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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 computationTue, 29 Nov 2011 06:03:23 -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/29/t1322564627odmz9tnehnz1fuq.htm/, Retrieved Fri, 26 Apr 2024 20:44:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148191, Retrieved Fri, 26 Apr 2024 20:44:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact56
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [central tendency] [2011-11-29 11:03:23] [05d3841c0e91f0207133db830e88168b] [Current]
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Dataseries X:
26
20
19
NA
20
25
NA
22
26
22
NA
NA
19
24
26
NA
13
NA
NA
22
NA
21
7
NA
17
25
25
19
NA
23
NA
22
21
NA
NA
NA
18
NA
NA
22
18
23
20
NA
NA
15
NA
NA
21
NA
18
19
22
16
NA
18
20
24
NA
NA
24
18
21
NA
17
NA
NA
NA
22
16
21
NA
NA
24
24
16
16
NA
NA
NA
NA
18
NA
20
NA
NA
24
17
19
20
15
NA
22
23
16
19
NA
19
NA
NA
21
NA
24
22
NA
18
NA
24
24
22
23
22
20
18
25
NA
16
20
NA
15
19
19
16
17
28
NA
25
20
NA
NA
16
NA
NA
NA
NA
23
21
NA
NA
23
18
20
9
NA
25
20
NA
NA
NA
NA
21
22
27
NA
NA
NA
18
16
22
20
NA
20




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148191&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148191&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148191&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'Herman Ole Andreas Wold' @ wold.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic MeanNANANA
Geometric MeanNA
Harmonic MeanNA
Quadratic MeanNA
Winsorized Mean ( 1 / 32 )20.29591836734690.35535907517135757.1138315732055
Winsorized Mean ( 2 / 32 )20.35714285714290.32860984599636861.94927846857
Winsorized Mean ( 3 / 32 )20.41836734693880.31610248406305564.5941375862955
Winsorized Mean ( 4 / 32 )20.41836734693880.31610248406305564.5941375862955
Winsorized Mean ( 5 / 32 )20.36734693877550.30748696520108966.2380824027963
Winsorized Mean ( 6 / 32 )20.42857142857140.29726291898657468.7222324877127
Winsorized Mean ( 7 / 32 )20.42857142857140.29726291898657468.7222324877127
Winsorized Mean ( 8 / 32 )20.42857142857140.29726291898657468.7222324877127
Winsorized Mean ( 9 / 32 )20.42857142857140.29726291898657468.7222324877127
Winsorized Mean ( 10 / 32 )20.42857142857140.29726291898657468.7222324877127
Winsorized Mean ( 11 / 32 )20.31632653061220.28073606280806672.3680681683641
Winsorized Mean ( 12 / 32 )20.31632653061220.28073606280806672.3680681683641
Winsorized Mean ( 13 / 32 )20.31632653061220.28073606280806672.3680681683641
Winsorized Mean ( 14 / 32 )20.31632653061220.28073606280806672.3680681683641
Winsorized Mean ( 15 / 32 )20.4693877551020.25792879467965779.360614934539
Winsorized Mean ( 16 / 32 )20.4693877551020.25792879467965779.360614934539
Winsorized Mean ( 17 / 32 )20.4693877551020.25792879467965779.360614934539
Winsorized Mean ( 18 / 32 )20.4693877551020.25792879467965779.360614934539
Winsorized Mean ( 19 / 32 )20.66326530612240.23295857705209788.6993111290404
Winsorized Mean ( 20 / 32 )20.45918367346940.20470397429904199.9452196447424
Winsorized Mean ( 21 / 32 )20.45918367346940.20470397429904199.9452196447424
Winsorized Mean ( 22 / 32 )20.45918367346940.20470397429904199.9452196447424
Winsorized Mean ( 23 / 32 )20.45918367346940.20470397429904199.9452196447424
Winsorized Mean ( 24 / 32 )20.45918367346940.20470397429904199.9452196447424
Winsorized Mean ( 25 / 32 )20.45918367346940.20470397429904199.9452196447424
Winsorized Mean ( 26 / 32 )20.19387755102040.173246475010541116.561549375199
Winsorized Mean ( 27 / 32 )20.19387755102040.173246475010541116.561549375199
Winsorized Mean ( 28 / 32 )20.19387755102040.173246475010541116.561549375199
Winsorized Mean ( 29 / 32 )20.48979591836730.137027518048538149.53051919914
Winsorized Mean ( 30 / 32 )20.48979591836730.137027518048538149.53051919914
Winsorized Mean ( 31 / 32 )20.48979591836730.137027518048538149.53051919914
Winsorized Mean ( 32 / 32 )20.48979591836730.137027518048538149.53051919914
Trimmed Mean ( 1 / 32 )20.28571428571430.33568081023443960.4315577990496
Trimmed Mean ( 2 / 32 )20.343750.31263270716188365.0723661790956
Trimmed Mean ( 3 / 32 )20.41304347826090.30293680143694367.3838351148958
Trimmed Mean ( 4 / 32 )20.41304347826090.29725941055693368.670806552485
Trimmed Mean ( 5 / 32 )20.40909090909090.29076537724976970.1909254194298
Trimmed Mean ( 6 / 32 )20.41860465116280.28576109346573671.4534102719307
Trimmed Mean ( 7 / 32 )20.41666666666670.28250190182765272.2708998933481
Trimmed Mean ( 8 / 32 )20.41666666666670.27869832264894273.2572283629572
Trimmed Mean ( 9 / 32 )20.41250.2742618113030774.4270589587969
Trimmed Mean ( 10 / 32 )20.41025641025640.26908405053510775.8508591262398
Trimmed Mean ( 11 / 32 )20.40789473684210.26303067100121677.5875096967219
Trimmed Mean ( 12 / 32 )20.41891891891890.25887201330607878.87650216857
Trimmed Mean ( 13 / 32 )20.43055555555560.25394107119646980.4539236575434
Trimmed Mean ( 14 / 32 )20.44285714285710.24808643578683282.4021558374222
Trimmed Mean ( 15 / 32 )20.45588235294120.2411140950196184.8390151196988
Trimmed Mean ( 16 / 32 )20.45588235294120.23670407614822286.4196455160826
Trimmed Mean ( 17 / 32 )20.4531250.23137966924361788.3963792793961
Trimmed Mean ( 18 / 32 )20.45161290322580.22493599695465790.9219208135391
Trimmed Mean ( 19 / 32 )20.450.21710082533602294.1958648399799
Trimmed Mean ( 20 / 32 )20.43103448275860.21174250271604296.4900018687211
Trimmed Mean ( 21 / 32 )20.42857142857140.20991207630187897.319657775157
Trimmed Mean ( 22 / 32 )20.42592592592590.20748039546338798.4474985229647
Trimmed Mean ( 23 / 32 )20.42307692307690.20430169083845799.9652858439906
Trimmed Mean ( 24 / 32 )20.420.200183589206896102.006363662984
Trimmed Mean ( 25 / 32 )20.41666666666670.194866141848118104.772776189
Trimmed Mean ( 26 / 32 )20.41304347826090.187987272044534108.587370071656
Trimmed Mean ( 27 / 32 )20.41304347826090.18505963633017110.305217729065
Trimmed Mean ( 28 / 32 )20.4523809523810.180984470533231113.006275577802
Trimmed Mean ( 29 / 32 )20.4750.175365917806754116.755868278594
Trimmed Mean ( 30 / 32 )20.47368421052630.175841169220103116.432825721826
Trimmed Mean ( 31 / 32 )20.47222222222220.175870222314642116.405278578634
Trimmed Mean ( 32 / 32 )20.47222222222220.17527820574039116.798446993143
MedianNA
MidrangeNA
Midmean - Weighted Average at Xnp20.3898305084746
Midmean - Weighted Average at X(n+1)p20.3898305084746
Midmean - Empirical Distribution Function20.3898305084746
Midmean - Empirical Distribution Function - Averaging20.3898305084746
Midmean - Empirical Distribution Function - Interpolation20.3898305084746
Midmean - Closest Observation20.3898305084746
Midmean - True Basic - Statistics Graphics Toolkit20.3898305084746
Midmean - MS Excel (old versions)20.3898305084746
Number of observations162

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & NA & NA & NA \tabularnewline
Geometric Mean & NA &  &  \tabularnewline
Harmonic Mean & NA &  &  \tabularnewline
Quadratic Mean & NA &  &  \tabularnewline
Winsorized Mean ( 1 / 32 ) & 20.2959183673469 & 0.355359075171357 & 57.1138315732055 \tabularnewline
Winsorized Mean ( 2 / 32 ) & 20.3571428571429 & 0.328609845996368 & 61.94927846857 \tabularnewline
Winsorized Mean ( 3 / 32 ) & 20.4183673469388 & 0.316102484063055 & 64.5941375862955 \tabularnewline
Winsorized Mean ( 4 / 32 ) & 20.4183673469388 & 0.316102484063055 & 64.5941375862955 \tabularnewline
Winsorized Mean ( 5 / 32 ) & 20.3673469387755 & 0.307486965201089 & 66.2380824027963 \tabularnewline
Winsorized Mean ( 6 / 32 ) & 20.4285714285714 & 0.297262918986574 & 68.7222324877127 \tabularnewline
Winsorized Mean ( 7 / 32 ) & 20.4285714285714 & 0.297262918986574 & 68.7222324877127 \tabularnewline
Winsorized Mean ( 8 / 32 ) & 20.4285714285714 & 0.297262918986574 & 68.7222324877127 \tabularnewline
Winsorized Mean ( 9 / 32 ) & 20.4285714285714 & 0.297262918986574 & 68.7222324877127 \tabularnewline
Winsorized Mean ( 10 / 32 ) & 20.4285714285714 & 0.297262918986574 & 68.7222324877127 \tabularnewline
Winsorized Mean ( 11 / 32 ) & 20.3163265306122 & 0.280736062808066 & 72.3680681683641 \tabularnewline
Winsorized Mean ( 12 / 32 ) & 20.3163265306122 & 0.280736062808066 & 72.3680681683641 \tabularnewline
Winsorized Mean ( 13 / 32 ) & 20.3163265306122 & 0.280736062808066 & 72.3680681683641 \tabularnewline
Winsorized Mean ( 14 / 32 ) & 20.3163265306122 & 0.280736062808066 & 72.3680681683641 \tabularnewline
Winsorized Mean ( 15 / 32 ) & 20.469387755102 & 0.257928794679657 & 79.360614934539 \tabularnewline
Winsorized Mean ( 16 / 32 ) & 20.469387755102 & 0.257928794679657 & 79.360614934539 \tabularnewline
Winsorized Mean ( 17 / 32 ) & 20.469387755102 & 0.257928794679657 & 79.360614934539 \tabularnewline
Winsorized Mean ( 18 / 32 ) & 20.469387755102 & 0.257928794679657 & 79.360614934539 \tabularnewline
Winsorized Mean ( 19 / 32 ) & 20.6632653061224 & 0.232958577052097 & 88.6993111290404 \tabularnewline
Winsorized Mean ( 20 / 32 ) & 20.4591836734694 & 0.204703974299041 & 99.9452196447424 \tabularnewline
Winsorized Mean ( 21 / 32 ) & 20.4591836734694 & 0.204703974299041 & 99.9452196447424 \tabularnewline
Winsorized Mean ( 22 / 32 ) & 20.4591836734694 & 0.204703974299041 & 99.9452196447424 \tabularnewline
Winsorized Mean ( 23 / 32 ) & 20.4591836734694 & 0.204703974299041 & 99.9452196447424 \tabularnewline
Winsorized Mean ( 24 / 32 ) & 20.4591836734694 & 0.204703974299041 & 99.9452196447424 \tabularnewline
Winsorized Mean ( 25 / 32 ) & 20.4591836734694 & 0.204703974299041 & 99.9452196447424 \tabularnewline
Winsorized Mean ( 26 / 32 ) & 20.1938775510204 & 0.173246475010541 & 116.561549375199 \tabularnewline
Winsorized Mean ( 27 / 32 ) & 20.1938775510204 & 0.173246475010541 & 116.561549375199 \tabularnewline
Winsorized Mean ( 28 / 32 ) & 20.1938775510204 & 0.173246475010541 & 116.561549375199 \tabularnewline
Winsorized Mean ( 29 / 32 ) & 20.4897959183673 & 0.137027518048538 & 149.53051919914 \tabularnewline
Winsorized Mean ( 30 / 32 ) & 20.4897959183673 & 0.137027518048538 & 149.53051919914 \tabularnewline
Winsorized Mean ( 31 / 32 ) & 20.4897959183673 & 0.137027518048538 & 149.53051919914 \tabularnewline
Winsorized Mean ( 32 / 32 ) & 20.4897959183673 & 0.137027518048538 & 149.53051919914 \tabularnewline
Trimmed Mean ( 1 / 32 ) & 20.2857142857143 & 0.335680810234439 & 60.4315577990496 \tabularnewline
Trimmed Mean ( 2 / 32 ) & 20.34375 & 0.312632707161883 & 65.0723661790956 \tabularnewline
Trimmed Mean ( 3 / 32 ) & 20.4130434782609 & 0.302936801436943 & 67.3838351148958 \tabularnewline
Trimmed Mean ( 4 / 32 ) & 20.4130434782609 & 0.297259410556933 & 68.670806552485 \tabularnewline
Trimmed Mean ( 5 / 32 ) & 20.4090909090909 & 0.290765377249769 & 70.1909254194298 \tabularnewline
Trimmed Mean ( 6 / 32 ) & 20.4186046511628 & 0.285761093465736 & 71.4534102719307 \tabularnewline
Trimmed Mean ( 7 / 32 ) & 20.4166666666667 & 0.282501901827652 & 72.2708998933481 \tabularnewline
Trimmed Mean ( 8 / 32 ) & 20.4166666666667 & 0.278698322648942 & 73.2572283629572 \tabularnewline
Trimmed Mean ( 9 / 32 ) & 20.4125 & 0.27426181130307 & 74.4270589587969 \tabularnewline
Trimmed Mean ( 10 / 32 ) & 20.4102564102564 & 0.269084050535107 & 75.8508591262398 \tabularnewline
Trimmed Mean ( 11 / 32 ) & 20.4078947368421 & 0.263030671001216 & 77.5875096967219 \tabularnewline
Trimmed Mean ( 12 / 32 ) & 20.4189189189189 & 0.258872013306078 & 78.87650216857 \tabularnewline
Trimmed Mean ( 13 / 32 ) & 20.4305555555556 & 0.253941071196469 & 80.4539236575434 \tabularnewline
Trimmed Mean ( 14 / 32 ) & 20.4428571428571 & 0.248086435786832 & 82.4021558374222 \tabularnewline
Trimmed Mean ( 15 / 32 ) & 20.4558823529412 & 0.24111409501961 & 84.8390151196988 \tabularnewline
Trimmed Mean ( 16 / 32 ) & 20.4558823529412 & 0.236704076148222 & 86.4196455160826 \tabularnewline
Trimmed Mean ( 17 / 32 ) & 20.453125 & 0.231379669243617 & 88.3963792793961 \tabularnewline
Trimmed Mean ( 18 / 32 ) & 20.4516129032258 & 0.224935996954657 & 90.9219208135391 \tabularnewline
Trimmed Mean ( 19 / 32 ) & 20.45 & 0.217100825336022 & 94.1958648399799 \tabularnewline
Trimmed Mean ( 20 / 32 ) & 20.4310344827586 & 0.211742502716042 & 96.4900018687211 \tabularnewline
Trimmed Mean ( 21 / 32 ) & 20.4285714285714 & 0.209912076301878 & 97.319657775157 \tabularnewline
Trimmed Mean ( 22 / 32 ) & 20.4259259259259 & 0.207480395463387 & 98.4474985229647 \tabularnewline
Trimmed Mean ( 23 / 32 ) & 20.4230769230769 & 0.204301690838457 & 99.9652858439906 \tabularnewline
Trimmed Mean ( 24 / 32 ) & 20.42 & 0.200183589206896 & 102.006363662984 \tabularnewline
Trimmed Mean ( 25 / 32 ) & 20.4166666666667 & 0.194866141848118 & 104.772776189 \tabularnewline
Trimmed Mean ( 26 / 32 ) & 20.4130434782609 & 0.187987272044534 & 108.587370071656 \tabularnewline
Trimmed Mean ( 27 / 32 ) & 20.4130434782609 & 0.18505963633017 & 110.305217729065 \tabularnewline
Trimmed Mean ( 28 / 32 ) & 20.452380952381 & 0.180984470533231 & 113.006275577802 \tabularnewline
Trimmed Mean ( 29 / 32 ) & 20.475 & 0.175365917806754 & 116.755868278594 \tabularnewline
Trimmed Mean ( 30 / 32 ) & 20.4736842105263 & 0.175841169220103 & 116.432825721826 \tabularnewline
Trimmed Mean ( 31 / 32 ) & 20.4722222222222 & 0.175870222314642 & 116.405278578634 \tabularnewline
Trimmed Mean ( 32 / 32 ) & 20.4722222222222 & 0.17527820574039 & 116.798446993143 \tabularnewline
Median & NA &  &  \tabularnewline
Midrange & NA &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 20.3898305084746 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 20.3898305084746 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 20.3898305084746 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 20.3898305084746 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 20.3898305084746 &  &  \tabularnewline
Midmean - Closest Observation & 20.3898305084746 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 20.3898305084746 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 20.3898305084746 &  &  \tabularnewline
Number of observations & 162 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148191&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]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NA[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]NA[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]NA[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 32 )[/C][C]20.2959183673469[/C][C]0.355359075171357[/C][C]57.1138315732055[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 32 )[/C][C]20.3571428571429[/C][C]0.328609845996368[/C][C]61.94927846857[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 32 )[/C][C]20.4183673469388[/C][C]0.316102484063055[/C][C]64.5941375862955[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 32 )[/C][C]20.4183673469388[/C][C]0.316102484063055[/C][C]64.5941375862955[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 32 )[/C][C]20.3673469387755[/C][C]0.307486965201089[/C][C]66.2380824027963[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 32 )[/C][C]20.4285714285714[/C][C]0.297262918986574[/C][C]68.7222324877127[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 32 )[/C][C]20.4285714285714[/C][C]0.297262918986574[/C][C]68.7222324877127[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 32 )[/C][C]20.4285714285714[/C][C]0.297262918986574[/C][C]68.7222324877127[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 32 )[/C][C]20.4285714285714[/C][C]0.297262918986574[/C][C]68.7222324877127[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 32 )[/C][C]20.4285714285714[/C][C]0.297262918986574[/C][C]68.7222324877127[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 32 )[/C][C]20.3163265306122[/C][C]0.280736062808066[/C][C]72.3680681683641[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 32 )[/C][C]20.3163265306122[/C][C]0.280736062808066[/C][C]72.3680681683641[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 32 )[/C][C]20.3163265306122[/C][C]0.280736062808066[/C][C]72.3680681683641[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 32 )[/C][C]20.3163265306122[/C][C]0.280736062808066[/C][C]72.3680681683641[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 32 )[/C][C]20.469387755102[/C][C]0.257928794679657[/C][C]79.360614934539[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 32 )[/C][C]20.469387755102[/C][C]0.257928794679657[/C][C]79.360614934539[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 32 )[/C][C]20.469387755102[/C][C]0.257928794679657[/C][C]79.360614934539[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 32 )[/C][C]20.469387755102[/C][C]0.257928794679657[/C][C]79.360614934539[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 32 )[/C][C]20.6632653061224[/C][C]0.232958577052097[/C][C]88.6993111290404[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 32 )[/C][C]20.4591836734694[/C][C]0.204703974299041[/C][C]99.9452196447424[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 32 )[/C][C]20.4591836734694[/C][C]0.204703974299041[/C][C]99.9452196447424[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 32 )[/C][C]20.4591836734694[/C][C]0.204703974299041[/C][C]99.9452196447424[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 32 )[/C][C]20.4591836734694[/C][C]0.204703974299041[/C][C]99.9452196447424[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 32 )[/C][C]20.4591836734694[/C][C]0.204703974299041[/C][C]99.9452196447424[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 32 )[/C][C]20.4591836734694[/C][C]0.204703974299041[/C][C]99.9452196447424[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 32 )[/C][C]20.1938775510204[/C][C]0.173246475010541[/C][C]116.561549375199[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 32 )[/C][C]20.1938775510204[/C][C]0.173246475010541[/C][C]116.561549375199[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 32 )[/C][C]20.1938775510204[/C][C]0.173246475010541[/C][C]116.561549375199[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 32 )[/C][C]20.4897959183673[/C][C]0.137027518048538[/C][C]149.53051919914[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 32 )[/C][C]20.4897959183673[/C][C]0.137027518048538[/C][C]149.53051919914[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 32 )[/C][C]20.4897959183673[/C][C]0.137027518048538[/C][C]149.53051919914[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 32 )[/C][C]20.4897959183673[/C][C]0.137027518048538[/C][C]149.53051919914[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 32 )[/C][C]20.2857142857143[/C][C]0.335680810234439[/C][C]60.4315577990496[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 32 )[/C][C]20.34375[/C][C]0.312632707161883[/C][C]65.0723661790956[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 32 )[/C][C]20.4130434782609[/C][C]0.302936801436943[/C][C]67.3838351148958[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 32 )[/C][C]20.4130434782609[/C][C]0.297259410556933[/C][C]68.670806552485[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 32 )[/C][C]20.4090909090909[/C][C]0.290765377249769[/C][C]70.1909254194298[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 32 )[/C][C]20.4186046511628[/C][C]0.285761093465736[/C][C]71.4534102719307[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 32 )[/C][C]20.4166666666667[/C][C]0.282501901827652[/C][C]72.2708998933481[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 32 )[/C][C]20.4166666666667[/C][C]0.278698322648942[/C][C]73.2572283629572[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 32 )[/C][C]20.4125[/C][C]0.27426181130307[/C][C]74.4270589587969[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 32 )[/C][C]20.4102564102564[/C][C]0.269084050535107[/C][C]75.8508591262398[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 32 )[/C][C]20.4078947368421[/C][C]0.263030671001216[/C][C]77.5875096967219[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 32 )[/C][C]20.4189189189189[/C][C]0.258872013306078[/C][C]78.87650216857[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 32 )[/C][C]20.4305555555556[/C][C]0.253941071196469[/C][C]80.4539236575434[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 32 )[/C][C]20.4428571428571[/C][C]0.248086435786832[/C][C]82.4021558374222[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 32 )[/C][C]20.4558823529412[/C][C]0.24111409501961[/C][C]84.8390151196988[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 32 )[/C][C]20.4558823529412[/C][C]0.236704076148222[/C][C]86.4196455160826[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 32 )[/C][C]20.453125[/C][C]0.231379669243617[/C][C]88.3963792793961[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 32 )[/C][C]20.4516129032258[/C][C]0.224935996954657[/C][C]90.9219208135391[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 32 )[/C][C]20.45[/C][C]0.217100825336022[/C][C]94.1958648399799[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 32 )[/C][C]20.4310344827586[/C][C]0.211742502716042[/C][C]96.4900018687211[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 32 )[/C][C]20.4285714285714[/C][C]0.209912076301878[/C][C]97.319657775157[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 32 )[/C][C]20.4259259259259[/C][C]0.207480395463387[/C][C]98.4474985229647[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 32 )[/C][C]20.4230769230769[/C][C]0.204301690838457[/C][C]99.9652858439906[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 32 )[/C][C]20.42[/C][C]0.200183589206896[/C][C]102.006363662984[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 32 )[/C][C]20.4166666666667[/C][C]0.194866141848118[/C][C]104.772776189[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 32 )[/C][C]20.4130434782609[/C][C]0.187987272044534[/C][C]108.587370071656[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 32 )[/C][C]20.4130434782609[/C][C]0.18505963633017[/C][C]110.305217729065[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 32 )[/C][C]20.452380952381[/C][C]0.180984470533231[/C][C]113.006275577802[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 32 )[/C][C]20.475[/C][C]0.175365917806754[/C][C]116.755868278594[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 32 )[/C][C]20.4736842105263[/C][C]0.175841169220103[/C][C]116.432825721826[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 32 )[/C][C]20.4722222222222[/C][C]0.175870222314642[/C][C]116.405278578634[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 32 )[/C][C]20.4722222222222[/C][C]0.17527820574039[/C][C]116.798446993143[/C][/ROW]
[ROW][C]Median[/C][C]NA[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]NA[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]20.3898305084746[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]20.3898305084746[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]20.3898305084746[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]20.3898305084746[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]20.3898305084746[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]20.3898305084746[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]20.3898305084746[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]20.3898305084746[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]162[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148191&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148191&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 MeanNANANA
Geometric MeanNA
Harmonic MeanNA
Quadratic MeanNA
Winsorized Mean ( 1 / 32 )20.29591836734690.35535907517135757.1138315732055
Winsorized Mean ( 2 / 32 )20.35714285714290.32860984599636861.94927846857
Winsorized Mean ( 3 / 32 )20.41836734693880.31610248406305564.5941375862955
Winsorized Mean ( 4 / 32 )20.41836734693880.31610248406305564.5941375862955
Winsorized Mean ( 5 / 32 )20.36734693877550.30748696520108966.2380824027963
Winsorized Mean ( 6 / 32 )20.42857142857140.29726291898657468.7222324877127
Winsorized Mean ( 7 / 32 )20.42857142857140.29726291898657468.7222324877127
Winsorized Mean ( 8 / 32 )20.42857142857140.29726291898657468.7222324877127
Winsorized Mean ( 9 / 32 )20.42857142857140.29726291898657468.7222324877127
Winsorized Mean ( 10 / 32 )20.42857142857140.29726291898657468.7222324877127
Winsorized Mean ( 11 / 32 )20.31632653061220.28073606280806672.3680681683641
Winsorized Mean ( 12 / 32 )20.31632653061220.28073606280806672.3680681683641
Winsorized Mean ( 13 / 32 )20.31632653061220.28073606280806672.3680681683641
Winsorized Mean ( 14 / 32 )20.31632653061220.28073606280806672.3680681683641
Winsorized Mean ( 15 / 32 )20.4693877551020.25792879467965779.360614934539
Winsorized Mean ( 16 / 32 )20.4693877551020.25792879467965779.360614934539
Winsorized Mean ( 17 / 32 )20.4693877551020.25792879467965779.360614934539
Winsorized Mean ( 18 / 32 )20.4693877551020.25792879467965779.360614934539
Winsorized Mean ( 19 / 32 )20.66326530612240.23295857705209788.6993111290404
Winsorized Mean ( 20 / 32 )20.45918367346940.20470397429904199.9452196447424
Winsorized Mean ( 21 / 32 )20.45918367346940.20470397429904199.9452196447424
Winsorized Mean ( 22 / 32 )20.45918367346940.20470397429904199.9452196447424
Winsorized Mean ( 23 / 32 )20.45918367346940.20470397429904199.9452196447424
Winsorized Mean ( 24 / 32 )20.45918367346940.20470397429904199.9452196447424
Winsorized Mean ( 25 / 32 )20.45918367346940.20470397429904199.9452196447424
Winsorized Mean ( 26 / 32 )20.19387755102040.173246475010541116.561549375199
Winsorized Mean ( 27 / 32 )20.19387755102040.173246475010541116.561549375199
Winsorized Mean ( 28 / 32 )20.19387755102040.173246475010541116.561549375199
Winsorized Mean ( 29 / 32 )20.48979591836730.137027518048538149.53051919914
Winsorized Mean ( 30 / 32 )20.48979591836730.137027518048538149.53051919914
Winsorized Mean ( 31 / 32 )20.48979591836730.137027518048538149.53051919914
Winsorized Mean ( 32 / 32 )20.48979591836730.137027518048538149.53051919914
Trimmed Mean ( 1 / 32 )20.28571428571430.33568081023443960.4315577990496
Trimmed Mean ( 2 / 32 )20.343750.31263270716188365.0723661790956
Trimmed Mean ( 3 / 32 )20.41304347826090.30293680143694367.3838351148958
Trimmed Mean ( 4 / 32 )20.41304347826090.29725941055693368.670806552485
Trimmed Mean ( 5 / 32 )20.40909090909090.29076537724976970.1909254194298
Trimmed Mean ( 6 / 32 )20.41860465116280.28576109346573671.4534102719307
Trimmed Mean ( 7 / 32 )20.41666666666670.28250190182765272.2708998933481
Trimmed Mean ( 8 / 32 )20.41666666666670.27869832264894273.2572283629572
Trimmed Mean ( 9 / 32 )20.41250.2742618113030774.4270589587969
Trimmed Mean ( 10 / 32 )20.41025641025640.26908405053510775.8508591262398
Trimmed Mean ( 11 / 32 )20.40789473684210.26303067100121677.5875096967219
Trimmed Mean ( 12 / 32 )20.41891891891890.25887201330607878.87650216857
Trimmed Mean ( 13 / 32 )20.43055555555560.25394107119646980.4539236575434
Trimmed Mean ( 14 / 32 )20.44285714285710.24808643578683282.4021558374222
Trimmed Mean ( 15 / 32 )20.45588235294120.2411140950196184.8390151196988
Trimmed Mean ( 16 / 32 )20.45588235294120.23670407614822286.4196455160826
Trimmed Mean ( 17 / 32 )20.4531250.23137966924361788.3963792793961
Trimmed Mean ( 18 / 32 )20.45161290322580.22493599695465790.9219208135391
Trimmed Mean ( 19 / 32 )20.450.21710082533602294.1958648399799
Trimmed Mean ( 20 / 32 )20.43103448275860.21174250271604296.4900018687211
Trimmed Mean ( 21 / 32 )20.42857142857140.20991207630187897.319657775157
Trimmed Mean ( 22 / 32 )20.42592592592590.20748039546338798.4474985229647
Trimmed Mean ( 23 / 32 )20.42307692307690.20430169083845799.9652858439906
Trimmed Mean ( 24 / 32 )20.420.200183589206896102.006363662984
Trimmed Mean ( 25 / 32 )20.41666666666670.194866141848118104.772776189
Trimmed Mean ( 26 / 32 )20.41304347826090.187987272044534108.587370071656
Trimmed Mean ( 27 / 32 )20.41304347826090.18505963633017110.305217729065
Trimmed Mean ( 28 / 32 )20.4523809523810.180984470533231113.006275577802
Trimmed Mean ( 29 / 32 )20.4750.175365917806754116.755868278594
Trimmed Mean ( 30 / 32 )20.47368421052630.175841169220103116.432825721826
Trimmed Mean ( 31 / 32 )20.47222222222220.175870222314642116.405278578634
Trimmed Mean ( 32 / 32 )20.47222222222220.17527820574039116.798446993143
MedianNA
MidrangeNA
Midmean - Weighted Average at Xnp20.3898305084746
Midmean - Weighted Average at X(n+1)p20.3898305084746
Midmean - Empirical Distribution Function20.3898305084746
Midmean - Empirical Distribution Function - Averaging20.3898305084746
Midmean - Empirical Distribution Function - Interpolation20.3898305084746
Midmean - Closest Observation20.3898305084746
Midmean - True Basic - Statistics Graphics Toolkit20.3898305084746
Midmean - MS Excel (old versions)20.3898305084746
Number of observations162



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')