Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 20 Oct 2009 11:54:00 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Oct/20/t1256061364e6lbacojuupsiqk.htm/, Retrieved Thu, 02 May 2024 16:19:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=48902, Retrieved Thu, 02 May 2024 16:19:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSHWWS3V2: Central Tendency Y[t]-X[t]: waarbij Y[t]=werkloosheidsgraad mannen en X[t]= werkloosheidsgraad vrouwen
Estimated Impact160
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
F RMPD  [Univariate Explorative Data Analysis] [Colombia Coffee] [2008-01-07 14:21:11] [74be16979710d4c4e7c6647856088456]
F RMPD    [Univariate Data Series] [] [2009-10-14 08:30:28] [74be16979710d4c4e7c6647856088456]
- RMP       [Histogram] [Histogram] [2009-10-16 09:23:58] [4395c69e961f9a13a0559fd2f0a72538]
- RMPD        [Quartiles] [Quartiles] [2009-10-16 09:37:48] [4395c69e961f9a13a0559fd2f0a72538]
- RM            [Percentiles] [Percentiles] [2009-10-16 09:44:59] [4395c69e961f9a13a0559fd2f0a72538]
- RM D              [Central Tendency] [Central Tendency ...] [2009-10-20 17:54:00] [d1081bd6cdf1fed9ed45c42dbd523bf1] [Current]
-    D                [Central Tendency] [Central Tendency ...] [2009-10-20 18:10:34] [4395c69e961f9a13a0559fd2f0a72538]
- RMPD                  [Univariate Explorative Data Analysis] [EDA E[t] Werkloos...] [2009-10-20 18:20:50] [4395c69e961f9a13a0559fd2f0a72538]
- RMP                     [Harrell-Davis Quantiles] [Harrell Davis Qua...] [2009-10-20 19:17:03] [4395c69e961f9a13a0559fd2f0a72538]
- RM D                  [Variability] [Variability e[t]] [2009-10-20 18:29:02] [4395c69e961f9a13a0559fd2f0a72538]
- RM D                  [Univariate Data Series] [Grafiek e[t] : ni...] [2009-10-20 18:36:07] [4395c69e961f9a13a0559fd2f0a72538]
-    D                [Central Tendency] [Central Tendency ...] [2009-10-20 18:41:52] [4395c69e961f9a13a0559fd2f0a72538]
- RM D                  [Univariate Data Series] [Grafiek E[t]: Y[t...] [2009-10-20 18:53:38] [4395c69e961f9a13a0559fd2f0a72538]
- RM D                    [Central Tendency] [Central Tendency ...] [2009-10-20 18:55:54] [4395c69e961f9a13a0559fd2f0a72538]
- RM                        [Variability] [Variability e[t]:...] [2009-10-20 19:03:21] [4395c69e961f9a13a0559fd2f0a72538]
- RMP                         [Univariate Explorative Data Analysis] [EDA e[t] : Y[t]/X[t]] [2009-10-20 19:07:22] [4395c69e961f9a13a0559fd2f0a72538]
- RMP                         [Univariate Explorative Data Analysis] [EDA e[t]: Y[t]/X[t]] [2009-10-20 19:10:52] [4395c69e961f9a13a0559fd2f0a72538]
- RMP                           [Harrell-Davis Quantiles] [Harrell Davis Qua...] [2009-10-20 19:22:36] [4395c69e961f9a13a0559fd2f0a72538]
- RMPD                [Bivariate Explorative Data Analysis] [Workshop 4: Y[t] ...] [2009-10-23 17:01:25] [3cb427d596a5d2eb77fa64560dc91319]
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Post a new message
Dataseries X:
-0,6
-1,5
-1,9
-1,8
-1,2
-1,1
-1,2
-1,7
-1,8
-1,8
-1,5
-1,5
-1,9
-2,8
-3,1
-2,8
-2,3
-1,7
-1,6
-1,7
-1,8
-1,7
-1,6
-1,4
-1,9
-2,6
-2,8
-2,6
-1,9
-1,5
-1,4
-1,3
-1,2
-1
-0,8
-1,1
-1,7
-2,9
-3,4
-3,1
-2,4
-2
-1,9
-1,9
-2
-2,2
-2,2
-2
-1,9
-1,7
-1,5
-1,3
-1,6
-1,7
-1,5
-1,1
-0,8
-0,7
-0,7
-0,7
-0,8
-1
-1,4
-1,4
-1,8
-1,7
-1,6
-1,2
-0,7
-0,3
0
0,2
0,2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=48902&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]3 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=48902&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=48902&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-1.595890410958900.0854622660590965-18.6736262042871
Geometric MeanNaN
Harmonic Mean0
Quadratic Mean1.75292319456027
Winsorized Mean ( 1 / 24 )-1.591780821917810.0843489126119515-18.8713852096804
Winsorized Mean ( 2 / 24 )-1.597260273972600.0828059247107256-19.2892027901684
Winsorized Mean ( 3 / 24 )-1.60136986301370.0777218715038722-20.6038510399729
Winsorized Mean ( 4 / 24 )-1.612328767123290.0729604781747803-22.0986595408665
Winsorized Mean ( 5 / 24 )-1.619178082191780.0716902248167182-22.5857581885304
Winsorized Mean ( 6 / 24 )-1.619178082191780.0716902248167182-22.5857581885304
Winsorized Mean ( 7 / 24 )-1.60.0675174029090723-23.6975939692877
Winsorized Mean ( 8 / 24 )-1.60.0675174029090723-23.6975939692877
Winsorized Mean ( 9 / 24 )-1.587671232876710.060406575459546-26.2830862501048
Winsorized Mean ( 10 / 24 )-1.573972602739730.0579333119623982-27.1686970660562
Winsorized Mean ( 11 / 24 )-1.558904109589040.0554089410427805-28.1345227006853
Winsorized Mean ( 12 / 24 )-1.591780821917810.0495318042999165-32.1365402374508
Winsorized Mean ( 13 / 24 )-1.556164383561640.0439656319600303-35.3950191134833
Winsorized Mean ( 14 / 24 )-1.575342465753420.0407212758349161-38.6859800793045
Winsorized Mean ( 15 / 24 )-1.575342465753420.0407212758349161-38.6859800793045
Winsorized Mean ( 16 / 24 )-1.553424657534250.0377286127275318-41.1736489955981
Winsorized Mean ( 17 / 24 )-1.576712328767120.0339845378455686-46.3949910377468
Winsorized Mean ( 18 / 24 )-1.576712328767120.0339845378455686-46.3949910377468
Winsorized Mean ( 19 / 24 )-1.576712328767120.0339845378455686-46.3949910377468
Winsorized Mean ( 20 / 24 )-1.576712328767120.0339845378455686-46.3949910377468
Winsorized Mean ( 21 / 24 )-1.605479452054790.0297049424060102-54.0475531011283
Winsorized Mean ( 22 / 24 )-1.605479452054790.0297049424060102-54.0475531011283
Winsorized Mean ( 23 / 24 )-1.605479452054790.0210900088660112-76.1251198259187
Winsorized Mean ( 24 / 24 )-1.605479452054790.0210900088660112-76.1251198259187
Trimmed Mean ( 1 / 24 )-1.595774647887320.0801265754128905-19.9156726674556
Trimmed Mean ( 2 / 24 )-1.60.0750390634274456-21.3222277427146
Trimmed Mean ( 3 / 24 )-1.601492537313430.0699063318939474-22.9091198740481
Trimmed Mean ( 4 / 24 )-1.601538461538460.0661979951072011-24.1931565894848
Trimmed Mean ( 5 / 24 )-1.59841269841270.0635803277940326-25.1400512370859
Trimmed Mean ( 6 / 24 )-1.593442622950820.060817241787861-26.2005078840795
Trimmed Mean ( 7 / 24 )-1.588135593220340.0574178826005478-27.6592504162664
Trimmed Mean ( 8 / 24 )-1.585964912280700.0544647339678221-29.1191161094754
Trimmed Mean ( 9 / 24 )-1.583636363636360.0507694091437514-31.192727871864
Trimmed Mean ( 10 / 24 )-1.583018867924530.0480939942854863-32.915104919914
Trimmed Mean ( 11 / 24 )-1.584313725490200.0453632440846031-34.9250534757926
Trimmed Mean ( 12 / 24 )-1.587755102040820.0425217684408462-37.3398181745336
Trimmed Mean ( 13 / 24 )-1.587234042553190.0404206628354523-39.2678875409498
Trimmed Mean ( 14 / 24 )-1.591111111111110.0390314846005562-40.7648114693654
Trimmed Mean ( 15 / 24 )-1.593023255813950.0380003131124842-41.9213192033042
Trimmed Mean ( 16 / 24 )-1.595121951219510.0366178717382172-43.5612960420832
Trimmed Mean ( 17 / 24 )-1.60.0354268362790828-45.1635022499791
Trimmed Mean ( 18 / 24 )-1.602702702702700.0347635700568914-46.102937646503
Trimmed Mean ( 19 / 24 )-1.605714285714290.0337919629306065-47.5176387063309
Trimmed Mean ( 20 / 24 )-1.609090909090910.0323813792017614-49.6918583691266
Trimmed Mean ( 21 / 24 )-1.612903225806450.0303180046878961-53.1995176598931
Trimmed Mean ( 22 / 24 )-1.613793103448280.0288208915789361-55.9938646945858
Trimmed Mean ( 23 / 24 )-1.614814814814810.0265294029772202-60.8688712746907
Trimmed Mean ( 24 / 24 )-1.6160.0262551582233536-61.5498099936259
Median-1.6
Midrange-1.6
Midmean - Weighted Average at Xnp-1.6075
Midmean - Weighted Average at X(n+1)p-1.6075
Midmean - Empirical Distribution Function-1.6075
Midmean - Empirical Distribution Function - Averaging-1.6075
Midmean - Empirical Distribution Function - Interpolation-1.6075
Midmean - Closest Observation-1.6075
Midmean - True Basic - Statistics Graphics Toolkit-1.6075
Midmean - MS Excel (old versions)-1.6075
Number of observations73

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -1.59589041095890 & 0.0854622660590965 & -18.6736262042871 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 0 &  &  \tabularnewline
Quadratic Mean & 1.75292319456027 &  &  \tabularnewline
Winsorized Mean ( 1 / 24 ) & -1.59178082191781 & 0.0843489126119515 & -18.8713852096804 \tabularnewline
Winsorized Mean ( 2 / 24 ) & -1.59726027397260 & 0.0828059247107256 & -19.2892027901684 \tabularnewline
Winsorized Mean ( 3 / 24 ) & -1.6013698630137 & 0.0777218715038722 & -20.6038510399729 \tabularnewline
Winsorized Mean ( 4 / 24 ) & -1.61232876712329 & 0.0729604781747803 & -22.0986595408665 \tabularnewline
Winsorized Mean ( 5 / 24 ) & -1.61917808219178 & 0.0716902248167182 & -22.5857581885304 \tabularnewline
Winsorized Mean ( 6 / 24 ) & -1.61917808219178 & 0.0716902248167182 & -22.5857581885304 \tabularnewline
Winsorized Mean ( 7 / 24 ) & -1.6 & 0.0675174029090723 & -23.6975939692877 \tabularnewline
Winsorized Mean ( 8 / 24 ) & -1.6 & 0.0675174029090723 & -23.6975939692877 \tabularnewline
Winsorized Mean ( 9 / 24 ) & -1.58767123287671 & 0.060406575459546 & -26.2830862501048 \tabularnewline
Winsorized Mean ( 10 / 24 ) & -1.57397260273973 & 0.0579333119623982 & -27.1686970660562 \tabularnewline
Winsorized Mean ( 11 / 24 ) & -1.55890410958904 & 0.0554089410427805 & -28.1345227006853 \tabularnewline
Winsorized Mean ( 12 / 24 ) & -1.59178082191781 & 0.0495318042999165 & -32.1365402374508 \tabularnewline
Winsorized Mean ( 13 / 24 ) & -1.55616438356164 & 0.0439656319600303 & -35.3950191134833 \tabularnewline
Winsorized Mean ( 14 / 24 ) & -1.57534246575342 & 0.0407212758349161 & -38.6859800793045 \tabularnewline
Winsorized Mean ( 15 / 24 ) & -1.57534246575342 & 0.0407212758349161 & -38.6859800793045 \tabularnewline
Winsorized Mean ( 16 / 24 ) & -1.55342465753425 & 0.0377286127275318 & -41.1736489955981 \tabularnewline
Winsorized Mean ( 17 / 24 ) & -1.57671232876712 & 0.0339845378455686 & -46.3949910377468 \tabularnewline
Winsorized Mean ( 18 / 24 ) & -1.57671232876712 & 0.0339845378455686 & -46.3949910377468 \tabularnewline
Winsorized Mean ( 19 / 24 ) & -1.57671232876712 & 0.0339845378455686 & -46.3949910377468 \tabularnewline
Winsorized Mean ( 20 / 24 ) & -1.57671232876712 & 0.0339845378455686 & -46.3949910377468 \tabularnewline
Winsorized Mean ( 21 / 24 ) & -1.60547945205479 & 0.0297049424060102 & -54.0475531011283 \tabularnewline
Winsorized Mean ( 22 / 24 ) & -1.60547945205479 & 0.0297049424060102 & -54.0475531011283 \tabularnewline
Winsorized Mean ( 23 / 24 ) & -1.60547945205479 & 0.0210900088660112 & -76.1251198259187 \tabularnewline
Winsorized Mean ( 24 / 24 ) & -1.60547945205479 & 0.0210900088660112 & -76.1251198259187 \tabularnewline
Trimmed Mean ( 1 / 24 ) & -1.59577464788732 & 0.0801265754128905 & -19.9156726674556 \tabularnewline
Trimmed Mean ( 2 / 24 ) & -1.6 & 0.0750390634274456 & -21.3222277427146 \tabularnewline
Trimmed Mean ( 3 / 24 ) & -1.60149253731343 & 0.0699063318939474 & -22.9091198740481 \tabularnewline
Trimmed Mean ( 4 / 24 ) & -1.60153846153846 & 0.0661979951072011 & -24.1931565894848 \tabularnewline
Trimmed Mean ( 5 / 24 ) & -1.5984126984127 & 0.0635803277940326 & -25.1400512370859 \tabularnewline
Trimmed Mean ( 6 / 24 ) & -1.59344262295082 & 0.060817241787861 & -26.2005078840795 \tabularnewline
Trimmed Mean ( 7 / 24 ) & -1.58813559322034 & 0.0574178826005478 & -27.6592504162664 \tabularnewline
Trimmed Mean ( 8 / 24 ) & -1.58596491228070 & 0.0544647339678221 & -29.1191161094754 \tabularnewline
Trimmed Mean ( 9 / 24 ) & -1.58363636363636 & 0.0507694091437514 & -31.192727871864 \tabularnewline
Trimmed Mean ( 10 / 24 ) & -1.58301886792453 & 0.0480939942854863 & -32.915104919914 \tabularnewline
Trimmed Mean ( 11 / 24 ) & -1.58431372549020 & 0.0453632440846031 & -34.9250534757926 \tabularnewline
Trimmed Mean ( 12 / 24 ) & -1.58775510204082 & 0.0425217684408462 & -37.3398181745336 \tabularnewline
Trimmed Mean ( 13 / 24 ) & -1.58723404255319 & 0.0404206628354523 & -39.2678875409498 \tabularnewline
Trimmed Mean ( 14 / 24 ) & -1.59111111111111 & 0.0390314846005562 & -40.7648114693654 \tabularnewline
Trimmed Mean ( 15 / 24 ) & -1.59302325581395 & 0.0380003131124842 & -41.9213192033042 \tabularnewline
Trimmed Mean ( 16 / 24 ) & -1.59512195121951 & 0.0366178717382172 & -43.5612960420832 \tabularnewline
Trimmed Mean ( 17 / 24 ) & -1.6 & 0.0354268362790828 & -45.1635022499791 \tabularnewline
Trimmed Mean ( 18 / 24 ) & -1.60270270270270 & 0.0347635700568914 & -46.102937646503 \tabularnewline
Trimmed Mean ( 19 / 24 ) & -1.60571428571429 & 0.0337919629306065 & -47.5176387063309 \tabularnewline
Trimmed Mean ( 20 / 24 ) & -1.60909090909091 & 0.0323813792017614 & -49.6918583691266 \tabularnewline
Trimmed Mean ( 21 / 24 ) & -1.61290322580645 & 0.0303180046878961 & -53.1995176598931 \tabularnewline
Trimmed Mean ( 22 / 24 ) & -1.61379310344828 & 0.0288208915789361 & -55.9938646945858 \tabularnewline
Trimmed Mean ( 23 / 24 ) & -1.61481481481481 & 0.0265294029772202 & -60.8688712746907 \tabularnewline
Trimmed Mean ( 24 / 24 ) & -1.616 & 0.0262551582233536 & -61.5498099936259 \tabularnewline
Median & -1.6 &  &  \tabularnewline
Midrange & -1.6 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -1.6075 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -1.6075 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -1.6075 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -1.6075 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -1.6075 &  &  \tabularnewline
Midmean - Closest Observation & -1.6075 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -1.6075 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -1.6075 &  &  \tabularnewline
Number of observations & 73 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=48902&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]-1.59589041095890[/C][C]0.0854622660590965[/C][C]-18.6736262042871[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/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]1.75292319456027[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 24 )[/C][C]-1.59178082191781[/C][C]0.0843489126119515[/C][C]-18.8713852096804[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 24 )[/C][C]-1.59726027397260[/C][C]0.0828059247107256[/C][C]-19.2892027901684[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 24 )[/C][C]-1.6013698630137[/C][C]0.0777218715038722[/C][C]-20.6038510399729[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 24 )[/C][C]-1.61232876712329[/C][C]0.0729604781747803[/C][C]-22.0986595408665[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 24 )[/C][C]-1.61917808219178[/C][C]0.0716902248167182[/C][C]-22.5857581885304[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 24 )[/C][C]-1.61917808219178[/C][C]0.0716902248167182[/C][C]-22.5857581885304[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 24 )[/C][C]-1.6[/C][C]0.0675174029090723[/C][C]-23.6975939692877[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 24 )[/C][C]-1.6[/C][C]0.0675174029090723[/C][C]-23.6975939692877[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 24 )[/C][C]-1.58767123287671[/C][C]0.060406575459546[/C][C]-26.2830862501048[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 24 )[/C][C]-1.57397260273973[/C][C]0.0579333119623982[/C][C]-27.1686970660562[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 24 )[/C][C]-1.55890410958904[/C][C]0.0554089410427805[/C][C]-28.1345227006853[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 24 )[/C][C]-1.59178082191781[/C][C]0.0495318042999165[/C][C]-32.1365402374508[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 24 )[/C][C]-1.55616438356164[/C][C]0.0439656319600303[/C][C]-35.3950191134833[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 24 )[/C][C]-1.57534246575342[/C][C]0.0407212758349161[/C][C]-38.6859800793045[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 24 )[/C][C]-1.57534246575342[/C][C]0.0407212758349161[/C][C]-38.6859800793045[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 24 )[/C][C]-1.55342465753425[/C][C]0.0377286127275318[/C][C]-41.1736489955981[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 24 )[/C][C]-1.57671232876712[/C][C]0.0339845378455686[/C][C]-46.3949910377468[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 24 )[/C][C]-1.57671232876712[/C][C]0.0339845378455686[/C][C]-46.3949910377468[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 24 )[/C][C]-1.57671232876712[/C][C]0.0339845378455686[/C][C]-46.3949910377468[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 24 )[/C][C]-1.57671232876712[/C][C]0.0339845378455686[/C][C]-46.3949910377468[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 24 )[/C][C]-1.60547945205479[/C][C]0.0297049424060102[/C][C]-54.0475531011283[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 24 )[/C][C]-1.60547945205479[/C][C]0.0297049424060102[/C][C]-54.0475531011283[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 24 )[/C][C]-1.60547945205479[/C][C]0.0210900088660112[/C][C]-76.1251198259187[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 24 )[/C][C]-1.60547945205479[/C][C]0.0210900088660112[/C][C]-76.1251198259187[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 24 )[/C][C]-1.59577464788732[/C][C]0.0801265754128905[/C][C]-19.9156726674556[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 24 )[/C][C]-1.6[/C][C]0.0750390634274456[/C][C]-21.3222277427146[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 24 )[/C][C]-1.60149253731343[/C][C]0.0699063318939474[/C][C]-22.9091198740481[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 24 )[/C][C]-1.60153846153846[/C][C]0.0661979951072011[/C][C]-24.1931565894848[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 24 )[/C][C]-1.5984126984127[/C][C]0.0635803277940326[/C][C]-25.1400512370859[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 24 )[/C][C]-1.59344262295082[/C][C]0.060817241787861[/C][C]-26.2005078840795[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 24 )[/C][C]-1.58813559322034[/C][C]0.0574178826005478[/C][C]-27.6592504162664[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 24 )[/C][C]-1.58596491228070[/C][C]0.0544647339678221[/C][C]-29.1191161094754[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 24 )[/C][C]-1.58363636363636[/C][C]0.0507694091437514[/C][C]-31.192727871864[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 24 )[/C][C]-1.58301886792453[/C][C]0.0480939942854863[/C][C]-32.915104919914[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 24 )[/C][C]-1.58431372549020[/C][C]0.0453632440846031[/C][C]-34.9250534757926[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 24 )[/C][C]-1.58775510204082[/C][C]0.0425217684408462[/C][C]-37.3398181745336[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 24 )[/C][C]-1.58723404255319[/C][C]0.0404206628354523[/C][C]-39.2678875409498[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 24 )[/C][C]-1.59111111111111[/C][C]0.0390314846005562[/C][C]-40.7648114693654[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 24 )[/C][C]-1.59302325581395[/C][C]0.0380003131124842[/C][C]-41.9213192033042[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 24 )[/C][C]-1.59512195121951[/C][C]0.0366178717382172[/C][C]-43.5612960420832[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 24 )[/C][C]-1.6[/C][C]0.0354268362790828[/C][C]-45.1635022499791[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 24 )[/C][C]-1.60270270270270[/C][C]0.0347635700568914[/C][C]-46.102937646503[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 24 )[/C][C]-1.60571428571429[/C][C]0.0337919629306065[/C][C]-47.5176387063309[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 24 )[/C][C]-1.60909090909091[/C][C]0.0323813792017614[/C][C]-49.6918583691266[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 24 )[/C][C]-1.61290322580645[/C][C]0.0303180046878961[/C][C]-53.1995176598931[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 24 )[/C][C]-1.61379310344828[/C][C]0.0288208915789361[/C][C]-55.9938646945858[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 24 )[/C][C]-1.61481481481481[/C][C]0.0265294029772202[/C][C]-60.8688712746907[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 24 )[/C][C]-1.616[/C][C]0.0262551582233536[/C][C]-61.5498099936259[/C][/ROW]
[ROW][C]Median[/C][C]-1.6[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-1.6[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-1.6075[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-1.6075[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-1.6075[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-1.6075[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-1.6075[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-1.6075[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-1.6075[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-1.6075[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]73[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=48902&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=48902&T=1

As an alternative you can also use a QR Code:  

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

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-1.595890410958900.0854622660590965-18.6736262042871
Geometric MeanNaN
Harmonic Mean0
Quadratic Mean1.75292319456027
Winsorized Mean ( 1 / 24 )-1.591780821917810.0843489126119515-18.8713852096804
Winsorized Mean ( 2 / 24 )-1.597260273972600.0828059247107256-19.2892027901684
Winsorized Mean ( 3 / 24 )-1.60136986301370.0777218715038722-20.6038510399729
Winsorized Mean ( 4 / 24 )-1.612328767123290.0729604781747803-22.0986595408665
Winsorized Mean ( 5 / 24 )-1.619178082191780.0716902248167182-22.5857581885304
Winsorized Mean ( 6 / 24 )-1.619178082191780.0716902248167182-22.5857581885304
Winsorized Mean ( 7 / 24 )-1.60.0675174029090723-23.6975939692877
Winsorized Mean ( 8 / 24 )-1.60.0675174029090723-23.6975939692877
Winsorized Mean ( 9 / 24 )-1.587671232876710.060406575459546-26.2830862501048
Winsorized Mean ( 10 / 24 )-1.573972602739730.0579333119623982-27.1686970660562
Winsorized Mean ( 11 / 24 )-1.558904109589040.0554089410427805-28.1345227006853
Winsorized Mean ( 12 / 24 )-1.591780821917810.0495318042999165-32.1365402374508
Winsorized Mean ( 13 / 24 )-1.556164383561640.0439656319600303-35.3950191134833
Winsorized Mean ( 14 / 24 )-1.575342465753420.0407212758349161-38.6859800793045
Winsorized Mean ( 15 / 24 )-1.575342465753420.0407212758349161-38.6859800793045
Winsorized Mean ( 16 / 24 )-1.553424657534250.0377286127275318-41.1736489955981
Winsorized Mean ( 17 / 24 )-1.576712328767120.0339845378455686-46.3949910377468
Winsorized Mean ( 18 / 24 )-1.576712328767120.0339845378455686-46.3949910377468
Winsorized Mean ( 19 / 24 )-1.576712328767120.0339845378455686-46.3949910377468
Winsorized Mean ( 20 / 24 )-1.576712328767120.0339845378455686-46.3949910377468
Winsorized Mean ( 21 / 24 )-1.605479452054790.0297049424060102-54.0475531011283
Winsorized Mean ( 22 / 24 )-1.605479452054790.0297049424060102-54.0475531011283
Winsorized Mean ( 23 / 24 )-1.605479452054790.0210900088660112-76.1251198259187
Winsorized Mean ( 24 / 24 )-1.605479452054790.0210900088660112-76.1251198259187
Trimmed Mean ( 1 / 24 )-1.595774647887320.0801265754128905-19.9156726674556
Trimmed Mean ( 2 / 24 )-1.60.0750390634274456-21.3222277427146
Trimmed Mean ( 3 / 24 )-1.601492537313430.0699063318939474-22.9091198740481
Trimmed Mean ( 4 / 24 )-1.601538461538460.0661979951072011-24.1931565894848
Trimmed Mean ( 5 / 24 )-1.59841269841270.0635803277940326-25.1400512370859
Trimmed Mean ( 6 / 24 )-1.593442622950820.060817241787861-26.2005078840795
Trimmed Mean ( 7 / 24 )-1.588135593220340.0574178826005478-27.6592504162664
Trimmed Mean ( 8 / 24 )-1.585964912280700.0544647339678221-29.1191161094754
Trimmed Mean ( 9 / 24 )-1.583636363636360.0507694091437514-31.192727871864
Trimmed Mean ( 10 / 24 )-1.583018867924530.0480939942854863-32.915104919914
Trimmed Mean ( 11 / 24 )-1.584313725490200.0453632440846031-34.9250534757926
Trimmed Mean ( 12 / 24 )-1.587755102040820.0425217684408462-37.3398181745336
Trimmed Mean ( 13 / 24 )-1.587234042553190.0404206628354523-39.2678875409498
Trimmed Mean ( 14 / 24 )-1.591111111111110.0390314846005562-40.7648114693654
Trimmed Mean ( 15 / 24 )-1.593023255813950.0380003131124842-41.9213192033042
Trimmed Mean ( 16 / 24 )-1.595121951219510.0366178717382172-43.5612960420832
Trimmed Mean ( 17 / 24 )-1.60.0354268362790828-45.1635022499791
Trimmed Mean ( 18 / 24 )-1.602702702702700.0347635700568914-46.102937646503
Trimmed Mean ( 19 / 24 )-1.605714285714290.0337919629306065-47.5176387063309
Trimmed Mean ( 20 / 24 )-1.609090909090910.0323813792017614-49.6918583691266
Trimmed Mean ( 21 / 24 )-1.612903225806450.0303180046878961-53.1995176598931
Trimmed Mean ( 22 / 24 )-1.613793103448280.0288208915789361-55.9938646945858
Trimmed Mean ( 23 / 24 )-1.614814814814810.0265294029772202-60.8688712746907
Trimmed Mean ( 24 / 24 )-1.6160.0262551582233536-61.5498099936259
Median-1.6
Midrange-1.6
Midmean - Weighted Average at Xnp-1.6075
Midmean - Weighted Average at X(n+1)p-1.6075
Midmean - Empirical Distribution Function-1.6075
Midmean - Empirical Distribution Function - Averaging-1.6075
Midmean - Empirical Distribution Function - Interpolation-1.6075
Midmean - Closest Observation-1.6075
Midmean - True Basic - Statistics Graphics Toolkit-1.6075
Midmean - MS Excel (old versions)-1.6075
Number of observations73



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')