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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 17 May 2011 14:27:01 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/May/17/t1305642222hnl9be39alkagoq.htm/, Retrieved Thu, 09 May 2024 20:07:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=121734, Retrieved Thu, 09 May 2024 20:07:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W52
Estimated Impact125
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2011-05-17 14:27:01] [7ec7c2b78d31d17737f91280a6e28d4a] [Current]
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Dataseries X:
90
51
47
59
54
79
59
80
46
62
55
77
72
72
71
50
66
78
59
52
71
98
70
84
90
98
98
78
59
0
58
55
62
80
91
86
61
49
61
56
73
85
82
32
39
30
51
48
57
59
32
56
54
74
62
78
72
48
59
61
80
69
58
63
27
23
34
45
51
51
73
37
35
66
54
30
66
61
37
55
64
53
63
70
72
52
53
50
60
73
66
78




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121734&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121734&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121734&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean60.92391304347831.8524936832681932.8875145938396
Geometric Mean0
Harmonic Mean0
Quadratic Mean63.435091783375
Winsorized Mean ( 1 / 30 )61.17391304347831.7774943239246634.4158134403535
Winsorized Mean ( 2 / 30 )61.26086956521741.7579163357731134.8485694788629
Winsorized Mean ( 3 / 30 )61.13043478260871.6890514327008336.1921689293142
Winsorized Mean ( 4 / 30 )61.08695652173911.6807169321735436.3457732544766
Winsorized Mean ( 5 / 30 )61.1956521739131.6591577317982336.8835650770755
Winsorized Mean ( 6 / 30 )60.93478260869561.6119480686935537.8019514351242
Winsorized Mean ( 7 / 30 )61.01086956521741.5696517552870238.8690480928116
Winsorized Mean ( 8 / 30 )61.01086956521741.5389119583588539.645458100333
Winsorized Mean ( 9 / 30 )61.01086956521741.4717838733996841.4536880501945
Winsorized Mean ( 10 / 30 )60.79347826086961.4387924646056542.2531252813673
Winsorized Mean ( 11 / 30 )61.03260869565221.396317172148143.7097028619646
Winsorized Mean ( 12 / 30 )61.81521739130441.2710651551832448.6326111129943
Winsorized Mean ( 13 / 30 )61.81521739130441.2288273135836450.3042345397027
Winsorized Mean ( 14 / 30 )61.81521739130441.1844801202375552.1876360228885
Winsorized Mean ( 15 / 30 )61.97826086956521.1624991470150453.3146721257451
Winsorized Mean ( 16 / 30 )61.97826086956521.1624991470150453.3146721257451
Winsorized Mean ( 17 / 30 )62.16304347826091.1385480789675354.5985230018852
Winsorized Mean ( 18 / 30 )62.16304347826091.0843847980896957.3256316279708
Winsorized Mean ( 19 / 30 )61.54347826086960.9950202147584261.8514853749093
Winsorized Mean ( 20 / 30 )61.54347826086960.93817648546943665.5990415599417
Winsorized Mean ( 21 / 30 )61.54347826086960.93817648546943665.5990415599417
Winsorized Mean ( 22 / 30 )61.54347826086960.93817648546943665.5990415599417
Winsorized Mean ( 23 / 30 )61.29347826086960.90514509102389267.7167438333394
Winsorized Mean ( 24 / 30 )61.5543478260870.87314941571207270.4969238007083
Winsorized Mean ( 25 / 30 )61.5543478260870.87314941571207270.4969238007083
Winsorized Mean ( 26 / 30 )61.83695652173910.83980595981836873.6324335387107
Winsorized Mean ( 27 / 30 )61.54347826086960.80124918051635676.80941180022
Winsorized Mean ( 28 / 30 )61.84782608695650.76627660371377380.7121420479366
Winsorized Mean ( 29 / 30 )61.53260869565220.72535986866676784.8304563757448
Winsorized Mean ( 30 / 30 )61.53260869565220.72535986866676784.8304563757448
Trimmed Mean ( 1 / 30 )61.18888888888891.7178576243650535.6193016353759
Trimmed Mean ( 2 / 30 )61.20454545454551.6492421782489837.1107083372844
Trimmed Mean ( 3 / 30 )61.17441860465121.582236538967438.66325741951
Trimmed Mean ( 4 / 30 )61.19047619047621.5355302606699839.8497364446453
Trimmed Mean ( 5 / 30 )61.2195121951221.484439453426641.2408280134337
Trimmed Mean ( 6 / 30 )61.2251.4316688279456942.7647782817567
Trimmed Mean ( 7 / 30 )61.28205128205131.382890725451844.3144567782317
Trimmed Mean ( 8 / 30 )61.3289473684211.3363196589290545.8939198855842
Trimmed Mean ( 9 / 30 )61.37837837837841.2887033314359747.6280124999646
Trimmed Mean ( 10 / 30 )61.43055555555561.2471918988614549.2550950752926
Trimmed Mean ( 11 / 30 )61.51428571428571.2046739302898651.0630172759566
Trimmed Mean ( 12 / 30 )61.57352941176471.162842211560252.9508894668958
Trimmed Mean ( 13 / 30 )61.57352941176471.1370394260952554.152501662336
Trimmed Mean ( 14 / 30 )61.5156251.1135867679850355.2409805580833
Trimmed Mean ( 15 / 30 )61.48387096774191.0929179103164956.2566231071619
Trimmed Mean ( 16 / 30 )61.43333333333331.0712911758375957.3451314814587
Trimmed Mean ( 17 / 30 )61.37931034482761.0446266121183558.7571766148668
Trimmed Mean ( 18 / 30 )61.30357142857141.0157588305573860.3524868151355
Trimmed Mean ( 19 / 30 )61.22222222222220.98969768823247761.8595182651789
Trimmed Mean ( 20 / 30 )61.19230769230770.97364922153211462.848412281393
Trimmed Mean ( 21 / 30 )61.160.96271724290983763.5285183166995
Trimmed Mean ( 22 / 30 )61.1250.9479471100247464.4814455928926
Trimmed Mean ( 23 / 30 )61.08695652173910.9282605867245565.8079825809366
Trimmed Mean ( 24 / 30 )61.06818181818180.90884642589916767.193070333928
Trimmed Mean ( 25 / 30 )61.02380952380950.88901418424495868.6421101094548
Trimmed Mean ( 26 / 30 )61.02380952380950.86193543395528970.7985855086392
Trimmed Mean ( 27 / 30 )60.89473684210530.83213334779492673.1790607881183
Trimmed Mean ( 28 / 30 )60.83333333333330.80128864466151875.9193752945678
Trimmed Mean ( 29 / 30 )60.7352941176470.76616137366618879.2721953953647
Trimmed Mean ( 30 / 30 )60.656250.72902024259474783.2024221770726
Median60.5
Midrange49
Midmean - Weighted Average at Xnp60.469387755102
Midmean - Weighted Average at X(n+1)p60.469387755102
Midmean - Empirical Distribution Function60.469387755102
Midmean - Empirical Distribution Function - Averaging60.469387755102
Midmean - Empirical Distribution Function - Interpolation60.469387755102
Midmean - Closest Observation60.469387755102
Midmean - True Basic - Statistics Graphics Toolkit60.469387755102
Midmean - MS Excel (old versions)61.1923076923077
Number of observations92

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 60.9239130434783 & 1.85249368326819 & 32.8875145938396 \tabularnewline
Geometric Mean & 0 &  &  \tabularnewline
Harmonic Mean & 0 &  &  \tabularnewline
Quadratic Mean & 63.435091783375 &  &  \tabularnewline
Winsorized Mean ( 1 / 30 ) & 61.1739130434783 & 1.77749432392466 & 34.4158134403535 \tabularnewline
Winsorized Mean ( 2 / 30 ) & 61.2608695652174 & 1.75791633577311 & 34.8485694788629 \tabularnewline
Winsorized Mean ( 3 / 30 ) & 61.1304347826087 & 1.68905143270083 & 36.1921689293142 \tabularnewline
Winsorized Mean ( 4 / 30 ) & 61.0869565217391 & 1.68071693217354 & 36.3457732544766 \tabularnewline
Winsorized Mean ( 5 / 30 ) & 61.195652173913 & 1.65915773179823 & 36.8835650770755 \tabularnewline
Winsorized Mean ( 6 / 30 ) & 60.9347826086956 & 1.61194806869355 & 37.8019514351242 \tabularnewline
Winsorized Mean ( 7 / 30 ) & 61.0108695652174 & 1.56965175528702 & 38.8690480928116 \tabularnewline
Winsorized Mean ( 8 / 30 ) & 61.0108695652174 & 1.53891195835885 & 39.645458100333 \tabularnewline
Winsorized Mean ( 9 / 30 ) & 61.0108695652174 & 1.47178387339968 & 41.4536880501945 \tabularnewline
Winsorized Mean ( 10 / 30 ) & 60.7934782608696 & 1.43879246460565 & 42.2531252813673 \tabularnewline
Winsorized Mean ( 11 / 30 ) & 61.0326086956522 & 1.3963171721481 & 43.7097028619646 \tabularnewline
Winsorized Mean ( 12 / 30 ) & 61.8152173913044 & 1.27106515518324 & 48.6326111129943 \tabularnewline
Winsorized Mean ( 13 / 30 ) & 61.8152173913044 & 1.22882731358364 & 50.3042345397027 \tabularnewline
Winsorized Mean ( 14 / 30 ) & 61.8152173913044 & 1.18448012023755 & 52.1876360228885 \tabularnewline
Winsorized Mean ( 15 / 30 ) & 61.9782608695652 & 1.16249914701504 & 53.3146721257451 \tabularnewline
Winsorized Mean ( 16 / 30 ) & 61.9782608695652 & 1.16249914701504 & 53.3146721257451 \tabularnewline
Winsorized Mean ( 17 / 30 ) & 62.1630434782609 & 1.13854807896753 & 54.5985230018852 \tabularnewline
Winsorized Mean ( 18 / 30 ) & 62.1630434782609 & 1.08438479808969 & 57.3256316279708 \tabularnewline
Winsorized Mean ( 19 / 30 ) & 61.5434782608696 & 0.99502021475842 & 61.8514853749093 \tabularnewline
Winsorized Mean ( 20 / 30 ) & 61.5434782608696 & 0.938176485469436 & 65.5990415599417 \tabularnewline
Winsorized Mean ( 21 / 30 ) & 61.5434782608696 & 0.938176485469436 & 65.5990415599417 \tabularnewline
Winsorized Mean ( 22 / 30 ) & 61.5434782608696 & 0.938176485469436 & 65.5990415599417 \tabularnewline
Winsorized Mean ( 23 / 30 ) & 61.2934782608696 & 0.905145091023892 & 67.7167438333394 \tabularnewline
Winsorized Mean ( 24 / 30 ) & 61.554347826087 & 0.873149415712072 & 70.4969238007083 \tabularnewline
Winsorized Mean ( 25 / 30 ) & 61.554347826087 & 0.873149415712072 & 70.4969238007083 \tabularnewline
Winsorized Mean ( 26 / 30 ) & 61.8369565217391 & 0.839805959818368 & 73.6324335387107 \tabularnewline
Winsorized Mean ( 27 / 30 ) & 61.5434782608696 & 0.801249180516356 & 76.80941180022 \tabularnewline
Winsorized Mean ( 28 / 30 ) & 61.8478260869565 & 0.766276603713773 & 80.7121420479366 \tabularnewline
Winsorized Mean ( 29 / 30 ) & 61.5326086956522 & 0.725359868666767 & 84.8304563757448 \tabularnewline
Winsorized Mean ( 30 / 30 ) & 61.5326086956522 & 0.725359868666767 & 84.8304563757448 \tabularnewline
Trimmed Mean ( 1 / 30 ) & 61.1888888888889 & 1.71785762436505 & 35.6193016353759 \tabularnewline
Trimmed Mean ( 2 / 30 ) & 61.2045454545455 & 1.64924217824898 & 37.1107083372844 \tabularnewline
Trimmed Mean ( 3 / 30 ) & 61.1744186046512 & 1.5822365389674 & 38.66325741951 \tabularnewline
Trimmed Mean ( 4 / 30 ) & 61.1904761904762 & 1.53553026066998 & 39.8497364446453 \tabularnewline
Trimmed Mean ( 5 / 30 ) & 61.219512195122 & 1.4844394534266 & 41.2408280134337 \tabularnewline
Trimmed Mean ( 6 / 30 ) & 61.225 & 1.43166882794569 & 42.7647782817567 \tabularnewline
Trimmed Mean ( 7 / 30 ) & 61.2820512820513 & 1.3828907254518 & 44.3144567782317 \tabularnewline
Trimmed Mean ( 8 / 30 ) & 61.328947368421 & 1.33631965892905 & 45.8939198855842 \tabularnewline
Trimmed Mean ( 9 / 30 ) & 61.3783783783784 & 1.28870333143597 & 47.6280124999646 \tabularnewline
Trimmed Mean ( 10 / 30 ) & 61.4305555555556 & 1.24719189886145 & 49.2550950752926 \tabularnewline
Trimmed Mean ( 11 / 30 ) & 61.5142857142857 & 1.20467393028986 & 51.0630172759566 \tabularnewline
Trimmed Mean ( 12 / 30 ) & 61.5735294117647 & 1.1628422115602 & 52.9508894668958 \tabularnewline
Trimmed Mean ( 13 / 30 ) & 61.5735294117647 & 1.13703942609525 & 54.152501662336 \tabularnewline
Trimmed Mean ( 14 / 30 ) & 61.515625 & 1.11358676798503 & 55.2409805580833 \tabularnewline
Trimmed Mean ( 15 / 30 ) & 61.4838709677419 & 1.09291791031649 & 56.2566231071619 \tabularnewline
Trimmed Mean ( 16 / 30 ) & 61.4333333333333 & 1.07129117583759 & 57.3451314814587 \tabularnewline
Trimmed Mean ( 17 / 30 ) & 61.3793103448276 & 1.04462661211835 & 58.7571766148668 \tabularnewline
Trimmed Mean ( 18 / 30 ) & 61.3035714285714 & 1.01575883055738 & 60.3524868151355 \tabularnewline
Trimmed Mean ( 19 / 30 ) & 61.2222222222222 & 0.989697688232477 & 61.8595182651789 \tabularnewline
Trimmed Mean ( 20 / 30 ) & 61.1923076923077 & 0.973649221532114 & 62.848412281393 \tabularnewline
Trimmed Mean ( 21 / 30 ) & 61.16 & 0.962717242909837 & 63.5285183166995 \tabularnewline
Trimmed Mean ( 22 / 30 ) & 61.125 & 0.94794711002474 & 64.4814455928926 \tabularnewline
Trimmed Mean ( 23 / 30 ) & 61.0869565217391 & 0.92826058672455 & 65.8079825809366 \tabularnewline
Trimmed Mean ( 24 / 30 ) & 61.0681818181818 & 0.908846425899167 & 67.193070333928 \tabularnewline
Trimmed Mean ( 25 / 30 ) & 61.0238095238095 & 0.889014184244958 & 68.6421101094548 \tabularnewline
Trimmed Mean ( 26 / 30 ) & 61.0238095238095 & 0.861935433955289 & 70.7985855086392 \tabularnewline
Trimmed Mean ( 27 / 30 ) & 60.8947368421053 & 0.832133347794926 & 73.1790607881183 \tabularnewline
Trimmed Mean ( 28 / 30 ) & 60.8333333333333 & 0.801288644661518 & 75.9193752945678 \tabularnewline
Trimmed Mean ( 29 / 30 ) & 60.735294117647 & 0.766161373666188 & 79.2721953953647 \tabularnewline
Trimmed Mean ( 30 / 30 ) & 60.65625 & 0.729020242594747 & 83.2024221770726 \tabularnewline
Median & 60.5 &  &  \tabularnewline
Midrange & 49 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 60.469387755102 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 60.469387755102 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 60.469387755102 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 60.469387755102 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 60.469387755102 &  &  \tabularnewline
Midmean - Closest Observation & 60.469387755102 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 60.469387755102 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 61.1923076923077 &  &  \tabularnewline
Number of observations & 92 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121734&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]60.9239130434783[/C][C]1.85249368326819[/C][C]32.8875145938396[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]0[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]0[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]63.435091783375[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 30 )[/C][C]61.1739130434783[/C][C]1.77749432392466[/C][C]34.4158134403535[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 30 )[/C][C]61.2608695652174[/C][C]1.75791633577311[/C][C]34.8485694788629[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 30 )[/C][C]61.1304347826087[/C][C]1.68905143270083[/C][C]36.1921689293142[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 30 )[/C][C]61.0869565217391[/C][C]1.68071693217354[/C][C]36.3457732544766[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 30 )[/C][C]61.195652173913[/C][C]1.65915773179823[/C][C]36.8835650770755[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 30 )[/C][C]60.9347826086956[/C][C]1.61194806869355[/C][C]37.8019514351242[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 30 )[/C][C]61.0108695652174[/C][C]1.56965175528702[/C][C]38.8690480928116[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 30 )[/C][C]61.0108695652174[/C][C]1.53891195835885[/C][C]39.645458100333[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 30 )[/C][C]61.0108695652174[/C][C]1.47178387339968[/C][C]41.4536880501945[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 30 )[/C][C]60.7934782608696[/C][C]1.43879246460565[/C][C]42.2531252813673[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 30 )[/C][C]61.0326086956522[/C][C]1.3963171721481[/C][C]43.7097028619646[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 30 )[/C][C]61.8152173913044[/C][C]1.27106515518324[/C][C]48.6326111129943[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 30 )[/C][C]61.8152173913044[/C][C]1.22882731358364[/C][C]50.3042345397027[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 30 )[/C][C]61.8152173913044[/C][C]1.18448012023755[/C][C]52.1876360228885[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 30 )[/C][C]61.9782608695652[/C][C]1.16249914701504[/C][C]53.3146721257451[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 30 )[/C][C]61.9782608695652[/C][C]1.16249914701504[/C][C]53.3146721257451[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 30 )[/C][C]62.1630434782609[/C][C]1.13854807896753[/C][C]54.5985230018852[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 30 )[/C][C]62.1630434782609[/C][C]1.08438479808969[/C][C]57.3256316279708[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 30 )[/C][C]61.5434782608696[/C][C]0.99502021475842[/C][C]61.8514853749093[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 30 )[/C][C]61.5434782608696[/C][C]0.938176485469436[/C][C]65.5990415599417[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 30 )[/C][C]61.5434782608696[/C][C]0.938176485469436[/C][C]65.5990415599417[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 30 )[/C][C]61.5434782608696[/C][C]0.938176485469436[/C][C]65.5990415599417[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 30 )[/C][C]61.2934782608696[/C][C]0.905145091023892[/C][C]67.7167438333394[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 30 )[/C][C]61.554347826087[/C][C]0.873149415712072[/C][C]70.4969238007083[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 30 )[/C][C]61.554347826087[/C][C]0.873149415712072[/C][C]70.4969238007083[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 30 )[/C][C]61.8369565217391[/C][C]0.839805959818368[/C][C]73.6324335387107[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 30 )[/C][C]61.5434782608696[/C][C]0.801249180516356[/C][C]76.80941180022[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 30 )[/C][C]61.8478260869565[/C][C]0.766276603713773[/C][C]80.7121420479366[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 30 )[/C][C]61.5326086956522[/C][C]0.725359868666767[/C][C]84.8304563757448[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 30 )[/C][C]61.5326086956522[/C][C]0.725359868666767[/C][C]84.8304563757448[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 30 )[/C][C]61.1888888888889[/C][C]1.71785762436505[/C][C]35.6193016353759[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 30 )[/C][C]61.2045454545455[/C][C]1.64924217824898[/C][C]37.1107083372844[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 30 )[/C][C]61.1744186046512[/C][C]1.5822365389674[/C][C]38.66325741951[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 30 )[/C][C]61.1904761904762[/C][C]1.53553026066998[/C][C]39.8497364446453[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 30 )[/C][C]61.219512195122[/C][C]1.4844394534266[/C][C]41.2408280134337[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 30 )[/C][C]61.225[/C][C]1.43166882794569[/C][C]42.7647782817567[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 30 )[/C][C]61.2820512820513[/C][C]1.3828907254518[/C][C]44.3144567782317[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 30 )[/C][C]61.328947368421[/C][C]1.33631965892905[/C][C]45.8939198855842[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 30 )[/C][C]61.3783783783784[/C][C]1.28870333143597[/C][C]47.6280124999646[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 30 )[/C][C]61.4305555555556[/C][C]1.24719189886145[/C][C]49.2550950752926[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 30 )[/C][C]61.5142857142857[/C][C]1.20467393028986[/C][C]51.0630172759566[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 30 )[/C][C]61.5735294117647[/C][C]1.1628422115602[/C][C]52.9508894668958[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 30 )[/C][C]61.5735294117647[/C][C]1.13703942609525[/C][C]54.152501662336[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 30 )[/C][C]61.515625[/C][C]1.11358676798503[/C][C]55.2409805580833[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 30 )[/C][C]61.4838709677419[/C][C]1.09291791031649[/C][C]56.2566231071619[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 30 )[/C][C]61.4333333333333[/C][C]1.07129117583759[/C][C]57.3451314814587[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 30 )[/C][C]61.3793103448276[/C][C]1.04462661211835[/C][C]58.7571766148668[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 30 )[/C][C]61.3035714285714[/C][C]1.01575883055738[/C][C]60.3524868151355[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 30 )[/C][C]61.2222222222222[/C][C]0.989697688232477[/C][C]61.8595182651789[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 30 )[/C][C]61.1923076923077[/C][C]0.973649221532114[/C][C]62.848412281393[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 30 )[/C][C]61.16[/C][C]0.962717242909837[/C][C]63.5285183166995[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 30 )[/C][C]61.125[/C][C]0.94794711002474[/C][C]64.4814455928926[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 30 )[/C][C]61.0869565217391[/C][C]0.92826058672455[/C][C]65.8079825809366[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 30 )[/C][C]61.0681818181818[/C][C]0.908846425899167[/C][C]67.193070333928[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 30 )[/C][C]61.0238095238095[/C][C]0.889014184244958[/C][C]68.6421101094548[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 30 )[/C][C]61.0238095238095[/C][C]0.861935433955289[/C][C]70.7985855086392[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 30 )[/C][C]60.8947368421053[/C][C]0.832133347794926[/C][C]73.1790607881183[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 30 )[/C][C]60.8333333333333[/C][C]0.801288644661518[/C][C]75.9193752945678[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 30 )[/C][C]60.735294117647[/C][C]0.766161373666188[/C][C]79.2721953953647[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 30 )[/C][C]60.65625[/C][C]0.729020242594747[/C][C]83.2024221770726[/C][/ROW]
[ROW][C]Median[/C][C]60.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]49[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]60.469387755102[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]60.469387755102[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]60.469387755102[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]60.469387755102[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]60.469387755102[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]60.469387755102[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]60.469387755102[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]61.1923076923077[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]92[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121734&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121734&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 Mean60.92391304347831.8524936832681932.8875145938396
Geometric Mean0
Harmonic Mean0
Quadratic Mean63.435091783375
Winsorized Mean ( 1 / 30 )61.17391304347831.7774943239246634.4158134403535
Winsorized Mean ( 2 / 30 )61.26086956521741.7579163357731134.8485694788629
Winsorized Mean ( 3 / 30 )61.13043478260871.6890514327008336.1921689293142
Winsorized Mean ( 4 / 30 )61.08695652173911.6807169321735436.3457732544766
Winsorized Mean ( 5 / 30 )61.1956521739131.6591577317982336.8835650770755
Winsorized Mean ( 6 / 30 )60.93478260869561.6119480686935537.8019514351242
Winsorized Mean ( 7 / 30 )61.01086956521741.5696517552870238.8690480928116
Winsorized Mean ( 8 / 30 )61.01086956521741.5389119583588539.645458100333
Winsorized Mean ( 9 / 30 )61.01086956521741.4717838733996841.4536880501945
Winsorized Mean ( 10 / 30 )60.79347826086961.4387924646056542.2531252813673
Winsorized Mean ( 11 / 30 )61.03260869565221.396317172148143.7097028619646
Winsorized Mean ( 12 / 30 )61.81521739130441.2710651551832448.6326111129943
Winsorized Mean ( 13 / 30 )61.81521739130441.2288273135836450.3042345397027
Winsorized Mean ( 14 / 30 )61.81521739130441.1844801202375552.1876360228885
Winsorized Mean ( 15 / 30 )61.97826086956521.1624991470150453.3146721257451
Winsorized Mean ( 16 / 30 )61.97826086956521.1624991470150453.3146721257451
Winsorized Mean ( 17 / 30 )62.16304347826091.1385480789675354.5985230018852
Winsorized Mean ( 18 / 30 )62.16304347826091.0843847980896957.3256316279708
Winsorized Mean ( 19 / 30 )61.54347826086960.9950202147584261.8514853749093
Winsorized Mean ( 20 / 30 )61.54347826086960.93817648546943665.5990415599417
Winsorized Mean ( 21 / 30 )61.54347826086960.93817648546943665.5990415599417
Winsorized Mean ( 22 / 30 )61.54347826086960.93817648546943665.5990415599417
Winsorized Mean ( 23 / 30 )61.29347826086960.90514509102389267.7167438333394
Winsorized Mean ( 24 / 30 )61.5543478260870.87314941571207270.4969238007083
Winsorized Mean ( 25 / 30 )61.5543478260870.87314941571207270.4969238007083
Winsorized Mean ( 26 / 30 )61.83695652173910.83980595981836873.6324335387107
Winsorized Mean ( 27 / 30 )61.54347826086960.80124918051635676.80941180022
Winsorized Mean ( 28 / 30 )61.84782608695650.76627660371377380.7121420479366
Winsorized Mean ( 29 / 30 )61.53260869565220.72535986866676784.8304563757448
Winsorized Mean ( 30 / 30 )61.53260869565220.72535986866676784.8304563757448
Trimmed Mean ( 1 / 30 )61.18888888888891.7178576243650535.6193016353759
Trimmed Mean ( 2 / 30 )61.20454545454551.6492421782489837.1107083372844
Trimmed Mean ( 3 / 30 )61.17441860465121.582236538967438.66325741951
Trimmed Mean ( 4 / 30 )61.19047619047621.5355302606699839.8497364446453
Trimmed Mean ( 5 / 30 )61.2195121951221.484439453426641.2408280134337
Trimmed Mean ( 6 / 30 )61.2251.4316688279456942.7647782817567
Trimmed Mean ( 7 / 30 )61.28205128205131.382890725451844.3144567782317
Trimmed Mean ( 8 / 30 )61.3289473684211.3363196589290545.8939198855842
Trimmed Mean ( 9 / 30 )61.37837837837841.2887033314359747.6280124999646
Trimmed Mean ( 10 / 30 )61.43055555555561.2471918988614549.2550950752926
Trimmed Mean ( 11 / 30 )61.51428571428571.2046739302898651.0630172759566
Trimmed Mean ( 12 / 30 )61.57352941176471.162842211560252.9508894668958
Trimmed Mean ( 13 / 30 )61.57352941176471.1370394260952554.152501662336
Trimmed Mean ( 14 / 30 )61.5156251.1135867679850355.2409805580833
Trimmed Mean ( 15 / 30 )61.48387096774191.0929179103164956.2566231071619
Trimmed Mean ( 16 / 30 )61.43333333333331.0712911758375957.3451314814587
Trimmed Mean ( 17 / 30 )61.37931034482761.0446266121183558.7571766148668
Trimmed Mean ( 18 / 30 )61.30357142857141.0157588305573860.3524868151355
Trimmed Mean ( 19 / 30 )61.22222222222220.98969768823247761.8595182651789
Trimmed Mean ( 20 / 30 )61.19230769230770.97364922153211462.848412281393
Trimmed Mean ( 21 / 30 )61.160.96271724290983763.5285183166995
Trimmed Mean ( 22 / 30 )61.1250.9479471100247464.4814455928926
Trimmed Mean ( 23 / 30 )61.08695652173910.9282605867245565.8079825809366
Trimmed Mean ( 24 / 30 )61.06818181818180.90884642589916767.193070333928
Trimmed Mean ( 25 / 30 )61.02380952380950.88901418424495868.6421101094548
Trimmed Mean ( 26 / 30 )61.02380952380950.86193543395528970.7985855086392
Trimmed Mean ( 27 / 30 )60.89473684210530.83213334779492673.1790607881183
Trimmed Mean ( 28 / 30 )60.83333333333330.80128864466151875.9193752945678
Trimmed Mean ( 29 / 30 )60.7352941176470.76616137366618879.2721953953647
Trimmed Mean ( 30 / 30 )60.656250.72902024259474783.2024221770726
Median60.5
Midrange49
Midmean - Weighted Average at Xnp60.469387755102
Midmean - Weighted Average at X(n+1)p60.469387755102
Midmean - Empirical Distribution Function60.469387755102
Midmean - Empirical Distribution Function - Averaging60.469387755102
Midmean - Empirical Distribution Function - Interpolation60.469387755102
Midmean - Closest Observation60.469387755102
Midmean - True Basic - Statistics Graphics Toolkit60.469387755102
Midmean - MS Excel (old versions)61.1923076923077
Number of observations92



Parameters (Session):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;
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')