817204301[/C][C]0.483459822467888[/C][C]204.56470756858[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 31 )[/C][C]98.8375268817204[/C][C]0.470237018009980[/C][C]210.186614614043[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 31 )[/C][C]98.8422580645161[/C][C]0.466736732427108[/C][C]211.773042911193[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 31 )[/C][C]98.8125806451613[/C][C]0.461844430780293[/C][C]213.952088754683[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 31 )[/C][C]98.742688172043[/C][C]0.448130085608533[/C][C]220.343804942166[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 31 )[/C][C]98.8706451612903[/C][C]0.423708162508617[/C][C]233.346095047861[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 31 )[/C][C]99.1045161290322[/C][C]0.377088930652432[/C][C]262.814705161362[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 31 )[/C][C]99.2077419354839[/C][C]0.353098855166872[/C][C]280.963080122701[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 31 )[/C][C]99.1455913978495[/C][C]0.325899283121018[/C][C]304.221569462714[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 31 )[/C][C]99.1513978494624[/C][C]0.325159923662194[/C][C]304.931175812644[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 31 )[/C][C]99.0431182795699[/C][C]0.307022451697045[/C][C]322.592428443315[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 31 )[/C][C]99.0345161290323[/C][C]0.303078814102781[/C][C]326.761593093232[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 31 )[/C][C]99.063870967742[/C][C]0.299345633241366[/C][C]330.934745548352[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 31 )[/C][C]99.0709677419355[/C][C]0.294795674301086[/C][C]336.066558564053[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 31 )[/C][C]99.0932258064516[/C][C]0.2901297110122[/C][C]341.548011269638[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 31 )[/C][C]99.015806451613[/C][C]0.269018193212127[/C][C]368.063606662976[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 31 )[/C][C]99.015806451613[/C][C]0.26366453757117[/C][C]375.53706449767[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 31 )[/C][C]98.9822580645161[/C][C]0.258776119754184[/C][C]382.501515822021[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 31 )[/C][C]99.051935483871[/C][C]0.244663772019033[/C][C]404.849212723514[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 31 )[/C][C]99.015806451613[/C][C]0.233631029083967[/C][C]423.81273942866[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 31 )[/C][C]98.9097849462366[/C][C]0.217899572971656[/C][C]453.923720901934[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 31 )[/C][C]98.9033333333333[/C][C]0.214083570067225[/C][C]461.98469738839[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 31 )[/C][C]98.8866666666667[/C][C]0.208991452329137[/C][C]473.161297099041[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 31 )[/C][C]98.9203296703297[/C][C]0.508702614934077[/C][C]194.456106114471[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 31 )[/C][C]98.9257303370786[/C][C]0.498929955301597[/C][C]198.275788586956[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 31 )[/C][C]98.932183908046[/C][C]0.488206363911166[/C][C]202.644191516618[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 31 )[/C][C]98.9318823529412[/C][C]0.479702741000282[/C][C]206.23580792273[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 31 )[/C][C]98.9304819277108[/C][C]0.470434487700026[/C][C]210.295980661167[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 31 )[/C][C]98.929012345679[/C][C]0.460315230318884[/C][C]214.915792113039[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 31 )[/C][C]98.9332911392405[/C][C]0.450292945201795[/C][C]219.708730046624[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 31 )[/C][C]98.938961038961[/C][C]0.438940250552251[/C][C]225.40416586194[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 31 )[/C][C]98.9453333333333[/C][C]0.425881865501882[/C][C]232.330468489732[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 31 )[/C][C]98.9519178082192[/C][C]0.412940722430023[/C][C]239.627414864582[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 31 )[/C][C]98.9669014084507[/C][C]0.400338970636677[/C][C]247.207763089012[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 31 )[/C][C]98.9821739130435[/C][C]0.386078049654179[/C][C]256.378662298218[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 31 )[/C][C]98.9821739130435[/C][C]0.3699845318911[/C][C]267.530573256986[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 31 )[/C][C]99.0303076923077[/C][C]0.353274651354921[/C][C]280.321011746795[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 31 )[/C][C]99.0471428571429[/C][C]0.33804651214189[/C][C]292.998564693279[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 31 )[/C][C]99.0413114754098[/C][C]0.328511336349032[/C][C]301.485216845551[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 31 )[/C][C]99.0249152542373[/C][C]0.321099019822177[/C][C]308.393701447848[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 31 )[/C][C]99.0133333333333[/C][C]0.316641537058565[/C][C]312.698498918101[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 31 )[/C][C]99.0003636363636[/C][C]0.311102845882601[/C][C]318.223908738279[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 31 )[/C][C]98.9964150943396[/C][C]0.307219976967902[/C][C]322.233000833415[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 31 )[/C][C]98.9929411764706[/C][C]0.302813641534564[/C][C]326.910441269441[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 31 )[/C][C]98.986530612245[/C][C]0.297685595086735[/C][C]332.520391466721[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 31 )[/C][C]98.9789361702128[/C][C]0.291785189897833[/C][C]339.218505931948[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 31 )[/C][C]98.9686666666667[/C][C]0.284890480463258[/C][C]347.391974999427[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 31 )[/C][C]98.9644186046512[/C][C]0.279997884489236[/C][C]353.447022591543[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 31 )[/C][C]98.9644186046512[/C][C]0.27436056208024[/C][C]360.709344864616[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 31 )[/C][C]98.9576923076923[/C][C]0.267641133210176[/C][C]369.740223114292[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 31 )[/C][C]98.948918918919[/C][C]0.261503444755871[/C][C]378.384762813713[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 31 )[/C][C]98.9425714285714[/C][C]0.255437125042426[/C][C]387.346089226998[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 31 )[/C][C]98.9457575757576[/C][C]0.250587578557057[/C][C]394.854996985529[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 31 )[/C][C]98.95[/C][C]0.244165464784740[/C][C]405.257967531304[/C][/ROW]
[ROW][C]Median[/C][C]99.02[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]98.66[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]98.8997826086956[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]98.9789361702127[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]98.9789361702127[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]98.9789361702127[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]98.9789361702127[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]98.9102083333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]98.9789361702127[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]98.9789361702127[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]93[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=1597&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=1597&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 Mean98.91473118279570.517967956453865190.966892739833
Geometric Mean98.7893062182587
Harmonic Mean98.6632614652913
Quadratic Mean99.0394204290632
Winsorized Mean ( 1 / 31 )98.91516129032260.517252144096835191.231998589463
Winsorized Mean ( 2 / 31 )98.91365591397850.516472798045321191.517648728711
Winsorized Mean ( 3 / 31 )98.93301075268820.507556890252771194.920042762927
Winsorized Mean ( 4 / 31 )98.93688172043010.505947215445985195.547833252168
Winsorized Mean ( 5 / 31 )98.93688172043010.503855401853514196.359672549852
Winsorized Mean ( 6 / 31 )98.90720430107530.497151972084148198.947625383922
Winsorized Mean ( 7 / 31 )98.90043010752690.495756794505365199.493846990445
Winsorized Mean ( 8 / 31 )98.89784946236560.494738465139702199.899252697967
Winsorized Mean ( 9 / 31 )98.8988172043010.483459822467888204.56470756858
Winsorized Mean ( 10 / 31 )98.83752688172040.470237018009980210.186614614043
Winsorized Mean ( 11 / 31 )98.84225806451610.466736732427108211.773042911193
Winsorized Mean ( 12 / 31 )98.81258064516130.461844430780293213.952088754683
Winsorized Mean ( 13 / 31 )98.7426881720430.448130085608533220.343804942166
Winsorized Mean ( 14 / 31 )98.87064516129030.423708162508617233.346095047861
Winsorized Mean ( 15 / 31 )99.10451612903220.377088930652432262.814705161362
Winsorized Mean ( 16 / 31 )99.20774193548390.353098855166872280.963080122701
Winsorized Mean ( 17 / 31 )99.14559139784950.325899283121018304.221569462714
Winsorized Mean ( 18 / 31 )99.15139784946240.325159923662194304.931175812644
Winsorized Mean ( 19 / 31 )99.04311827956990.307022451697045322.592428443315
Winsorized Mean ( 20 / 31 )99.03451612903230.303078814102781326.761593093232
Winsorized Mean ( 21 / 31 )99.0638709677420.299345633241366330.934745548352
Winsorized Mean ( 22 / 31 )99.07096774193550.294795674301086336.066558564053
Winsorized Mean ( 23 / 31 )99.09322580645160.2901297110122341.548011269638
Winsorized Mean ( 24 / 31 )99.0158064516130.269018193212127368.063606662976
Winsorized Mean ( 25 / 31 )99.0158064516130.26366453757117375.53706449767
Winsorized Mean ( 26 / 31 )98.98225806451610.258776119754184382.501515822021
Winsorized Mean ( 27 / 31 )99.0519354838710.244663772019033404.849212723514
Winsorized Mean ( 28 / 31 )99.0158064516130.233631029083967423.81273942866
Winsorized Mean ( 29 / 31 )98.90978494623660.217899572971656453.923720901934
Winsorized Mean ( 30 / 31 )98.90333333333330.214083570067225461.98469738839
Winsorized Mean ( 31 / 31 )98.88666666666670.208991452329137473.161297099041
Trimmed Mean ( 1 / 31 )98.92032967032970.508702614934077194.456106114471
Trimmed Mean ( 2 / 31 )98.92573033707860.498929955301597198.275788586956
Trimmed Mean ( 3 / 31 )98.9321839080460.488206363911166202.644191516618
Trimmed Mean ( 4 / 31 )98.93188235294120.479702741000282206.23580792273
Trimmed Mean ( 5 / 31 )98.93048192771080.470434487700026210.295980661167
Trimmed Mean ( 6 / 31 )98.9290123456790.460315230318884214.915792113039
Trimmed Mean ( 7 / 31 )98.93329113924050.450292945201795219.708730046624
Trimmed Mean ( 8 / 31 )98.9389610389610.438940250552251225.40416586194
Trimmed Mean ( 9 / 31 )98.94533333333330.425881865501882232.330468489732
Trimmed Mean ( 10 / 31 )98.95191780821920.412940722430023239.627414864582
Trimmed Mean ( 11 / 31 )98.96690140845070.400338970636677247.207763089012
Trimmed Mean ( 12 / 31 )98.98217391304350.386078049654179256.378662298218
Trimmed Mean ( 13 / 31 )98.98217391304350.3699845318911267.530573256986
Trimmed Mean ( 14 / 31 )99.03030769230770.353274651354921280.321011746795
Trimmed Mean ( 15 / 31 )99.04714285714290.33804651214189292.998564693279
Trimmed Mean ( 16 / 31 )99.04131147540980.328511336349032301.485216845551
Trimmed Mean ( 17 / 31 )99.02491525423730.321099019822177308.393701447848
Trimmed Mean ( 18 / 31 )99.01333333333330.316641537058565312.698498918101
Trimmed Mean ( 19 / 31 )99.00036363636360.311102845882601318.223908738279
Trimmed Mean ( 20 / 31 )98.99641509433960.307219976967902322.233000833415
Trimmed Mean ( 21 / 31 )98.99294117647060.302813641534564326.910441269441
Trimmed Mean ( 22 / 31 )98.9865306122450.297685595086735332.520391466721
Trimmed Mean ( 23 / 31 )98.97893617021280.291785189897833339.218505931948
Trimmed Mean ( 24 / 31 )98.96866666666670.284890480463258347.391974999427
Trimmed Mean ( 25 / 31 )98.96441860465120.279997884489236353.447022591543
Trimmed Mean ( 26 / 31 )98.96441860465120.27436056208024360.709344864616
Trimmed Mean ( 27 / 31 )98.95769230769230.267641133210176369.740223114292
Trimmed Mean ( 28 / 31 )98.9489189189190.261503444755871378.384762813713
Trimmed Mean ( 29 / 31 )98.94257142857140.255437125042426387.346089226998
Trimmed Mean ( 30 / 31 )98.94575757575760.250587578557057394.854996985529
Trimmed Mean ( 31 / 31 )98.950.244165464784740405.257967531304
Median99.02
Midrange98.66
Midmean - Weighted Average at Xnp98.8997826086956
Midmean - Weighted Average at X(n+1)p98.9789361702127
Midmean - Empirical Distribution Function98.9789361702127
Midmean - Empirical Distribution Function - Averaging98.9789361702127
Midmean - Empirical Distribution Function - Interpolation98.9789361702127
Midmean - Closest Observation98.9102083333333
Midmean - True Basic - Statistics Graphics Toolkit98.9789361702127
Midmean - MS Excel (old versions)98.9789361702127
Number of observations93



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')