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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 14 Nov 2011 14:01:15 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/14/t1321297447upscqcljgzubf42.htm/, Retrieved Fri, 29 Mar 2024 08:37:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=142268, Retrieved Fri, 29 Mar 2024 08:37:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact81
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [Arabica Price in ...] [2008-01-06 21:28:17] [74be16979710d4c4e7c6647856088456]
- RM D  [Central Tendency] [] [2011-11-11 17:47:10] [86f7284edee3dbb8ea5c7e2dec87d892]
-    D      [Central Tendency] [] [2011-11-14 19:01:15] [79818163420d1233b8d9d93d595e6c9e] [Current]
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Dataseries X:
9
14
14
15
16
16
16
21
22
22
25
29
31
34
35
37
38
39
40
40
43
45
47
47
48
48
49
50
51
55
57
58
63
64
65
67
68
68
70
70
70
71
71
71
73
79
80
82
82
83
84
85
86
86
87
88
88
89
89
90
90
93
93
93
93
95
96
96
97
98
98
98
99
99
99
100
100
100
100
100
100
100
100
100
100




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=142268&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=142268&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=142268&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'George Udny Yule' @ yule.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean67.25882352941183.1029105764020121.6760431450789
Geometric Mean58.6353058159671
Harmonic Mean47.062380119828
Quadratic Mean73.0240089446816
Winsorized Mean ( 1 / 28 )67.31764705882353.0902943649145121.7835711131958
Winsorized Mean ( 2 / 28 )67.31764705882353.0902943649145121.7835711131958
Winsorized Mean ( 3 / 28 )67.35294117647063.0831023101740921.845833968665
Winsorized Mean ( 4 / 28 )67.43.0736614904675521.9282442809756
Winsorized Mean ( 5 / 28 )67.43.0736614904675521.9282442809756
Winsorized Mean ( 6 / 28 )67.43.0736614904675521.9282442809756
Winsorized Mean ( 7 / 28 )67.81176470588242.9943220833498722.6467837521402
Winsorized Mean ( 8 / 28 )67.90588235294122.9769244901413422.8107506850861
Winsorized Mean ( 9 / 28 )67.90588235294122.9769244901413422.8107506850861
Winsorized Mean ( 10 / 28 )68.14117647058822.8982344157470923.511271586713
Winsorized Mean ( 11 / 28 )68.65882352941182.8088272691250624.443946512524
Winsorized Mean ( 12 / 28 )68.94117647058822.7620047595263324.9605567234473
Winsorized Mean ( 13 / 28 )69.24705882352942.6686742731193825.9481119599461
Winsorized Mean ( 14 / 28 )69.41176470588232.6429597892363426.2628909408941
Winsorized Mean ( 15 / 28 )69.76470588235292.5890118519269826.9464606082926
Winsorized Mean ( 16 / 28 )69.76470588235292.5365478127551927.503800847568
Winsorized Mean ( 17 / 28 )69.76470588235292.4815084787690528.1138293418041
Winsorized Mean ( 18 / 28 )69.97647058823532.4504602249149628.5564604871984
Winsorized Mean ( 19 / 28 )69.75294117647062.4224617593367728.7942383022664
Winsorized Mean ( 20 / 28 )69.98823529411762.2629950975788430.9272589096625
Winsorized Mean ( 21 / 28 )70.48235294117652.1937402518608932.1288506610516
Winsorized Mean ( 22 / 28 )712.1231022173249433.4416305633453
Winsorized Mean ( 23 / 28 )712.1231022173249433.4416305633453
Winsorized Mean ( 24 / 28 )70.4352941176471.9830123831472335.5193415413066
Winsorized Mean ( 25 / 28 )70.4352941176471.9830123831472335.5193415413066
Winsorized Mean ( 26 / 28 )70.4352941176471.9062367827579536.9499186852019
Winsorized Mean ( 27 / 28 )70.75294117647061.8639214920135937.959185233728
Winsorized Mean ( 28 / 28 )70.75294117647061.7821795960856239.7002307353717
Trimmed Mean ( 1 / 28 )67.5662650602413.0729782060213921.9872255936756
Trimmed Mean ( 2 / 28 )67.82716049382723.0516030053566122.2267314505744
Trimmed Mean ( 3 / 28 )68.10126582278483.0255106482172722.5090154162611
Trimmed Mean ( 4 / 28 )68.37662337662342.9969817900646522.8151614411872
Trimmed Mean ( 5 / 28 )68.65333333333332.9656589036389123.1494367909589
Trimmed Mean ( 6 / 28 )68.9452054794522.9277116644517823.5491788062955
Trimmed Mean ( 7 / 28 )69.25352112676062.8818950777882124.0305490857464
Trimmed Mean ( 8 / 28 )69.50724637681162.8458269644959824.4242700782483
Trimmed Mean ( 9 / 28 )69.76119402985072.8056357278317124.8646655507786
Trimmed Mean ( 10 / 28 )70.03076923076922.756458258377525.4060691896675
Trimmed Mean ( 11 / 28 )70.28571428571432.7123986217688525.9127525436798
Trimmed Mean ( 12 / 28 )70.49180327868852.6757995537435226.3442017471258
Trimmed Mean ( 13 / 28 )70.67796610169492.6389432423921126.782677613645
Trimmed Mean ( 14 / 28 )70.84210526315792.6096012084647527.1467169134379
Trimmed Mean ( 15 / 28 )712.5763754457979227.5580952752058
Trimmed Mean ( 16 / 28 )71.13207547169812.5433880435540427.967449030035
Trimmed Mean ( 17 / 28 )71.27450980392162.5096017075401228.4007257365887
Trimmed Mean ( 18 / 28 )71.42857142857142.4748737341529228.8615012729203
Trimmed Mean ( 19 / 28 )71.57446808510642.4344780407793929.4003342343528
Trimmed Mean ( 20 / 28 )71.75555555555562.3853838510233130.0813454089467
Trimmed Mean ( 21 / 28 )71.93023255813952.3515493699825530.5884424440866
Trimmed Mean ( 22 / 28 )72.07317073170732.3186387522198631.0842603931745
Trimmed Mean ( 23 / 28 )72.17948717948722.2867546188291731.5641593484321
Trimmed Mean ( 24 / 28 )72.29729729729732.2397128411714332.2797172781685
Trimmed Mean ( 25 / 28 )72.48571428571432.2032716042977832.8991278897804
Trimmed Mean ( 26 / 28 )72.69696969696972.1472696054510833.8555389190163
Trimmed Mean ( 27 / 28 )72.93548387096772.0842138271160834.994242395891
Trimmed Mean ( 28 / 28 )73.17241379310342.0018888651390236.5516862935456
Median71
Midrange54.5
Midmean - Weighted Average at Xnp72.4090909090909
Midmean - Weighted Average at X(n+1)p72.4090909090909
Midmean - Empirical Distribution Function72.4090909090909
Midmean - Empirical Distribution Function - Averaging72.4090909090909
Midmean - Empirical Distribution Function - Interpolation72.4090909090909
Midmean - Closest Observation71.7555555555556
Midmean - True Basic - Statistics Graphics Toolkit72.4090909090909
Midmean - MS Excel (old versions)72.4090909090909
Number of observations85

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 67.2588235294118 & 3.10291057640201 & 21.6760431450789 \tabularnewline
Geometric Mean & 58.6353058159671 &  &  \tabularnewline
Harmonic Mean & 47.062380119828 &  &  \tabularnewline
Quadratic Mean & 73.0240089446816 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 67.3176470588235 & 3.09029436491451 & 21.7835711131958 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 67.3176470588235 & 3.09029436491451 & 21.7835711131958 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 67.3529411764706 & 3.08310231017409 & 21.845833968665 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 67.4 & 3.07366149046755 & 21.9282442809756 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 67.4 & 3.07366149046755 & 21.9282442809756 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 67.4 & 3.07366149046755 & 21.9282442809756 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 67.8117647058824 & 2.99432208334987 & 22.6467837521402 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 67.9058823529412 & 2.97692449014134 & 22.8107506850861 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 67.9058823529412 & 2.97692449014134 & 22.8107506850861 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 68.1411764705882 & 2.89823441574709 & 23.511271586713 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 68.6588235294118 & 2.80882726912506 & 24.443946512524 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 68.9411764705882 & 2.76200475952633 & 24.9605567234473 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 69.2470588235294 & 2.66867427311938 & 25.9481119599461 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 69.4117647058823 & 2.64295978923634 & 26.2628909408941 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 69.7647058823529 & 2.58901185192698 & 26.9464606082926 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 69.7647058823529 & 2.53654781275519 & 27.503800847568 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 69.7647058823529 & 2.48150847876905 & 28.1138293418041 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 69.9764705882353 & 2.45046022491496 & 28.5564604871984 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 69.7529411764706 & 2.42246175933677 & 28.7942383022664 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 69.9882352941176 & 2.26299509757884 & 30.9272589096625 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 70.4823529411765 & 2.19374025186089 & 32.1288506610516 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 71 & 2.12310221732494 & 33.4416305633453 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 71 & 2.12310221732494 & 33.4416305633453 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 70.435294117647 & 1.98301238314723 & 35.5193415413066 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 70.435294117647 & 1.98301238314723 & 35.5193415413066 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 70.435294117647 & 1.90623678275795 & 36.9499186852019 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 70.7529411764706 & 1.86392149201359 & 37.959185233728 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 70.7529411764706 & 1.78217959608562 & 39.7002307353717 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 67.566265060241 & 3.07297820602139 & 21.9872255936756 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 67.8271604938272 & 3.05160300535661 & 22.2267314505744 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 68.1012658227848 & 3.02551064821727 & 22.5090154162611 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 68.3766233766234 & 2.99698179006465 & 22.8151614411872 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 68.6533333333333 & 2.96565890363891 & 23.1494367909589 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 68.945205479452 & 2.92771166445178 & 23.5491788062955 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 69.2535211267606 & 2.88189507778821 & 24.0305490857464 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 69.5072463768116 & 2.84582696449598 & 24.4242700782483 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 69.7611940298507 & 2.80563572783171 & 24.8646655507786 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 70.0307692307692 & 2.7564582583775 & 25.4060691896675 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 70.2857142857143 & 2.71239862176885 & 25.9127525436798 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 70.4918032786885 & 2.67579955374352 & 26.3442017471258 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 70.6779661016949 & 2.63894324239211 & 26.782677613645 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 70.8421052631579 & 2.60960120846475 & 27.1467169134379 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 71 & 2.57637544579792 & 27.5580952752058 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 71.1320754716981 & 2.54338804355404 & 27.967449030035 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 71.2745098039216 & 2.50960170754012 & 28.4007257365887 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 71.4285714285714 & 2.47487373415292 & 28.8615012729203 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 71.5744680851064 & 2.43447804077939 & 29.4003342343528 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 71.7555555555556 & 2.38538385102331 & 30.0813454089467 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 71.9302325581395 & 2.35154936998255 & 30.5884424440866 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 72.0731707317073 & 2.31863875221986 & 31.0842603931745 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 72.1794871794872 & 2.28675461882917 & 31.5641593484321 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 72.2972972972973 & 2.23971284117143 & 32.2797172781685 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 72.4857142857143 & 2.20327160429778 & 32.8991278897804 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 72.6969696969697 & 2.14726960545108 & 33.8555389190163 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 72.9354838709677 & 2.08421382711608 & 34.994242395891 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 73.1724137931034 & 2.00188886513902 & 36.5516862935456 \tabularnewline
Median & 71 &  &  \tabularnewline
Midrange & 54.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 72.4090909090909 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 72.4090909090909 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 72.4090909090909 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 72.4090909090909 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 72.4090909090909 &  &  \tabularnewline
Midmean - Closest Observation & 71.7555555555556 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 72.4090909090909 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 72.4090909090909 &  &  \tabularnewline
Number of observations & 85 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=142268&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]67.2588235294118[/C][C]3.10291057640201[/C][C]21.6760431450789[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]58.6353058159671[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]47.062380119828[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]73.0240089446816[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]67.3176470588235[/C][C]3.09029436491451[/C][C]21.7835711131958[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]67.3176470588235[/C][C]3.09029436491451[/C][C]21.7835711131958[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]67.3529411764706[/C][C]3.08310231017409[/C][C]21.845833968665[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]67.4[/C][C]3.07366149046755[/C][C]21.9282442809756[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]67.4[/C][C]3.07366149046755[/C][C]21.9282442809756[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]67.4[/C][C]3.07366149046755[/C][C]21.9282442809756[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]67.8117647058824[/C][C]2.99432208334987[/C][C]22.6467837521402[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]67.9058823529412[/C][C]2.97692449014134[/C][C]22.8107506850861[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]67.9058823529412[/C][C]2.97692449014134[/C][C]22.8107506850861[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]68.1411764705882[/C][C]2.89823441574709[/C][C]23.511271586713[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]68.6588235294118[/C][C]2.80882726912506[/C][C]24.443946512524[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]68.9411764705882[/C][C]2.76200475952633[/C][C]24.9605567234473[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]69.2470588235294[/C][C]2.66867427311938[/C][C]25.9481119599461[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]69.4117647058823[/C][C]2.64295978923634[/C][C]26.2628909408941[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]69.7647058823529[/C][C]2.58901185192698[/C][C]26.9464606082926[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]69.7647058823529[/C][C]2.53654781275519[/C][C]27.503800847568[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]69.7647058823529[/C][C]2.48150847876905[/C][C]28.1138293418041[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]69.9764705882353[/C][C]2.45046022491496[/C][C]28.5564604871984[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]69.7529411764706[/C][C]2.42246175933677[/C][C]28.7942383022664[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]69.9882352941176[/C][C]2.26299509757884[/C][C]30.9272589096625[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]70.4823529411765[/C][C]2.19374025186089[/C][C]32.1288506610516[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]71[/C][C]2.12310221732494[/C][C]33.4416305633453[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]71[/C][C]2.12310221732494[/C][C]33.4416305633453[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]70.435294117647[/C][C]1.98301238314723[/C][C]35.5193415413066[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]70.435294117647[/C][C]1.98301238314723[/C][C]35.5193415413066[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]70.435294117647[/C][C]1.90623678275795[/C][C]36.9499186852019[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]70.7529411764706[/C][C]1.86392149201359[/C][C]37.959185233728[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]70.7529411764706[/C][C]1.78217959608562[/C][C]39.7002307353717[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]67.566265060241[/C][C]3.07297820602139[/C][C]21.9872255936756[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]67.8271604938272[/C][C]3.05160300535661[/C][C]22.2267314505744[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]68.1012658227848[/C][C]3.02551064821727[/C][C]22.5090154162611[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]68.3766233766234[/C][C]2.99698179006465[/C][C]22.8151614411872[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]68.6533333333333[/C][C]2.96565890363891[/C][C]23.1494367909589[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]68.945205479452[/C][C]2.92771166445178[/C][C]23.5491788062955[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]69.2535211267606[/C][C]2.88189507778821[/C][C]24.0305490857464[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]69.5072463768116[/C][C]2.84582696449598[/C][C]24.4242700782483[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]69.7611940298507[/C][C]2.80563572783171[/C][C]24.8646655507786[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]70.0307692307692[/C][C]2.7564582583775[/C][C]25.4060691896675[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]70.2857142857143[/C][C]2.71239862176885[/C][C]25.9127525436798[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]70.4918032786885[/C][C]2.67579955374352[/C][C]26.3442017471258[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]70.6779661016949[/C][C]2.63894324239211[/C][C]26.782677613645[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]70.8421052631579[/C][C]2.60960120846475[/C][C]27.1467169134379[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]71[/C][C]2.57637544579792[/C][C]27.5580952752058[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]71.1320754716981[/C][C]2.54338804355404[/C][C]27.967449030035[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]71.2745098039216[/C][C]2.50960170754012[/C][C]28.4007257365887[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]71.4285714285714[/C][C]2.47487373415292[/C][C]28.8615012729203[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]71.5744680851064[/C][C]2.43447804077939[/C][C]29.4003342343528[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]71.7555555555556[/C][C]2.38538385102331[/C][C]30.0813454089467[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]71.9302325581395[/C][C]2.35154936998255[/C][C]30.5884424440866[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]72.0731707317073[/C][C]2.31863875221986[/C][C]31.0842603931745[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]72.1794871794872[/C][C]2.28675461882917[/C][C]31.5641593484321[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]72.2972972972973[/C][C]2.23971284117143[/C][C]32.2797172781685[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]72.4857142857143[/C][C]2.20327160429778[/C][C]32.8991278897804[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]72.6969696969697[/C][C]2.14726960545108[/C][C]33.8555389190163[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]72.9354838709677[/C][C]2.08421382711608[/C][C]34.994242395891[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]73.1724137931034[/C][C]2.00188886513902[/C][C]36.5516862935456[/C][/ROW]
[ROW][C]Median[/C][C]71[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]54.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]72.4090909090909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]72.4090909090909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]72.4090909090909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]72.4090909090909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]72.4090909090909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]71.7555555555556[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]72.4090909090909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]72.4090909090909[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]85[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=142268&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=142268&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 Mean67.25882352941183.1029105764020121.6760431450789
Geometric Mean58.6353058159671
Harmonic Mean47.062380119828
Quadratic Mean73.0240089446816
Winsorized Mean ( 1 / 28 )67.31764705882353.0902943649145121.7835711131958
Winsorized Mean ( 2 / 28 )67.31764705882353.0902943649145121.7835711131958
Winsorized Mean ( 3 / 28 )67.35294117647063.0831023101740921.845833968665
Winsorized Mean ( 4 / 28 )67.43.0736614904675521.9282442809756
Winsorized Mean ( 5 / 28 )67.43.0736614904675521.9282442809756
Winsorized Mean ( 6 / 28 )67.43.0736614904675521.9282442809756
Winsorized Mean ( 7 / 28 )67.81176470588242.9943220833498722.6467837521402
Winsorized Mean ( 8 / 28 )67.90588235294122.9769244901413422.8107506850861
Winsorized Mean ( 9 / 28 )67.90588235294122.9769244901413422.8107506850861
Winsorized Mean ( 10 / 28 )68.14117647058822.8982344157470923.511271586713
Winsorized Mean ( 11 / 28 )68.65882352941182.8088272691250624.443946512524
Winsorized Mean ( 12 / 28 )68.94117647058822.7620047595263324.9605567234473
Winsorized Mean ( 13 / 28 )69.24705882352942.6686742731193825.9481119599461
Winsorized Mean ( 14 / 28 )69.41176470588232.6429597892363426.2628909408941
Winsorized Mean ( 15 / 28 )69.76470588235292.5890118519269826.9464606082926
Winsorized Mean ( 16 / 28 )69.76470588235292.5365478127551927.503800847568
Winsorized Mean ( 17 / 28 )69.76470588235292.4815084787690528.1138293418041
Winsorized Mean ( 18 / 28 )69.97647058823532.4504602249149628.5564604871984
Winsorized Mean ( 19 / 28 )69.75294117647062.4224617593367728.7942383022664
Winsorized Mean ( 20 / 28 )69.98823529411762.2629950975788430.9272589096625
Winsorized Mean ( 21 / 28 )70.48235294117652.1937402518608932.1288506610516
Winsorized Mean ( 22 / 28 )712.1231022173249433.4416305633453
Winsorized Mean ( 23 / 28 )712.1231022173249433.4416305633453
Winsorized Mean ( 24 / 28 )70.4352941176471.9830123831472335.5193415413066
Winsorized Mean ( 25 / 28 )70.4352941176471.9830123831472335.5193415413066
Winsorized Mean ( 26 / 28 )70.4352941176471.9062367827579536.9499186852019
Winsorized Mean ( 27 / 28 )70.75294117647061.8639214920135937.959185233728
Winsorized Mean ( 28 / 28 )70.75294117647061.7821795960856239.7002307353717
Trimmed Mean ( 1 / 28 )67.5662650602413.0729782060213921.9872255936756
Trimmed Mean ( 2 / 28 )67.82716049382723.0516030053566122.2267314505744
Trimmed Mean ( 3 / 28 )68.10126582278483.0255106482172722.5090154162611
Trimmed Mean ( 4 / 28 )68.37662337662342.9969817900646522.8151614411872
Trimmed Mean ( 5 / 28 )68.65333333333332.9656589036389123.1494367909589
Trimmed Mean ( 6 / 28 )68.9452054794522.9277116644517823.5491788062955
Trimmed Mean ( 7 / 28 )69.25352112676062.8818950777882124.0305490857464
Trimmed Mean ( 8 / 28 )69.50724637681162.8458269644959824.4242700782483
Trimmed Mean ( 9 / 28 )69.76119402985072.8056357278317124.8646655507786
Trimmed Mean ( 10 / 28 )70.03076923076922.756458258377525.4060691896675
Trimmed Mean ( 11 / 28 )70.28571428571432.7123986217688525.9127525436798
Trimmed Mean ( 12 / 28 )70.49180327868852.6757995537435226.3442017471258
Trimmed Mean ( 13 / 28 )70.67796610169492.6389432423921126.782677613645
Trimmed Mean ( 14 / 28 )70.84210526315792.6096012084647527.1467169134379
Trimmed Mean ( 15 / 28 )712.5763754457979227.5580952752058
Trimmed Mean ( 16 / 28 )71.13207547169812.5433880435540427.967449030035
Trimmed Mean ( 17 / 28 )71.27450980392162.5096017075401228.4007257365887
Trimmed Mean ( 18 / 28 )71.42857142857142.4748737341529228.8615012729203
Trimmed Mean ( 19 / 28 )71.57446808510642.4344780407793929.4003342343528
Trimmed Mean ( 20 / 28 )71.75555555555562.3853838510233130.0813454089467
Trimmed Mean ( 21 / 28 )71.93023255813952.3515493699825530.5884424440866
Trimmed Mean ( 22 / 28 )72.07317073170732.3186387522198631.0842603931745
Trimmed Mean ( 23 / 28 )72.17948717948722.2867546188291731.5641593484321
Trimmed Mean ( 24 / 28 )72.29729729729732.2397128411714332.2797172781685
Trimmed Mean ( 25 / 28 )72.48571428571432.2032716042977832.8991278897804
Trimmed Mean ( 26 / 28 )72.69696969696972.1472696054510833.8555389190163
Trimmed Mean ( 27 / 28 )72.93548387096772.0842138271160834.994242395891
Trimmed Mean ( 28 / 28 )73.17241379310342.0018888651390236.5516862935456
Median71
Midrange54.5
Midmean - Weighted Average at Xnp72.4090909090909
Midmean - Weighted Average at X(n+1)p72.4090909090909
Midmean - Empirical Distribution Function72.4090909090909
Midmean - Empirical Distribution Function - Averaging72.4090909090909
Midmean - Empirical Distribution Function - Interpolation72.4090909090909
Midmean - Closest Observation71.7555555555556
Midmean - True Basic - Statistics Graphics Toolkit72.4090909090909
Midmean - MS Excel (old versions)72.4090909090909
Number of observations85



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')