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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 computationWed, 17 Dec 2014 14:18:12 +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/2014/Dec/17/t14188262362fltppjxexgcjlq.htm/, Retrieved Thu, 16 May 2024 11:45:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270315, Retrieved Thu, 16 May 2024 11:45:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact64
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [LFM M Central Ten...] [2014-12-17 14:18:12] [ca907db95fc0b179b22bb0898c34dff4] [Current]
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Dataseries X:
68
131
71
68
89
87
49
96
100
141
110
146
147
61
60
109
68
73
65
52
62
101
42
96
57
86
88
85
102
86
114
94
64
105
49
95
102
63
117
57
73
105
31
48
50
150
154
194
159
39
100
111
138
101
101
114
114
111
75
82
121
32
117
165
154
126
120
172
114
156
167
2
165
165
118
155
220
122
44
152
103
175
110
131
121
168
94
51
145
66
128
119
132
142
166




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270315&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270315&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270315&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean104.6736842105264.2850933604253924.4273987533693
Geometric Mean93.4676347603166
Harmonic Mean60.7337882235039
Quadratic Mean112.617096953863
Winsorized Mean ( 1 / 31 )104.7052631578954.146501748339625.2514696755699
Winsorized Mean ( 2 / 31 )104.3263157894744.0595633044581625.6989010800506
Winsorized Mean ( 3 / 31 )104.4526315789474.0020926334911726.0995037208396
Winsorized Mean ( 4 / 31 )104.4105263157893.9509448523886526.4267232818158
Winsorized Mean ( 5 / 31 )104.4631578947373.9245062463971526.618165785986
Winsorized Mean ( 6 / 31 )104.6526315789473.8734681521127427.017811291895
Winsorized Mean ( 7 / 31 )104.6526315789473.8497180252189927.184492706578
Winsorized Mean ( 8 / 31 )104.6526315789473.8497180252189927.184492706578
Winsorized Mean ( 9 / 31 )104.7473684210533.8352396895317527.3118180089134
Winsorized Mean ( 10 / 31 )104.2210526315793.7168897805918328.0398555738137
Winsorized Mean ( 11 / 31 )103.9894736842113.6456878986841328.523964907074
Winsorized Mean ( 12 / 31 )104.4947368421053.5333913070310529.573496893529
Winsorized Mean ( 13 / 31 )104.3578947368423.5127002272867329.7087391420958
Winsorized Mean ( 14 / 31 )104.83.4504523617288130.3728291288425
Winsorized Mean ( 15 / 31 )104.6421052631583.3812246166229230.9479898935764
Winsorized Mean ( 16 / 31 )104.4736842105263.3084046525423331.5782666217217
Winsorized Mean ( 17 / 31 )104.1157894736843.2064766190632132.4704658236685
Winsorized Mean ( 18 / 31 )104.1157894736843.1538690278756433.0120840635585
Winsorized Mean ( 19 / 31 )104.1157894736843.0987431313242833.5993611155466
Winsorized Mean ( 20 / 31 )103.6947368421052.9829704670368434.7622405209768
Winsorized Mean ( 21 / 31 )103.9157894736842.8938929850136235.9086497019154
Winsorized Mean ( 22 / 31 )103.2210526315792.8006229888991436.8564612376308
Winsorized Mean ( 23 / 31 )101.7684210526322.615118959803938.9154079094982
Winsorized Mean ( 24 / 31 )102.2736842105262.4811243570379441.2207005748895
Winsorized Mean ( 25 / 31 )102.82.4112279354666842.6338789825374
Winsorized Mean ( 26 / 31 )101.9789473684212.3109350525014444.1288677749881
Winsorized Mean ( 27 / 31 )101.9789473684212.167818113807247.0422065019662
Winsorized Mean ( 28 / 31 )102.8631578947371.7629768756000558.3462887791572
Winsorized Mean ( 29 / 31 )103.4736842105261.614245243309164.1003494601674
Winsorized Mean ( 30 / 31 )103.7894736842111.5760593221623165.8537862279285
Winsorized Mean ( 31 / 31 )103.4631578947371.5384443012848567.2518061319011
Trimmed Mean ( 1 / 31 )104.5376344086024.0469590202740725.8311571441419
Trimmed Mean ( 2 / 31 )104.3626373626373.9334362836069626.5321794578396
Trimmed Mean ( 3 / 31 )104.382022471913.8566137036177227.0657189165703
Trimmed Mean ( 4 / 31 )104.356321839083.7929920682212727.5129290971648
Trimmed Mean ( 5 / 31 )104.3411764705883.7368463216597627.9222551555837
Trimmed Mean ( 6 / 31 )104.3132530120483.6793267995873228.3511790862797
Trimmed Mean ( 7 / 31 )104.3132530120483.6251662739302328.7747499369061
Trimmed Mean ( 8 / 31 )104.1772151898733.5673043513973529.2033437374263
Trimmed Mean ( 9 / 31 )104.1038961038963.4996135132566129.7472551496182
Trimmed Mean ( 10 / 31 )104.0133333333333.4231587190218930.3851915353353
Trimmed Mean ( 11 / 31 )103.9863013698633.3561146829482530.984132305787
Trimmed Mean ( 12 / 31 )103.9859154929583.2899146514127231.6074811996431
Trimmed Mean ( 13 / 31 )103.9275362318843.2310381224810332.1653698570666
Trimmed Mean ( 14 / 31 )103.9275362318843.1641737709349832.8450786067842
Trimmed Mean ( 15 / 31 )103.7846153846153.0944656171334833.5387844705655
Trimmed Mean ( 16 / 31 )103.6984126984133.0223298440006534.3107529789493
Trimmed Mean ( 17 / 31 )103.6229508196722.9474601397886235.1566928491537
Trimmed Mean ( 18 / 31 )103.5762711864412.873954808598236.0396311300946
Trimmed Mean ( 19 / 31 )103.5263157894742.7928822509448537.0679128181827
Trimmed Mean ( 20 / 31 )103.4727272727272.7026429944016438.2857549025398
Trimmed Mean ( 21 / 31 )103.4528301886792.6121528578518639.6044319832627
Trimmed Mean ( 22 / 31 )103.4117647058822.5157038496780441.1064938025663
Trimmed Mean ( 23 / 31 )103.4285714285712.4124112193314942.8735244637242
Trimmed Mean ( 24 / 31 )103.5744680851062.3178798010887444.6850039576928
Trimmed Mean ( 25 / 31 )103.6888888888892.224932690440846.6031576300612
Trimmed Mean ( 26 / 31 )103.7674418604652.1195804995904248.9565939489048
Trimmed Mean ( 27 / 31 )103.9268292682932.0028608331469751.8891914746761
Trimmed Mean ( 28 / 31 )103.9268292682931.8827990733480755.1980456860357
Trimmed Mean ( 29 / 31 )104.2162162162161.8266196215809857.0541425181969
Trimmed Mean ( 30 / 31 )104.2857142857141.7853613096520358.4115460114009
Trimmed Mean ( 31 / 31 )104.3333333333331.7351461965011360.1294193790233
Median103
Midrange111
Midmean - Weighted Average at Xnp101.44
Midmean - Weighted Average at X(n+1)p102.039215686275
Midmean - Empirical Distribution Function102.039215686275
Midmean - Empirical Distribution Function - Averaging102.039215686275
Midmean - Empirical Distribution Function - Interpolation103.574468085106
Midmean - Closest Observation101.44
Midmean - True Basic - Statistics Graphics Toolkit102.039215686275
Midmean - MS Excel (old versions)102.039215686275
Number of observations95

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 104.673684210526 & 4.28509336042539 & 24.4273987533693 \tabularnewline
Geometric Mean & 93.4676347603166 &  &  \tabularnewline
Harmonic Mean & 60.7337882235039 &  &  \tabularnewline
Quadratic Mean & 112.617096953863 &  &  \tabularnewline
Winsorized Mean ( 1 / 31 ) & 104.705263157895 & 4.1465017483396 & 25.2514696755699 \tabularnewline
Winsorized Mean ( 2 / 31 ) & 104.326315789474 & 4.05956330445816 & 25.6989010800506 \tabularnewline
Winsorized Mean ( 3 / 31 ) & 104.452631578947 & 4.00209263349117 & 26.0995037208396 \tabularnewline
Winsorized Mean ( 4 / 31 ) & 104.410526315789 & 3.95094485238865 & 26.4267232818158 \tabularnewline
Winsorized Mean ( 5 / 31 ) & 104.463157894737 & 3.92450624639715 & 26.618165785986 \tabularnewline
Winsorized Mean ( 6 / 31 ) & 104.652631578947 & 3.87346815211274 & 27.017811291895 \tabularnewline
Winsorized Mean ( 7 / 31 ) & 104.652631578947 & 3.84971802521899 & 27.184492706578 \tabularnewline
Winsorized Mean ( 8 / 31 ) & 104.652631578947 & 3.84971802521899 & 27.184492706578 \tabularnewline
Winsorized Mean ( 9 / 31 ) & 104.747368421053 & 3.83523968953175 & 27.3118180089134 \tabularnewline
Winsorized Mean ( 10 / 31 ) & 104.221052631579 & 3.71688978059183 & 28.0398555738137 \tabularnewline
Winsorized Mean ( 11 / 31 ) & 103.989473684211 & 3.64568789868413 & 28.523964907074 \tabularnewline
Winsorized Mean ( 12 / 31 ) & 104.494736842105 & 3.53339130703105 & 29.573496893529 \tabularnewline
Winsorized Mean ( 13 / 31 ) & 104.357894736842 & 3.51270022728673 & 29.7087391420958 \tabularnewline
Winsorized Mean ( 14 / 31 ) & 104.8 & 3.45045236172881 & 30.3728291288425 \tabularnewline
Winsorized Mean ( 15 / 31 ) & 104.642105263158 & 3.38122461662292 & 30.9479898935764 \tabularnewline
Winsorized Mean ( 16 / 31 ) & 104.473684210526 & 3.30840465254233 & 31.5782666217217 \tabularnewline
Winsorized Mean ( 17 / 31 ) & 104.115789473684 & 3.20647661906321 & 32.4704658236685 \tabularnewline
Winsorized Mean ( 18 / 31 ) & 104.115789473684 & 3.15386902787564 & 33.0120840635585 \tabularnewline
Winsorized Mean ( 19 / 31 ) & 104.115789473684 & 3.09874313132428 & 33.5993611155466 \tabularnewline
Winsorized Mean ( 20 / 31 ) & 103.694736842105 & 2.98297046703684 & 34.7622405209768 \tabularnewline
Winsorized Mean ( 21 / 31 ) & 103.915789473684 & 2.89389298501362 & 35.9086497019154 \tabularnewline
Winsorized Mean ( 22 / 31 ) & 103.221052631579 & 2.80062298889914 & 36.8564612376308 \tabularnewline
Winsorized Mean ( 23 / 31 ) & 101.768421052632 & 2.6151189598039 & 38.9154079094982 \tabularnewline
Winsorized Mean ( 24 / 31 ) & 102.273684210526 & 2.48112435703794 & 41.2207005748895 \tabularnewline
Winsorized Mean ( 25 / 31 ) & 102.8 & 2.41122793546668 & 42.6338789825374 \tabularnewline
Winsorized Mean ( 26 / 31 ) & 101.978947368421 & 2.31093505250144 & 44.1288677749881 \tabularnewline
Winsorized Mean ( 27 / 31 ) & 101.978947368421 & 2.1678181138072 & 47.0422065019662 \tabularnewline
Winsorized Mean ( 28 / 31 ) & 102.863157894737 & 1.76297687560005 & 58.3462887791572 \tabularnewline
Winsorized Mean ( 29 / 31 ) & 103.473684210526 & 1.6142452433091 & 64.1003494601674 \tabularnewline
Winsorized Mean ( 30 / 31 ) & 103.789473684211 & 1.57605932216231 & 65.8537862279285 \tabularnewline
Winsorized Mean ( 31 / 31 ) & 103.463157894737 & 1.53844430128485 & 67.2518061319011 \tabularnewline
Trimmed Mean ( 1 / 31 ) & 104.537634408602 & 4.04695902027407 & 25.8311571441419 \tabularnewline
Trimmed Mean ( 2 / 31 ) & 104.362637362637 & 3.93343628360696 & 26.5321794578396 \tabularnewline
Trimmed Mean ( 3 / 31 ) & 104.38202247191 & 3.85661370361772 & 27.0657189165703 \tabularnewline
Trimmed Mean ( 4 / 31 ) & 104.35632183908 & 3.79299206822127 & 27.5129290971648 \tabularnewline
Trimmed Mean ( 5 / 31 ) & 104.341176470588 & 3.73684632165976 & 27.9222551555837 \tabularnewline
Trimmed Mean ( 6 / 31 ) & 104.313253012048 & 3.67932679958732 & 28.3511790862797 \tabularnewline
Trimmed Mean ( 7 / 31 ) & 104.313253012048 & 3.62516627393023 & 28.7747499369061 \tabularnewline
Trimmed Mean ( 8 / 31 ) & 104.177215189873 & 3.56730435139735 & 29.2033437374263 \tabularnewline
Trimmed Mean ( 9 / 31 ) & 104.103896103896 & 3.49961351325661 & 29.7472551496182 \tabularnewline
Trimmed Mean ( 10 / 31 ) & 104.013333333333 & 3.42315871902189 & 30.3851915353353 \tabularnewline
Trimmed Mean ( 11 / 31 ) & 103.986301369863 & 3.35611468294825 & 30.984132305787 \tabularnewline
Trimmed Mean ( 12 / 31 ) & 103.985915492958 & 3.28991465141272 & 31.6074811996431 \tabularnewline
Trimmed Mean ( 13 / 31 ) & 103.927536231884 & 3.23103812248103 & 32.1653698570666 \tabularnewline
Trimmed Mean ( 14 / 31 ) & 103.927536231884 & 3.16417377093498 & 32.8450786067842 \tabularnewline
Trimmed Mean ( 15 / 31 ) & 103.784615384615 & 3.09446561713348 & 33.5387844705655 \tabularnewline
Trimmed Mean ( 16 / 31 ) & 103.698412698413 & 3.02232984400065 & 34.3107529789493 \tabularnewline
Trimmed Mean ( 17 / 31 ) & 103.622950819672 & 2.94746013978862 & 35.1566928491537 \tabularnewline
Trimmed Mean ( 18 / 31 ) & 103.576271186441 & 2.8739548085982 & 36.0396311300946 \tabularnewline
Trimmed Mean ( 19 / 31 ) & 103.526315789474 & 2.79288225094485 & 37.0679128181827 \tabularnewline
Trimmed Mean ( 20 / 31 ) & 103.472727272727 & 2.70264299440164 & 38.2857549025398 \tabularnewline
Trimmed Mean ( 21 / 31 ) & 103.452830188679 & 2.61215285785186 & 39.6044319832627 \tabularnewline
Trimmed Mean ( 22 / 31 ) & 103.411764705882 & 2.51570384967804 & 41.1064938025663 \tabularnewline
Trimmed Mean ( 23 / 31 ) & 103.428571428571 & 2.41241121933149 & 42.8735244637242 \tabularnewline
Trimmed Mean ( 24 / 31 ) & 103.574468085106 & 2.31787980108874 & 44.6850039576928 \tabularnewline
Trimmed Mean ( 25 / 31 ) & 103.688888888889 & 2.2249326904408 & 46.6031576300612 \tabularnewline
Trimmed Mean ( 26 / 31 ) & 103.767441860465 & 2.11958049959042 & 48.9565939489048 \tabularnewline
Trimmed Mean ( 27 / 31 ) & 103.926829268293 & 2.00286083314697 & 51.8891914746761 \tabularnewline
Trimmed Mean ( 28 / 31 ) & 103.926829268293 & 1.88279907334807 & 55.1980456860357 \tabularnewline
Trimmed Mean ( 29 / 31 ) & 104.216216216216 & 1.82661962158098 & 57.0541425181969 \tabularnewline
Trimmed Mean ( 30 / 31 ) & 104.285714285714 & 1.78536130965203 & 58.4115460114009 \tabularnewline
Trimmed Mean ( 31 / 31 ) & 104.333333333333 & 1.73514619650113 & 60.1294193790233 \tabularnewline
Median & 103 &  &  \tabularnewline
Midrange & 111 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 101.44 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 102.039215686275 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 102.039215686275 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 102.039215686275 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 103.574468085106 &  &  \tabularnewline
Midmean - Closest Observation & 101.44 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 102.039215686275 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 102.039215686275 &  &  \tabularnewline
Number of observations & 95 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270315&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]104.673684210526[/C][C]4.28509336042539[/C][C]24.4273987533693[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]93.4676347603166[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]60.7337882235039[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]112.617096953863[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 31 )[/C][C]104.705263157895[/C][C]4.1465017483396[/C][C]25.2514696755699[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 31 )[/C][C]104.326315789474[/C][C]4.05956330445816[/C][C]25.6989010800506[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 31 )[/C][C]104.452631578947[/C][C]4.00209263349117[/C][C]26.0995037208396[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 31 )[/C][C]104.410526315789[/C][C]3.95094485238865[/C][C]26.4267232818158[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 31 )[/C][C]104.463157894737[/C][C]3.92450624639715[/C][C]26.618165785986[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 31 )[/C][C]104.652631578947[/C][C]3.87346815211274[/C][C]27.017811291895[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 31 )[/C][C]104.652631578947[/C][C]3.84971802521899[/C][C]27.184492706578[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 31 )[/C][C]104.652631578947[/C][C]3.84971802521899[/C][C]27.184492706578[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 31 )[/C][C]104.747368421053[/C][C]3.83523968953175[/C][C]27.3118180089134[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 31 )[/C][C]104.221052631579[/C][C]3.71688978059183[/C][C]28.0398555738137[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 31 )[/C][C]103.989473684211[/C][C]3.64568789868413[/C][C]28.523964907074[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 31 )[/C][C]104.494736842105[/C][C]3.53339130703105[/C][C]29.573496893529[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 31 )[/C][C]104.357894736842[/C][C]3.51270022728673[/C][C]29.7087391420958[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 31 )[/C][C]104.8[/C][C]3.45045236172881[/C][C]30.3728291288425[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 31 )[/C][C]104.642105263158[/C][C]3.38122461662292[/C][C]30.9479898935764[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 31 )[/C][C]104.473684210526[/C][C]3.30840465254233[/C][C]31.5782666217217[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 31 )[/C][C]104.115789473684[/C][C]3.20647661906321[/C][C]32.4704658236685[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 31 )[/C][C]104.115789473684[/C][C]3.15386902787564[/C][C]33.0120840635585[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 31 )[/C][C]104.115789473684[/C][C]3.09874313132428[/C][C]33.5993611155466[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 31 )[/C][C]103.694736842105[/C][C]2.98297046703684[/C][C]34.7622405209768[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 31 )[/C][C]103.915789473684[/C][C]2.89389298501362[/C][C]35.9086497019154[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 31 )[/C][C]103.221052631579[/C][C]2.80062298889914[/C][C]36.8564612376308[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 31 )[/C][C]101.768421052632[/C][C]2.6151189598039[/C][C]38.9154079094982[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 31 )[/C][C]102.273684210526[/C][C]2.48112435703794[/C][C]41.2207005748895[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 31 )[/C][C]102.8[/C][C]2.41122793546668[/C][C]42.6338789825374[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 31 )[/C][C]101.978947368421[/C][C]2.31093505250144[/C][C]44.1288677749881[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 31 )[/C][C]101.978947368421[/C][C]2.1678181138072[/C][C]47.0422065019662[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 31 )[/C][C]102.863157894737[/C][C]1.76297687560005[/C][C]58.3462887791572[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 31 )[/C][C]103.473684210526[/C][C]1.6142452433091[/C][C]64.1003494601674[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 31 )[/C][C]103.789473684211[/C][C]1.57605932216231[/C][C]65.8537862279285[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 31 )[/C][C]103.463157894737[/C][C]1.53844430128485[/C][C]67.2518061319011[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 31 )[/C][C]104.537634408602[/C][C]4.04695902027407[/C][C]25.8311571441419[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 31 )[/C][C]104.362637362637[/C][C]3.93343628360696[/C][C]26.5321794578396[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 31 )[/C][C]104.38202247191[/C][C]3.85661370361772[/C][C]27.0657189165703[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 31 )[/C][C]104.35632183908[/C][C]3.79299206822127[/C][C]27.5129290971648[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 31 )[/C][C]104.341176470588[/C][C]3.73684632165976[/C][C]27.9222551555837[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 31 )[/C][C]104.313253012048[/C][C]3.67932679958732[/C][C]28.3511790862797[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 31 )[/C][C]104.313253012048[/C][C]3.62516627393023[/C][C]28.7747499369061[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 31 )[/C][C]104.177215189873[/C][C]3.56730435139735[/C][C]29.2033437374263[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 31 )[/C][C]104.103896103896[/C][C]3.49961351325661[/C][C]29.7472551496182[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 31 )[/C][C]104.013333333333[/C][C]3.42315871902189[/C][C]30.3851915353353[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 31 )[/C][C]103.986301369863[/C][C]3.35611468294825[/C][C]30.984132305787[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 31 )[/C][C]103.985915492958[/C][C]3.28991465141272[/C][C]31.6074811996431[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 31 )[/C][C]103.927536231884[/C][C]3.23103812248103[/C][C]32.1653698570666[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 31 )[/C][C]103.927536231884[/C][C]3.16417377093498[/C][C]32.8450786067842[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 31 )[/C][C]103.784615384615[/C][C]3.09446561713348[/C][C]33.5387844705655[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 31 )[/C][C]103.698412698413[/C][C]3.02232984400065[/C][C]34.3107529789493[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 31 )[/C][C]103.622950819672[/C][C]2.94746013978862[/C][C]35.1566928491537[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 31 )[/C][C]103.576271186441[/C][C]2.8739548085982[/C][C]36.0396311300946[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 31 )[/C][C]103.526315789474[/C][C]2.79288225094485[/C][C]37.0679128181827[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 31 )[/C][C]103.472727272727[/C][C]2.70264299440164[/C][C]38.2857549025398[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 31 )[/C][C]103.452830188679[/C][C]2.61215285785186[/C][C]39.6044319832627[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 31 )[/C][C]103.411764705882[/C][C]2.51570384967804[/C][C]41.1064938025663[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 31 )[/C][C]103.428571428571[/C][C]2.41241121933149[/C][C]42.8735244637242[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 31 )[/C][C]103.574468085106[/C][C]2.31787980108874[/C][C]44.6850039576928[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 31 )[/C][C]103.688888888889[/C][C]2.2249326904408[/C][C]46.6031576300612[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 31 )[/C][C]103.767441860465[/C][C]2.11958049959042[/C][C]48.9565939489048[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 31 )[/C][C]103.926829268293[/C][C]2.00286083314697[/C][C]51.8891914746761[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 31 )[/C][C]103.926829268293[/C][C]1.88279907334807[/C][C]55.1980456860357[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 31 )[/C][C]104.216216216216[/C][C]1.82661962158098[/C][C]57.0541425181969[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 31 )[/C][C]104.285714285714[/C][C]1.78536130965203[/C][C]58.4115460114009[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 31 )[/C][C]104.333333333333[/C][C]1.73514619650113[/C][C]60.1294193790233[/C][/ROW]
[ROW][C]Median[/C][C]103[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]111[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]101.44[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]102.039215686275[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]102.039215686275[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]102.039215686275[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]103.574468085106[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]101.44[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]102.039215686275[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]102.039215686275[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]95[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270315&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270315&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 Mean104.6736842105264.2850933604253924.4273987533693
Geometric Mean93.4676347603166
Harmonic Mean60.7337882235039
Quadratic Mean112.617096953863
Winsorized Mean ( 1 / 31 )104.7052631578954.146501748339625.2514696755699
Winsorized Mean ( 2 / 31 )104.3263157894744.0595633044581625.6989010800506
Winsorized Mean ( 3 / 31 )104.4526315789474.0020926334911726.0995037208396
Winsorized Mean ( 4 / 31 )104.4105263157893.9509448523886526.4267232818158
Winsorized Mean ( 5 / 31 )104.4631578947373.9245062463971526.618165785986
Winsorized Mean ( 6 / 31 )104.6526315789473.8734681521127427.017811291895
Winsorized Mean ( 7 / 31 )104.6526315789473.8497180252189927.184492706578
Winsorized Mean ( 8 / 31 )104.6526315789473.8497180252189927.184492706578
Winsorized Mean ( 9 / 31 )104.7473684210533.8352396895317527.3118180089134
Winsorized Mean ( 10 / 31 )104.2210526315793.7168897805918328.0398555738137
Winsorized Mean ( 11 / 31 )103.9894736842113.6456878986841328.523964907074
Winsorized Mean ( 12 / 31 )104.4947368421053.5333913070310529.573496893529
Winsorized Mean ( 13 / 31 )104.3578947368423.5127002272867329.7087391420958
Winsorized Mean ( 14 / 31 )104.83.4504523617288130.3728291288425
Winsorized Mean ( 15 / 31 )104.6421052631583.3812246166229230.9479898935764
Winsorized Mean ( 16 / 31 )104.4736842105263.3084046525423331.5782666217217
Winsorized Mean ( 17 / 31 )104.1157894736843.2064766190632132.4704658236685
Winsorized Mean ( 18 / 31 )104.1157894736843.1538690278756433.0120840635585
Winsorized Mean ( 19 / 31 )104.1157894736843.0987431313242833.5993611155466
Winsorized Mean ( 20 / 31 )103.6947368421052.9829704670368434.7622405209768
Winsorized Mean ( 21 / 31 )103.9157894736842.8938929850136235.9086497019154
Winsorized Mean ( 22 / 31 )103.2210526315792.8006229888991436.8564612376308
Winsorized Mean ( 23 / 31 )101.7684210526322.615118959803938.9154079094982
Winsorized Mean ( 24 / 31 )102.2736842105262.4811243570379441.2207005748895
Winsorized Mean ( 25 / 31 )102.82.4112279354666842.6338789825374
Winsorized Mean ( 26 / 31 )101.9789473684212.3109350525014444.1288677749881
Winsorized Mean ( 27 / 31 )101.9789473684212.167818113807247.0422065019662
Winsorized Mean ( 28 / 31 )102.8631578947371.7629768756000558.3462887791572
Winsorized Mean ( 29 / 31 )103.4736842105261.614245243309164.1003494601674
Winsorized Mean ( 30 / 31 )103.7894736842111.5760593221623165.8537862279285
Winsorized Mean ( 31 / 31 )103.4631578947371.5384443012848567.2518061319011
Trimmed Mean ( 1 / 31 )104.5376344086024.0469590202740725.8311571441419
Trimmed Mean ( 2 / 31 )104.3626373626373.9334362836069626.5321794578396
Trimmed Mean ( 3 / 31 )104.382022471913.8566137036177227.0657189165703
Trimmed Mean ( 4 / 31 )104.356321839083.7929920682212727.5129290971648
Trimmed Mean ( 5 / 31 )104.3411764705883.7368463216597627.9222551555837
Trimmed Mean ( 6 / 31 )104.3132530120483.6793267995873228.3511790862797
Trimmed Mean ( 7 / 31 )104.3132530120483.6251662739302328.7747499369061
Trimmed Mean ( 8 / 31 )104.1772151898733.5673043513973529.2033437374263
Trimmed Mean ( 9 / 31 )104.1038961038963.4996135132566129.7472551496182
Trimmed Mean ( 10 / 31 )104.0133333333333.4231587190218930.3851915353353
Trimmed Mean ( 11 / 31 )103.9863013698633.3561146829482530.984132305787
Trimmed Mean ( 12 / 31 )103.9859154929583.2899146514127231.6074811996431
Trimmed Mean ( 13 / 31 )103.9275362318843.2310381224810332.1653698570666
Trimmed Mean ( 14 / 31 )103.9275362318843.1641737709349832.8450786067842
Trimmed Mean ( 15 / 31 )103.7846153846153.0944656171334833.5387844705655
Trimmed Mean ( 16 / 31 )103.6984126984133.0223298440006534.3107529789493
Trimmed Mean ( 17 / 31 )103.6229508196722.9474601397886235.1566928491537
Trimmed Mean ( 18 / 31 )103.5762711864412.873954808598236.0396311300946
Trimmed Mean ( 19 / 31 )103.5263157894742.7928822509448537.0679128181827
Trimmed Mean ( 20 / 31 )103.4727272727272.7026429944016438.2857549025398
Trimmed Mean ( 21 / 31 )103.4528301886792.6121528578518639.6044319832627
Trimmed Mean ( 22 / 31 )103.4117647058822.5157038496780441.1064938025663
Trimmed Mean ( 23 / 31 )103.4285714285712.4124112193314942.8735244637242
Trimmed Mean ( 24 / 31 )103.5744680851062.3178798010887444.6850039576928
Trimmed Mean ( 25 / 31 )103.6888888888892.224932690440846.6031576300612
Trimmed Mean ( 26 / 31 )103.7674418604652.1195804995904248.9565939489048
Trimmed Mean ( 27 / 31 )103.9268292682932.0028608331469751.8891914746761
Trimmed Mean ( 28 / 31 )103.9268292682931.8827990733480755.1980456860357
Trimmed Mean ( 29 / 31 )104.2162162162161.8266196215809857.0541425181969
Trimmed Mean ( 30 / 31 )104.2857142857141.7853613096520358.4115460114009
Trimmed Mean ( 31 / 31 )104.3333333333331.7351461965011360.1294193790233
Median103
Midrange111
Midmean - Weighted Average at Xnp101.44
Midmean - Weighted Average at X(n+1)p102.039215686275
Midmean - Empirical Distribution Function102.039215686275
Midmean - Empirical Distribution Function - Averaging102.039215686275
Midmean - Empirical Distribution Function - Interpolation103.574468085106
Midmean - Closest Observation101.44
Midmean - True Basic - Statistics Graphics Toolkit102.039215686275
Midmean - MS Excel (old versions)102.039215686275
Number of observations95



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')