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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 computationFri, 16 Dec 2011 09:37:31 -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/Dec/16/t1324046314ynvdbek4bivxriy.htm/, Retrieved Fri, 03 May 2024 07:40:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=155994, Retrieved Fri, 03 May 2024 07:40:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordscentral tendency
Estimated Impact71
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Linear Regression Graphical Model Validation] [Colombia Coffee -...] [2008-02-26 10:22:06] [74be16979710d4c4e7c6647856088456]
-  M D  [Linear Regression Graphical Model Validation] [mini-tutorial] [2011-11-15 09:10:29] [227e53f633d125e3e89f625705633e7f]
- RMPD      [Central Tendency] [Paper] [2011-12-16 14:37:31] [065e524ef27b3ebe8baf73e00eb8c266] [Current]
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Dataseries X:
83
79
92
83
92
103
82
86
106
79
86
76
108
82
108
118
127
123
72
105
63
86
58
59
100
100
78
94
105
89
101
92
105
76
80
66
117
94
107
110
110
106
94
71
101
84
89
119
97
82
89
70
101
81
74
107
97
83
95
82
88
74
104
73
73
81
79
83
111
138
81
107
66
81
74
96
86
69
73
71
64
79
60
111
107
90
98
77
93
68
74
70
80
81
72
81
92
81




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155994&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155994&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155994&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'Gertrude Mary Cox' @ cox.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean88.65306122448981.6467490585316753.8351977583868
Geometric Mean87.2018452545856
Harmonic Mean85.7822000840038
Quadratic Mean90.1244038164209
Winsorized Mean ( 1 / 32 )88.55102040816331.6136464677839854.8763450830531
Winsorized Mean ( 2 / 32 )88.48979591836731.5906737512606255.6303867139559
Winsorized Mean ( 3 / 32 )88.45918367346941.548240238657257.1353085036666
Winsorized Mean ( 4 / 32 )88.45918367346941.5332192539678857.695064449877
Winsorized Mean ( 5 / 32 )88.51020408163271.5069266328195558.7355762078642
Winsorized Mean ( 6 / 32 )88.14285714285711.4409624620954261.1694332513571
Winsorized Mean ( 7 / 32 )88.28571428571431.4191145009328362.2118329618091
Winsorized Mean ( 8 / 32 )88.28571428571431.3939848537033363.333338272055
Winsorized Mean ( 9 / 32 )88.37755102040821.3811355130133563.9890511739771
Winsorized Mean ( 10 / 32 )88.17346938775511.3491958245823765.3526106301495
Winsorized Mean ( 11 / 32 )88.28571428571431.3339030271817766.1860063937646
Winsorized Mean ( 12 / 32 )88.16326530612251.3155348707345167.0170493138642
Winsorized Mean ( 13 / 32 )88.29591836734691.2980272124096668.0231643244474
Winsorized Mean ( 14 / 32 )88.29591836734691.2980272124096668.0231643244474
Winsorized Mean ( 15 / 32 )88.44897959183671.2785862341051869.1771718109715
Winsorized Mean ( 16 / 32 )88.28571428571431.254489098885170.3758321727757
Winsorized Mean ( 17 / 32 )88.28571428571431.254489098885170.3758321727757
Winsorized Mean ( 18 / 32 )88.28571428571431.2052204280728373.2527529647707
Winsorized Mean ( 19 / 32 )88.28571428571431.2052204280728373.2527529647707
Winsorized Mean ( 20 / 32 )88.28571428571431.2052204280728373.2527529647707
Winsorized Mean ( 21 / 32 )88.07142857142861.1749229464732574.9593229375522
Winsorized Mean ( 22 / 32 )88.29591836734691.0897268291193781.0257359990857
Winsorized Mean ( 23 / 32 )87.82653061224491.0259647782018185.6038457442731
Winsorized Mean ( 24 / 32 )88.07142857142860.99739298296399288.3016324314847
Winsorized Mean ( 25 / 32 )88.32653061224490.96877132781111491.1737662713593
Winsorized Mean ( 26 / 32 )88.32653061224490.90452907103880397.6491894404307
Winsorized Mean ( 27 / 32 )88.32653061224490.90452907103880397.6491894404307
Winsorized Mean ( 28 / 32 )87.75510204081630.830091189707189105.717423734821
Winsorized Mean ( 29 / 32 )87.45918367346940.792900377935529110.302865413164
Winsorized Mean ( 30 / 32 )87.7653061224490.759926389240843115.491852059678
Winsorized Mean ( 31 / 32 )87.44897959183670.720754573531144121.32976023087
Winsorized Mean ( 32 / 32 )87.44897959183670.64691445038595135.178584339343
Trimmed Mean ( 1 / 32 )88.65306122448981.5672019895416856.5677314194937
Trimmed Mean ( 2 / 32 )88.45833333333331.5142766834801858.4162288823166
Trimmed Mean ( 3 / 32 )88.29347826086961.467968069835360.146729397715
Trimmed Mean ( 4 / 32 )88.29347826086961.4334204311138461.5963581545026
Trimmed Mean ( 5 / 32 )88.17045454545451.3990052435950163.0236769655584
Trimmed Mean ( 6 / 32 )88.09302325581391.36705700122264.4399049762143
Trimmed Mean ( 7 / 32 )88.08333333333331.3469125287512565.3964763509899
Trimmed Mean ( 8 / 32 )88.08333333333331.3283446011525566.310604384515
Trimmed Mean ( 9 / 32 )88.01251.3117644111093967.0947460188875
Trimmed Mean ( 10 / 32 )87.96153846153851.2946574699894667.9419386984688
Trimmed Mean ( 11 / 32 )87.93421052631581.2802597771362368.6846623604882
Trimmed Mean ( 12 / 32 )87.89189189189191.2656378465698569.4447405552053
Trimmed Mean ( 13 / 32 )87.86111111111111.251181844357970.2224952410501
Trimmed Mean ( 14 / 32 )87.81428571428571.2364868514491271.0191827849768
Trimmed Mean ( 15 / 32 )87.76470588235291.2186575695228872.0175282025401
Trimmed Mean ( 16 / 32 )87.76470588235291.2000329632165973.1352459245011
Trimmed Mean ( 17 / 32 )87.6406251.1813210563788574.1886589820451
Trimmed Mean ( 18 / 32 )87.58064516129031.1584076095648875.6043420624518
Trimmed Mean ( 19 / 32 )87.51666666666671.1383136666870376.8827338438065
Trimmed Mean ( 20 / 32 )87.4482758620691.1134041188522978.5413619200648
Trimmed Mean ( 21 / 32 )87.3751.0824942638041280.7163630529967
Trimmed Mean ( 22 / 32 )87.31481481481481.0497159690626683.1794670064727
Trimmed Mean ( 23 / 32 )87.23076923076921.0237066978285485.2107048003109
Trimmed Mean ( 24 / 32 )87.181.0027268942687286.9429158610326
Trimmed Mean ( 25 / 32 )87.10416666666670.98041078348492488.8445620284287
Trimmed Mean ( 26 / 32 )870.95603852528846891.0005169234673
Trimmed Mean ( 27 / 32 )870.93624226927481792.9246658211526
Trimmed Mean ( 28 / 32 )86.76190476190480.90924374378337295.4220530579486
Trimmed Mean ( 29 / 32 )86.6750.89039569135271997.3443614358919
Trimmed Mean ( 30 / 32 )86.60526315789470.87280671970563799.2261645133796
Trimmed Mean ( 31 / 32 )86.50.85402873450785101.284648285104
Trimmed Mean ( 32 / 32 )86.50.837104813575074103.332340941368
Median86
Midrange98
Midmean - Weighted Average at Xnp87.4509803921569
Midmean - Weighted Average at X(n+1)p87.4509803921569
Midmean - Empirical Distribution Function87.4509803921569
Midmean - Empirical Distribution Function - Averaging87.4509803921569
Midmean - Empirical Distribution Function - Interpolation87.66
Midmean - Closest Observation87.4509803921569
Midmean - True Basic - Statistics Graphics Toolkit87.4509803921569
Midmean - MS Excel (old versions)87.4509803921569
Number of observations98

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 88.6530612244898 & 1.64674905853167 & 53.8351977583868 \tabularnewline
Geometric Mean & 87.2018452545856 &  &  \tabularnewline
Harmonic Mean & 85.7822000840038 &  &  \tabularnewline
Quadratic Mean & 90.1244038164209 &  &  \tabularnewline
Winsorized Mean ( 1 / 32 ) & 88.5510204081633 & 1.61364646778398 & 54.8763450830531 \tabularnewline
Winsorized Mean ( 2 / 32 ) & 88.4897959183673 & 1.59067375126062 & 55.6303867139559 \tabularnewline
Winsorized Mean ( 3 / 32 ) & 88.4591836734694 & 1.5482402386572 & 57.1353085036666 \tabularnewline
Winsorized Mean ( 4 / 32 ) & 88.4591836734694 & 1.53321925396788 & 57.695064449877 \tabularnewline
Winsorized Mean ( 5 / 32 ) & 88.5102040816327 & 1.50692663281955 & 58.7355762078642 \tabularnewline
Winsorized Mean ( 6 / 32 ) & 88.1428571428571 & 1.44096246209542 & 61.1694332513571 \tabularnewline
Winsorized Mean ( 7 / 32 ) & 88.2857142857143 & 1.41911450093283 & 62.2118329618091 \tabularnewline
Winsorized Mean ( 8 / 32 ) & 88.2857142857143 & 1.39398485370333 & 63.333338272055 \tabularnewline
Winsorized Mean ( 9 / 32 ) & 88.3775510204082 & 1.38113551301335 & 63.9890511739771 \tabularnewline
Winsorized Mean ( 10 / 32 ) & 88.1734693877551 & 1.34919582458237 & 65.3526106301495 \tabularnewline
Winsorized Mean ( 11 / 32 ) & 88.2857142857143 & 1.33390302718177 & 66.1860063937646 \tabularnewline
Winsorized Mean ( 12 / 32 ) & 88.1632653061225 & 1.31553487073451 & 67.0170493138642 \tabularnewline
Winsorized Mean ( 13 / 32 ) & 88.2959183673469 & 1.29802721240966 & 68.0231643244474 \tabularnewline
Winsorized Mean ( 14 / 32 ) & 88.2959183673469 & 1.29802721240966 & 68.0231643244474 \tabularnewline
Winsorized Mean ( 15 / 32 ) & 88.4489795918367 & 1.27858623410518 & 69.1771718109715 \tabularnewline
Winsorized Mean ( 16 / 32 ) & 88.2857142857143 & 1.2544890988851 & 70.3758321727757 \tabularnewline
Winsorized Mean ( 17 / 32 ) & 88.2857142857143 & 1.2544890988851 & 70.3758321727757 \tabularnewline
Winsorized Mean ( 18 / 32 ) & 88.2857142857143 & 1.20522042807283 & 73.2527529647707 \tabularnewline
Winsorized Mean ( 19 / 32 ) & 88.2857142857143 & 1.20522042807283 & 73.2527529647707 \tabularnewline
Winsorized Mean ( 20 / 32 ) & 88.2857142857143 & 1.20522042807283 & 73.2527529647707 \tabularnewline
Winsorized Mean ( 21 / 32 ) & 88.0714285714286 & 1.17492294647325 & 74.9593229375522 \tabularnewline
Winsorized Mean ( 22 / 32 ) & 88.2959183673469 & 1.08972682911937 & 81.0257359990857 \tabularnewline
Winsorized Mean ( 23 / 32 ) & 87.8265306122449 & 1.02596477820181 & 85.6038457442731 \tabularnewline
Winsorized Mean ( 24 / 32 ) & 88.0714285714286 & 0.997392982963992 & 88.3016324314847 \tabularnewline
Winsorized Mean ( 25 / 32 ) & 88.3265306122449 & 0.968771327811114 & 91.1737662713593 \tabularnewline
Winsorized Mean ( 26 / 32 ) & 88.3265306122449 & 0.904529071038803 & 97.6491894404307 \tabularnewline
Winsorized Mean ( 27 / 32 ) & 88.3265306122449 & 0.904529071038803 & 97.6491894404307 \tabularnewline
Winsorized Mean ( 28 / 32 ) & 87.7551020408163 & 0.830091189707189 & 105.717423734821 \tabularnewline
Winsorized Mean ( 29 / 32 ) & 87.4591836734694 & 0.792900377935529 & 110.302865413164 \tabularnewline
Winsorized Mean ( 30 / 32 ) & 87.765306122449 & 0.759926389240843 & 115.491852059678 \tabularnewline
Winsorized Mean ( 31 / 32 ) & 87.4489795918367 & 0.720754573531144 & 121.32976023087 \tabularnewline
Winsorized Mean ( 32 / 32 ) & 87.4489795918367 & 0.64691445038595 & 135.178584339343 \tabularnewline
Trimmed Mean ( 1 / 32 ) & 88.6530612244898 & 1.56720198954168 & 56.5677314194937 \tabularnewline
Trimmed Mean ( 2 / 32 ) & 88.4583333333333 & 1.51427668348018 & 58.4162288823166 \tabularnewline
Trimmed Mean ( 3 / 32 ) & 88.2934782608696 & 1.4679680698353 & 60.146729397715 \tabularnewline
Trimmed Mean ( 4 / 32 ) & 88.2934782608696 & 1.43342043111384 & 61.5963581545026 \tabularnewline
Trimmed Mean ( 5 / 32 ) & 88.1704545454545 & 1.39900524359501 & 63.0236769655584 \tabularnewline
Trimmed Mean ( 6 / 32 ) & 88.0930232558139 & 1.367057001222 & 64.4399049762143 \tabularnewline
Trimmed Mean ( 7 / 32 ) & 88.0833333333333 & 1.34691252875125 & 65.3964763509899 \tabularnewline
Trimmed Mean ( 8 / 32 ) & 88.0833333333333 & 1.32834460115255 & 66.310604384515 \tabularnewline
Trimmed Mean ( 9 / 32 ) & 88.0125 & 1.31176441110939 & 67.0947460188875 \tabularnewline
Trimmed Mean ( 10 / 32 ) & 87.9615384615385 & 1.29465746998946 & 67.9419386984688 \tabularnewline
Trimmed Mean ( 11 / 32 ) & 87.9342105263158 & 1.28025977713623 & 68.6846623604882 \tabularnewline
Trimmed Mean ( 12 / 32 ) & 87.8918918918919 & 1.26563784656985 & 69.4447405552053 \tabularnewline
Trimmed Mean ( 13 / 32 ) & 87.8611111111111 & 1.2511818443579 & 70.2224952410501 \tabularnewline
Trimmed Mean ( 14 / 32 ) & 87.8142857142857 & 1.23648685144912 & 71.0191827849768 \tabularnewline
Trimmed Mean ( 15 / 32 ) & 87.7647058823529 & 1.21865756952288 & 72.0175282025401 \tabularnewline
Trimmed Mean ( 16 / 32 ) & 87.7647058823529 & 1.20003296321659 & 73.1352459245011 \tabularnewline
Trimmed Mean ( 17 / 32 ) & 87.640625 & 1.18132105637885 & 74.1886589820451 \tabularnewline
Trimmed Mean ( 18 / 32 ) & 87.5806451612903 & 1.15840760956488 & 75.6043420624518 \tabularnewline
Trimmed Mean ( 19 / 32 ) & 87.5166666666667 & 1.13831366668703 & 76.8827338438065 \tabularnewline
Trimmed Mean ( 20 / 32 ) & 87.448275862069 & 1.11340411885229 & 78.5413619200648 \tabularnewline
Trimmed Mean ( 21 / 32 ) & 87.375 & 1.08249426380412 & 80.7163630529967 \tabularnewline
Trimmed Mean ( 22 / 32 ) & 87.3148148148148 & 1.04971596906266 & 83.1794670064727 \tabularnewline
Trimmed Mean ( 23 / 32 ) & 87.2307692307692 & 1.02370669782854 & 85.2107048003109 \tabularnewline
Trimmed Mean ( 24 / 32 ) & 87.18 & 1.00272689426872 & 86.9429158610326 \tabularnewline
Trimmed Mean ( 25 / 32 ) & 87.1041666666667 & 0.980410783484924 & 88.8445620284287 \tabularnewline
Trimmed Mean ( 26 / 32 ) & 87 & 0.956038525288468 & 91.0005169234673 \tabularnewline
Trimmed Mean ( 27 / 32 ) & 87 & 0.936242269274817 & 92.9246658211526 \tabularnewline
Trimmed Mean ( 28 / 32 ) & 86.7619047619048 & 0.909243743783372 & 95.4220530579486 \tabularnewline
Trimmed Mean ( 29 / 32 ) & 86.675 & 0.890395691352719 & 97.3443614358919 \tabularnewline
Trimmed Mean ( 30 / 32 ) & 86.6052631578947 & 0.872806719705637 & 99.2261645133796 \tabularnewline
Trimmed Mean ( 31 / 32 ) & 86.5 & 0.85402873450785 & 101.284648285104 \tabularnewline
Trimmed Mean ( 32 / 32 ) & 86.5 & 0.837104813575074 & 103.332340941368 \tabularnewline
Median & 86 &  &  \tabularnewline
Midrange & 98 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 87.4509803921569 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 87.4509803921569 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 87.4509803921569 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 87.4509803921569 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 87.66 &  &  \tabularnewline
Midmean - Closest Observation & 87.4509803921569 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 87.4509803921569 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 87.4509803921569 &  &  \tabularnewline
Number of observations & 98 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155994&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]88.6530612244898[/C][C]1.64674905853167[/C][C]53.8351977583868[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]87.2018452545856[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]85.7822000840038[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]90.1244038164209[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 32 )[/C][C]88.5510204081633[/C][C]1.61364646778398[/C][C]54.8763450830531[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 32 )[/C][C]88.4897959183673[/C][C]1.59067375126062[/C][C]55.6303867139559[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 32 )[/C][C]88.4591836734694[/C][C]1.5482402386572[/C][C]57.1353085036666[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 32 )[/C][C]88.4591836734694[/C][C]1.53321925396788[/C][C]57.695064449877[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 32 )[/C][C]88.5102040816327[/C][C]1.50692663281955[/C][C]58.7355762078642[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 32 )[/C][C]88.1428571428571[/C][C]1.44096246209542[/C][C]61.1694332513571[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 32 )[/C][C]88.2857142857143[/C][C]1.41911450093283[/C][C]62.2118329618091[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 32 )[/C][C]88.2857142857143[/C][C]1.39398485370333[/C][C]63.333338272055[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 32 )[/C][C]88.3775510204082[/C][C]1.38113551301335[/C][C]63.9890511739771[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 32 )[/C][C]88.1734693877551[/C][C]1.34919582458237[/C][C]65.3526106301495[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 32 )[/C][C]88.2857142857143[/C][C]1.33390302718177[/C][C]66.1860063937646[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 32 )[/C][C]88.1632653061225[/C][C]1.31553487073451[/C][C]67.0170493138642[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 32 )[/C][C]88.2959183673469[/C][C]1.29802721240966[/C][C]68.0231643244474[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 32 )[/C][C]88.2959183673469[/C][C]1.29802721240966[/C][C]68.0231643244474[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 32 )[/C][C]88.4489795918367[/C][C]1.27858623410518[/C][C]69.1771718109715[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 32 )[/C][C]88.2857142857143[/C][C]1.2544890988851[/C][C]70.3758321727757[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 32 )[/C][C]88.2857142857143[/C][C]1.2544890988851[/C][C]70.3758321727757[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 32 )[/C][C]88.2857142857143[/C][C]1.20522042807283[/C][C]73.2527529647707[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 32 )[/C][C]88.2857142857143[/C][C]1.20522042807283[/C][C]73.2527529647707[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 32 )[/C][C]88.2857142857143[/C][C]1.20522042807283[/C][C]73.2527529647707[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 32 )[/C][C]88.0714285714286[/C][C]1.17492294647325[/C][C]74.9593229375522[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 32 )[/C][C]88.2959183673469[/C][C]1.08972682911937[/C][C]81.0257359990857[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 32 )[/C][C]87.8265306122449[/C][C]1.02596477820181[/C][C]85.6038457442731[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 32 )[/C][C]88.0714285714286[/C][C]0.997392982963992[/C][C]88.3016324314847[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 32 )[/C][C]88.3265306122449[/C][C]0.968771327811114[/C][C]91.1737662713593[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 32 )[/C][C]88.3265306122449[/C][C]0.904529071038803[/C][C]97.6491894404307[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 32 )[/C][C]88.3265306122449[/C][C]0.904529071038803[/C][C]97.6491894404307[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 32 )[/C][C]87.7551020408163[/C][C]0.830091189707189[/C][C]105.717423734821[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 32 )[/C][C]87.4591836734694[/C][C]0.792900377935529[/C][C]110.302865413164[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 32 )[/C][C]87.765306122449[/C][C]0.759926389240843[/C][C]115.491852059678[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 32 )[/C][C]87.4489795918367[/C][C]0.720754573531144[/C][C]121.32976023087[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 32 )[/C][C]87.4489795918367[/C][C]0.64691445038595[/C][C]135.178584339343[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 32 )[/C][C]88.6530612244898[/C][C]1.56720198954168[/C][C]56.5677314194937[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 32 )[/C][C]88.4583333333333[/C][C]1.51427668348018[/C][C]58.4162288823166[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 32 )[/C][C]88.2934782608696[/C][C]1.4679680698353[/C][C]60.146729397715[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 32 )[/C][C]88.2934782608696[/C][C]1.43342043111384[/C][C]61.5963581545026[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 32 )[/C][C]88.1704545454545[/C][C]1.39900524359501[/C][C]63.0236769655584[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 32 )[/C][C]88.0930232558139[/C][C]1.367057001222[/C][C]64.4399049762143[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 32 )[/C][C]88.0833333333333[/C][C]1.34691252875125[/C][C]65.3964763509899[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 32 )[/C][C]88.0833333333333[/C][C]1.32834460115255[/C][C]66.310604384515[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 32 )[/C][C]88.0125[/C][C]1.31176441110939[/C][C]67.0947460188875[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 32 )[/C][C]87.9615384615385[/C][C]1.29465746998946[/C][C]67.9419386984688[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 32 )[/C][C]87.9342105263158[/C][C]1.28025977713623[/C][C]68.6846623604882[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 32 )[/C][C]87.8918918918919[/C][C]1.26563784656985[/C][C]69.4447405552053[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 32 )[/C][C]87.8611111111111[/C][C]1.2511818443579[/C][C]70.2224952410501[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 32 )[/C][C]87.8142857142857[/C][C]1.23648685144912[/C][C]71.0191827849768[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 32 )[/C][C]87.7647058823529[/C][C]1.21865756952288[/C][C]72.0175282025401[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 32 )[/C][C]87.7647058823529[/C][C]1.20003296321659[/C][C]73.1352459245011[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 32 )[/C][C]87.640625[/C][C]1.18132105637885[/C][C]74.1886589820451[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 32 )[/C][C]87.5806451612903[/C][C]1.15840760956488[/C][C]75.6043420624518[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 32 )[/C][C]87.5166666666667[/C][C]1.13831366668703[/C][C]76.8827338438065[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 32 )[/C][C]87.448275862069[/C][C]1.11340411885229[/C][C]78.5413619200648[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 32 )[/C][C]87.375[/C][C]1.08249426380412[/C][C]80.7163630529967[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 32 )[/C][C]87.3148148148148[/C][C]1.04971596906266[/C][C]83.1794670064727[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 32 )[/C][C]87.2307692307692[/C][C]1.02370669782854[/C][C]85.2107048003109[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 32 )[/C][C]87.18[/C][C]1.00272689426872[/C][C]86.9429158610326[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 32 )[/C][C]87.1041666666667[/C][C]0.980410783484924[/C][C]88.8445620284287[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 32 )[/C][C]87[/C][C]0.956038525288468[/C][C]91.0005169234673[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 32 )[/C][C]87[/C][C]0.936242269274817[/C][C]92.9246658211526[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 32 )[/C][C]86.7619047619048[/C][C]0.909243743783372[/C][C]95.4220530579486[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 32 )[/C][C]86.675[/C][C]0.890395691352719[/C][C]97.3443614358919[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 32 )[/C][C]86.6052631578947[/C][C]0.872806719705637[/C][C]99.2261645133796[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 32 )[/C][C]86.5[/C][C]0.85402873450785[/C][C]101.284648285104[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 32 )[/C][C]86.5[/C][C]0.837104813575074[/C][C]103.332340941368[/C][/ROW]
[ROW][C]Median[/C][C]86[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]98[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]87.4509803921569[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]87.4509803921569[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]87.4509803921569[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]87.4509803921569[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]87.66[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]87.4509803921569[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]87.4509803921569[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]87.4509803921569[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]98[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155994&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155994&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 Mean88.65306122448981.6467490585316753.8351977583868
Geometric Mean87.2018452545856
Harmonic Mean85.7822000840038
Quadratic Mean90.1244038164209
Winsorized Mean ( 1 / 32 )88.55102040816331.6136464677839854.8763450830531
Winsorized Mean ( 2 / 32 )88.48979591836731.5906737512606255.6303867139559
Winsorized Mean ( 3 / 32 )88.45918367346941.548240238657257.1353085036666
Winsorized Mean ( 4 / 32 )88.45918367346941.5332192539678857.695064449877
Winsorized Mean ( 5 / 32 )88.51020408163271.5069266328195558.7355762078642
Winsorized Mean ( 6 / 32 )88.14285714285711.4409624620954261.1694332513571
Winsorized Mean ( 7 / 32 )88.28571428571431.4191145009328362.2118329618091
Winsorized Mean ( 8 / 32 )88.28571428571431.3939848537033363.333338272055
Winsorized Mean ( 9 / 32 )88.37755102040821.3811355130133563.9890511739771
Winsorized Mean ( 10 / 32 )88.17346938775511.3491958245823765.3526106301495
Winsorized Mean ( 11 / 32 )88.28571428571431.3339030271817766.1860063937646
Winsorized Mean ( 12 / 32 )88.16326530612251.3155348707345167.0170493138642
Winsorized Mean ( 13 / 32 )88.29591836734691.2980272124096668.0231643244474
Winsorized Mean ( 14 / 32 )88.29591836734691.2980272124096668.0231643244474
Winsorized Mean ( 15 / 32 )88.44897959183671.2785862341051869.1771718109715
Winsorized Mean ( 16 / 32 )88.28571428571431.254489098885170.3758321727757
Winsorized Mean ( 17 / 32 )88.28571428571431.254489098885170.3758321727757
Winsorized Mean ( 18 / 32 )88.28571428571431.2052204280728373.2527529647707
Winsorized Mean ( 19 / 32 )88.28571428571431.2052204280728373.2527529647707
Winsorized Mean ( 20 / 32 )88.28571428571431.2052204280728373.2527529647707
Winsorized Mean ( 21 / 32 )88.07142857142861.1749229464732574.9593229375522
Winsorized Mean ( 22 / 32 )88.29591836734691.0897268291193781.0257359990857
Winsorized Mean ( 23 / 32 )87.82653061224491.0259647782018185.6038457442731
Winsorized Mean ( 24 / 32 )88.07142857142860.99739298296399288.3016324314847
Winsorized Mean ( 25 / 32 )88.32653061224490.96877132781111491.1737662713593
Winsorized Mean ( 26 / 32 )88.32653061224490.90452907103880397.6491894404307
Winsorized Mean ( 27 / 32 )88.32653061224490.90452907103880397.6491894404307
Winsorized Mean ( 28 / 32 )87.75510204081630.830091189707189105.717423734821
Winsorized Mean ( 29 / 32 )87.45918367346940.792900377935529110.302865413164
Winsorized Mean ( 30 / 32 )87.7653061224490.759926389240843115.491852059678
Winsorized Mean ( 31 / 32 )87.44897959183670.720754573531144121.32976023087
Winsorized Mean ( 32 / 32 )87.44897959183670.64691445038595135.178584339343
Trimmed Mean ( 1 / 32 )88.65306122448981.5672019895416856.5677314194937
Trimmed Mean ( 2 / 32 )88.45833333333331.5142766834801858.4162288823166
Trimmed Mean ( 3 / 32 )88.29347826086961.467968069835360.146729397715
Trimmed Mean ( 4 / 32 )88.29347826086961.4334204311138461.5963581545026
Trimmed Mean ( 5 / 32 )88.17045454545451.3990052435950163.0236769655584
Trimmed Mean ( 6 / 32 )88.09302325581391.36705700122264.4399049762143
Trimmed Mean ( 7 / 32 )88.08333333333331.3469125287512565.3964763509899
Trimmed Mean ( 8 / 32 )88.08333333333331.3283446011525566.310604384515
Trimmed Mean ( 9 / 32 )88.01251.3117644111093967.0947460188875
Trimmed Mean ( 10 / 32 )87.96153846153851.2946574699894667.9419386984688
Trimmed Mean ( 11 / 32 )87.93421052631581.2802597771362368.6846623604882
Trimmed Mean ( 12 / 32 )87.89189189189191.2656378465698569.4447405552053
Trimmed Mean ( 13 / 32 )87.86111111111111.251181844357970.2224952410501
Trimmed Mean ( 14 / 32 )87.81428571428571.2364868514491271.0191827849768
Trimmed Mean ( 15 / 32 )87.76470588235291.2186575695228872.0175282025401
Trimmed Mean ( 16 / 32 )87.76470588235291.2000329632165973.1352459245011
Trimmed Mean ( 17 / 32 )87.6406251.1813210563788574.1886589820451
Trimmed Mean ( 18 / 32 )87.58064516129031.1584076095648875.6043420624518
Trimmed Mean ( 19 / 32 )87.51666666666671.1383136666870376.8827338438065
Trimmed Mean ( 20 / 32 )87.4482758620691.1134041188522978.5413619200648
Trimmed Mean ( 21 / 32 )87.3751.0824942638041280.7163630529967
Trimmed Mean ( 22 / 32 )87.31481481481481.0497159690626683.1794670064727
Trimmed Mean ( 23 / 32 )87.23076923076921.0237066978285485.2107048003109
Trimmed Mean ( 24 / 32 )87.181.0027268942687286.9429158610326
Trimmed Mean ( 25 / 32 )87.10416666666670.98041078348492488.8445620284287
Trimmed Mean ( 26 / 32 )870.95603852528846891.0005169234673
Trimmed Mean ( 27 / 32 )870.93624226927481792.9246658211526
Trimmed Mean ( 28 / 32 )86.76190476190480.90924374378337295.4220530579486
Trimmed Mean ( 29 / 32 )86.6750.89039569135271997.3443614358919
Trimmed Mean ( 30 / 32 )86.60526315789470.87280671970563799.2261645133796
Trimmed Mean ( 31 / 32 )86.50.85402873450785101.284648285104
Trimmed Mean ( 32 / 32 )86.50.837104813575074103.332340941368
Median86
Midrange98
Midmean - Weighted Average at Xnp87.4509803921569
Midmean - Weighted Average at X(n+1)p87.4509803921569
Midmean - Empirical Distribution Function87.4509803921569
Midmean - Empirical Distribution Function - Averaging87.4509803921569
Midmean - Empirical Distribution Function - Interpolation87.66
Midmean - Closest Observation87.4509803921569
Midmean - True Basic - Statistics Graphics Toolkit87.4509803921569
Midmean - MS Excel (old versions)87.4509803921569
Number of observations98



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')