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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 28 Nov 2011 11:37:35 -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/28/t1322498302fwp7r6v3wnexeiq.htm/, Retrieved Wed, 24 Apr 2024 18:10:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147853, Retrieved Wed, 24 Apr 2024 18:10:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact97
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- R PD        [Univariate Data Series] [] [2011-11-28 16:15:31] [86a47bcc75cd2e0d5b5c9888edc893c2]
- RMP             [Central Tendency] [] [2011-11-28 16:37:35] [d34c5d8ebaf8c35edbecb57bc39ed04e] [Current]
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Dataseries X:
9 676
8 642
9 402
9 610
9 294
9 448
10 319
9 548
9 801
9 596
8 923
9 746
9 829
9 125
9 782
9 441
9 162
9 915
10 444
10 209
9 985
9 842
9 429
10 132
9 849
9 172
10 313
9 819
9 955
10 048
10 082
10 541
10 208
10 233
9 439
9 963
10 158
9 225
10 474
9 757
10 490
10 281
10 444
10 640
10 695
10 786
9 832
9 747
10 411
9 511
10 402
9 701
10 540
10 112
10 915
11 183
10 384
10 834
9 886
10 216
10 943
9 867
10 203
10 837
10 573
10 647
11 502
10 656
10 866
10 835
9 945
10 331




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147853&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147853&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147853&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean10065.986111111166.3204168336484151.778088734871
Geometric Mean10050.4048080184
Harmonic Mean10034.7470408289
Quadratic Mean10081.4861317665
Winsorized Mean ( 1 / 24 )10065.458333333364.0154364988088157.234862149548
Winsorized Mean ( 2 / 24 )10064.402777777861.2047081423959164.438375465535
Winsorized Mean ( 3 / 24 )10064.777777777860.6432854334432165.966894864626
Winsorized Mean ( 4 / 24 )10062.611111111160.0014493681085167.706134053147
Winsorized Mean ( 5 / 24 )10064.277777777858.8709837840242170.954808818889
Winsorized Mean ( 6 / 24 )10069.861111111157.7181013853163174.466257021977
Winsorized Mean ( 7 / 24 )10080.263888888955.8054901952956180.632117980009
Winsorized Mean ( 8 / 24 )10077.930555555654.2988683800215185.60111575481
Winsorized Mean ( 9 / 24 )10067.805555555652.0763615573815193.327745150976
Winsorized Mean ( 10 / 24 )10062.666666666751.1267029017984196.818220138203
Winsorized Mean ( 11 / 24 )10062.361111111150.7199084973493198.390758367338
Winsorized Mean ( 12 / 24 )10071.694444444448.7830728826945206.458795014066
Winsorized Mean ( 13 / 24 )10066.277777777845.7722436336082219.921004055537
Winsorized Mean ( 14 / 24 )10069.388888888943.3474361104957232.294912742274
Winsorized Mean ( 15 / 24 )10072.097222222242.8697309766125234.946592683706
Winsorized Mean ( 16 / 24 )10075.652777777839.0093893422511258.287887805125
Winsorized Mean ( 17 / 24 )10077.777777777837.6038947961885267.998244128671
Winsorized Mean ( 18 / 24 )10081.527777777834.9434372607887288.509905380448
Winsorized Mean ( 19 / 24 )10081.791666666734.90776992609288.812252630654
Winsorized Mean ( 20 / 24 )10075.402777777833.2100104855214303.384510588166
Winsorized Mean ( 21 / 24 )10080.069444444431.8635117772862316.351490535641
Winsorized Mean ( 22 / 24 )10080.37530.3250416716373332.410919963485
Winsorized Mean ( 23 / 24 )10069.194444444427.2376347653226369.679472215552
Winsorized Mean ( 24 / 24 )10068.527777777826.268543433332383.292199026227
Trimmed Mean ( 1 / 24 )10065.814285714361.7125081457444163.108170258486
Trimmed Mean ( 2 / 24 )10066.191176470658.9649464228694170.714836307668
Trimmed Mean ( 3 / 24 )10067.166666666757.5042294312897175.068282215583
Trimmed Mean ( 4 / 24 )10068.062556.0074128588251179.763034678606
Trimmed Mean ( 5 / 24 )10069.645161290354.4379293572944184.974801212586
Trimmed Mean ( 6 / 24 )10070.933333333352.8978167859093190.384668881382
Trimmed Mean ( 7 / 24 )10071.155172413851.3523338418098196.118743179966
Trimmed Mean ( 8 / 24 )10069.482142857149.9619010111083201.543214711112
Trimmed Mean ( 9 / 24 )10068.074074074148.6165982061719207.091290743496
Trimmed Mean ( 10 / 24 )10068.115384615447.469039317222212.098570551071
Trimmed Mean ( 11 / 24 )10068.946.2330586732666217.78572062813
Trimmed Mean ( 12 / 24 )10069.791666666744.7466762339221225.039992110807
Trimmed Mean ( 13 / 24 )10069.543478260943.2927424887234232.591951893177
Trimmed Mean ( 14 / 24 )10069.954545454542.10526116164239.16143179344
Trimmed Mean ( 15 / 24 )10070.023809523841.0922376546332245.059027793985
Trimmed Mean ( 16 / 24 )10069.77539.8331373372498252.79894261764
Trimmed Mean ( 17 / 24 )10069.078947368439.0458092851161257.878608017652
Trimmed Mean ( 18 / 24 )10068.055555555638.2563604929401263.173376291598
Trimmed Mean ( 19 / 24 )10066.470588235337.7501457374415266.660443068201
Trimmed Mean ( 20 / 24 )10064.6562536.9480511887047272.400192329409
Trimmed Mean ( 21 / 24 )10063.366666666736.1920319970657278.054757121196
Trimmed Mean ( 22 / 24 )10061.321428571435.3670120104703284.483219153283
Trimmed Mean ( 23 / 24 )10058.923076923134.4982908418072291.57743272119
Trimmed Mean ( 24 / 24 )10057.583333333334.1021970405892294.924790955919
Median10065
Midrange10072
Midmean - Weighted Average at Xnp10058.1351351351
Midmean - Weighted Average at X(n+1)p10068.0555555556
Midmean - Empirical Distribution Function10058.1351351351
Midmean - Empirical Distribution Function - Averaging10068.0555555556
Midmean - Empirical Distribution Function - Interpolation10068.0555555556
Midmean - Closest Observation10058.1351351351
Midmean - True Basic - Statistics Graphics Toolkit10068.0555555556
Midmean - MS Excel (old versions)10069.0789473684
Number of observations72

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 10065.9861111111 & 66.3204168336484 & 151.778088734871 \tabularnewline
Geometric Mean & 10050.4048080184 &  &  \tabularnewline
Harmonic Mean & 10034.7470408289 &  &  \tabularnewline
Quadratic Mean & 10081.4861317665 &  &  \tabularnewline
Winsorized Mean ( 1 / 24 ) & 10065.4583333333 & 64.0154364988088 & 157.234862149548 \tabularnewline
Winsorized Mean ( 2 / 24 ) & 10064.4027777778 & 61.2047081423959 & 164.438375465535 \tabularnewline
Winsorized Mean ( 3 / 24 ) & 10064.7777777778 & 60.6432854334432 & 165.966894864626 \tabularnewline
Winsorized Mean ( 4 / 24 ) & 10062.6111111111 & 60.0014493681085 & 167.706134053147 \tabularnewline
Winsorized Mean ( 5 / 24 ) & 10064.2777777778 & 58.8709837840242 & 170.954808818889 \tabularnewline
Winsorized Mean ( 6 / 24 ) & 10069.8611111111 & 57.7181013853163 & 174.466257021977 \tabularnewline
Winsorized Mean ( 7 / 24 ) & 10080.2638888889 & 55.8054901952956 & 180.632117980009 \tabularnewline
Winsorized Mean ( 8 / 24 ) & 10077.9305555556 & 54.2988683800215 & 185.60111575481 \tabularnewline
Winsorized Mean ( 9 / 24 ) & 10067.8055555556 & 52.0763615573815 & 193.327745150976 \tabularnewline
Winsorized Mean ( 10 / 24 ) & 10062.6666666667 & 51.1267029017984 & 196.818220138203 \tabularnewline
Winsorized Mean ( 11 / 24 ) & 10062.3611111111 & 50.7199084973493 & 198.390758367338 \tabularnewline
Winsorized Mean ( 12 / 24 ) & 10071.6944444444 & 48.7830728826945 & 206.458795014066 \tabularnewline
Winsorized Mean ( 13 / 24 ) & 10066.2777777778 & 45.7722436336082 & 219.921004055537 \tabularnewline
Winsorized Mean ( 14 / 24 ) & 10069.3888888889 & 43.3474361104957 & 232.294912742274 \tabularnewline
Winsorized Mean ( 15 / 24 ) & 10072.0972222222 & 42.8697309766125 & 234.946592683706 \tabularnewline
Winsorized Mean ( 16 / 24 ) & 10075.6527777778 & 39.0093893422511 & 258.287887805125 \tabularnewline
Winsorized Mean ( 17 / 24 ) & 10077.7777777778 & 37.6038947961885 & 267.998244128671 \tabularnewline
Winsorized Mean ( 18 / 24 ) & 10081.5277777778 & 34.9434372607887 & 288.509905380448 \tabularnewline
Winsorized Mean ( 19 / 24 ) & 10081.7916666667 & 34.90776992609 & 288.812252630654 \tabularnewline
Winsorized Mean ( 20 / 24 ) & 10075.4027777778 & 33.2100104855214 & 303.384510588166 \tabularnewline
Winsorized Mean ( 21 / 24 ) & 10080.0694444444 & 31.8635117772862 & 316.351490535641 \tabularnewline
Winsorized Mean ( 22 / 24 ) & 10080.375 & 30.3250416716373 & 332.410919963485 \tabularnewline
Winsorized Mean ( 23 / 24 ) & 10069.1944444444 & 27.2376347653226 & 369.679472215552 \tabularnewline
Winsorized Mean ( 24 / 24 ) & 10068.5277777778 & 26.268543433332 & 383.292199026227 \tabularnewline
Trimmed Mean ( 1 / 24 ) & 10065.8142857143 & 61.7125081457444 & 163.108170258486 \tabularnewline
Trimmed Mean ( 2 / 24 ) & 10066.1911764706 & 58.9649464228694 & 170.714836307668 \tabularnewline
Trimmed Mean ( 3 / 24 ) & 10067.1666666667 & 57.5042294312897 & 175.068282215583 \tabularnewline
Trimmed Mean ( 4 / 24 ) & 10068.0625 & 56.0074128588251 & 179.763034678606 \tabularnewline
Trimmed Mean ( 5 / 24 ) & 10069.6451612903 & 54.4379293572944 & 184.974801212586 \tabularnewline
Trimmed Mean ( 6 / 24 ) & 10070.9333333333 & 52.8978167859093 & 190.384668881382 \tabularnewline
Trimmed Mean ( 7 / 24 ) & 10071.1551724138 & 51.3523338418098 & 196.118743179966 \tabularnewline
Trimmed Mean ( 8 / 24 ) & 10069.4821428571 & 49.9619010111083 & 201.543214711112 \tabularnewline
Trimmed Mean ( 9 / 24 ) & 10068.0740740741 & 48.6165982061719 & 207.091290743496 \tabularnewline
Trimmed Mean ( 10 / 24 ) & 10068.1153846154 & 47.469039317222 & 212.098570551071 \tabularnewline
Trimmed Mean ( 11 / 24 ) & 10068.9 & 46.2330586732666 & 217.78572062813 \tabularnewline
Trimmed Mean ( 12 / 24 ) & 10069.7916666667 & 44.7466762339221 & 225.039992110807 \tabularnewline
Trimmed Mean ( 13 / 24 ) & 10069.5434782609 & 43.2927424887234 & 232.591951893177 \tabularnewline
Trimmed Mean ( 14 / 24 ) & 10069.9545454545 & 42.10526116164 & 239.16143179344 \tabularnewline
Trimmed Mean ( 15 / 24 ) & 10070.0238095238 & 41.0922376546332 & 245.059027793985 \tabularnewline
Trimmed Mean ( 16 / 24 ) & 10069.775 & 39.8331373372498 & 252.79894261764 \tabularnewline
Trimmed Mean ( 17 / 24 ) & 10069.0789473684 & 39.0458092851161 & 257.878608017652 \tabularnewline
Trimmed Mean ( 18 / 24 ) & 10068.0555555556 & 38.2563604929401 & 263.173376291598 \tabularnewline
Trimmed Mean ( 19 / 24 ) & 10066.4705882353 & 37.7501457374415 & 266.660443068201 \tabularnewline
Trimmed Mean ( 20 / 24 ) & 10064.65625 & 36.9480511887047 & 272.400192329409 \tabularnewline
Trimmed Mean ( 21 / 24 ) & 10063.3666666667 & 36.1920319970657 & 278.054757121196 \tabularnewline
Trimmed Mean ( 22 / 24 ) & 10061.3214285714 & 35.3670120104703 & 284.483219153283 \tabularnewline
Trimmed Mean ( 23 / 24 ) & 10058.9230769231 & 34.4982908418072 & 291.57743272119 \tabularnewline
Trimmed Mean ( 24 / 24 ) & 10057.5833333333 & 34.1021970405892 & 294.924790955919 \tabularnewline
Median & 10065 &  &  \tabularnewline
Midrange & 10072 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 10058.1351351351 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 10068.0555555556 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 10058.1351351351 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 10068.0555555556 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 10068.0555555556 &  &  \tabularnewline
Midmean - Closest Observation & 10058.1351351351 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 10068.0555555556 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 10069.0789473684 &  &  \tabularnewline
Number of observations & 72 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147853&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]10065.9861111111[/C][C]66.3204168336484[/C][C]151.778088734871[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]10050.4048080184[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]10034.7470408289[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]10081.4861317665[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 24 )[/C][C]10065.4583333333[/C][C]64.0154364988088[/C][C]157.234862149548[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 24 )[/C][C]10064.4027777778[/C][C]61.2047081423959[/C][C]164.438375465535[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 24 )[/C][C]10064.7777777778[/C][C]60.6432854334432[/C][C]165.966894864626[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 24 )[/C][C]10062.6111111111[/C][C]60.0014493681085[/C][C]167.706134053147[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 24 )[/C][C]10064.2777777778[/C][C]58.8709837840242[/C][C]170.954808818889[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 24 )[/C][C]10069.8611111111[/C][C]57.7181013853163[/C][C]174.466257021977[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 24 )[/C][C]10080.2638888889[/C][C]55.8054901952956[/C][C]180.632117980009[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 24 )[/C][C]10077.9305555556[/C][C]54.2988683800215[/C][C]185.60111575481[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 24 )[/C][C]10067.8055555556[/C][C]52.0763615573815[/C][C]193.327745150976[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 24 )[/C][C]10062.6666666667[/C][C]51.1267029017984[/C][C]196.818220138203[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 24 )[/C][C]10062.3611111111[/C][C]50.7199084973493[/C][C]198.390758367338[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 24 )[/C][C]10071.6944444444[/C][C]48.7830728826945[/C][C]206.458795014066[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 24 )[/C][C]10066.2777777778[/C][C]45.7722436336082[/C][C]219.921004055537[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 24 )[/C][C]10069.3888888889[/C][C]43.3474361104957[/C][C]232.294912742274[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 24 )[/C][C]10072.0972222222[/C][C]42.8697309766125[/C][C]234.946592683706[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 24 )[/C][C]10075.6527777778[/C][C]39.0093893422511[/C][C]258.287887805125[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 24 )[/C][C]10077.7777777778[/C][C]37.6038947961885[/C][C]267.998244128671[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 24 )[/C][C]10081.5277777778[/C][C]34.9434372607887[/C][C]288.509905380448[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 24 )[/C][C]10081.7916666667[/C][C]34.90776992609[/C][C]288.812252630654[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 24 )[/C][C]10075.4027777778[/C][C]33.2100104855214[/C][C]303.384510588166[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 24 )[/C][C]10080.0694444444[/C][C]31.8635117772862[/C][C]316.351490535641[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 24 )[/C][C]10080.375[/C][C]30.3250416716373[/C][C]332.410919963485[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 24 )[/C][C]10069.1944444444[/C][C]27.2376347653226[/C][C]369.679472215552[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 24 )[/C][C]10068.5277777778[/C][C]26.268543433332[/C][C]383.292199026227[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 24 )[/C][C]10065.8142857143[/C][C]61.7125081457444[/C][C]163.108170258486[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 24 )[/C][C]10066.1911764706[/C][C]58.9649464228694[/C][C]170.714836307668[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 24 )[/C][C]10067.1666666667[/C][C]57.5042294312897[/C][C]175.068282215583[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 24 )[/C][C]10068.0625[/C][C]56.0074128588251[/C][C]179.763034678606[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 24 )[/C][C]10069.6451612903[/C][C]54.4379293572944[/C][C]184.974801212586[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 24 )[/C][C]10070.9333333333[/C][C]52.8978167859093[/C][C]190.384668881382[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 24 )[/C][C]10071.1551724138[/C][C]51.3523338418098[/C][C]196.118743179966[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 24 )[/C][C]10069.4821428571[/C][C]49.9619010111083[/C][C]201.543214711112[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 24 )[/C][C]10068.0740740741[/C][C]48.6165982061719[/C][C]207.091290743496[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 24 )[/C][C]10068.1153846154[/C][C]47.469039317222[/C][C]212.098570551071[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 24 )[/C][C]10068.9[/C][C]46.2330586732666[/C][C]217.78572062813[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 24 )[/C][C]10069.7916666667[/C][C]44.7466762339221[/C][C]225.039992110807[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 24 )[/C][C]10069.5434782609[/C][C]43.2927424887234[/C][C]232.591951893177[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 24 )[/C][C]10069.9545454545[/C][C]42.10526116164[/C][C]239.16143179344[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 24 )[/C][C]10070.0238095238[/C][C]41.0922376546332[/C][C]245.059027793985[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 24 )[/C][C]10069.775[/C][C]39.8331373372498[/C][C]252.79894261764[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 24 )[/C][C]10069.0789473684[/C][C]39.0458092851161[/C][C]257.878608017652[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 24 )[/C][C]10068.0555555556[/C][C]38.2563604929401[/C][C]263.173376291598[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 24 )[/C][C]10066.4705882353[/C][C]37.7501457374415[/C][C]266.660443068201[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 24 )[/C][C]10064.65625[/C][C]36.9480511887047[/C][C]272.400192329409[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 24 )[/C][C]10063.3666666667[/C][C]36.1920319970657[/C][C]278.054757121196[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 24 )[/C][C]10061.3214285714[/C][C]35.3670120104703[/C][C]284.483219153283[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 24 )[/C][C]10058.9230769231[/C][C]34.4982908418072[/C][C]291.57743272119[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 24 )[/C][C]10057.5833333333[/C][C]34.1021970405892[/C][C]294.924790955919[/C][/ROW]
[ROW][C]Median[/C][C]10065[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]10072[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]10058.1351351351[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]10068.0555555556[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]10058.1351351351[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]10068.0555555556[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]10068.0555555556[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]10058.1351351351[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]10068.0555555556[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]10069.0789473684[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]72[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147853&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147853&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 Mean10065.986111111166.3204168336484151.778088734871
Geometric Mean10050.4048080184
Harmonic Mean10034.7470408289
Quadratic Mean10081.4861317665
Winsorized Mean ( 1 / 24 )10065.458333333364.0154364988088157.234862149548
Winsorized Mean ( 2 / 24 )10064.402777777861.2047081423959164.438375465535
Winsorized Mean ( 3 / 24 )10064.777777777860.6432854334432165.966894864626
Winsorized Mean ( 4 / 24 )10062.611111111160.0014493681085167.706134053147
Winsorized Mean ( 5 / 24 )10064.277777777858.8709837840242170.954808818889
Winsorized Mean ( 6 / 24 )10069.861111111157.7181013853163174.466257021977
Winsorized Mean ( 7 / 24 )10080.263888888955.8054901952956180.632117980009
Winsorized Mean ( 8 / 24 )10077.930555555654.2988683800215185.60111575481
Winsorized Mean ( 9 / 24 )10067.805555555652.0763615573815193.327745150976
Winsorized Mean ( 10 / 24 )10062.666666666751.1267029017984196.818220138203
Winsorized Mean ( 11 / 24 )10062.361111111150.7199084973493198.390758367338
Winsorized Mean ( 12 / 24 )10071.694444444448.7830728826945206.458795014066
Winsorized Mean ( 13 / 24 )10066.277777777845.7722436336082219.921004055537
Winsorized Mean ( 14 / 24 )10069.388888888943.3474361104957232.294912742274
Winsorized Mean ( 15 / 24 )10072.097222222242.8697309766125234.946592683706
Winsorized Mean ( 16 / 24 )10075.652777777839.0093893422511258.287887805125
Winsorized Mean ( 17 / 24 )10077.777777777837.6038947961885267.998244128671
Winsorized Mean ( 18 / 24 )10081.527777777834.9434372607887288.509905380448
Winsorized Mean ( 19 / 24 )10081.791666666734.90776992609288.812252630654
Winsorized Mean ( 20 / 24 )10075.402777777833.2100104855214303.384510588166
Winsorized Mean ( 21 / 24 )10080.069444444431.8635117772862316.351490535641
Winsorized Mean ( 22 / 24 )10080.37530.3250416716373332.410919963485
Winsorized Mean ( 23 / 24 )10069.194444444427.2376347653226369.679472215552
Winsorized Mean ( 24 / 24 )10068.527777777826.268543433332383.292199026227
Trimmed Mean ( 1 / 24 )10065.814285714361.7125081457444163.108170258486
Trimmed Mean ( 2 / 24 )10066.191176470658.9649464228694170.714836307668
Trimmed Mean ( 3 / 24 )10067.166666666757.5042294312897175.068282215583
Trimmed Mean ( 4 / 24 )10068.062556.0074128588251179.763034678606
Trimmed Mean ( 5 / 24 )10069.645161290354.4379293572944184.974801212586
Trimmed Mean ( 6 / 24 )10070.933333333352.8978167859093190.384668881382
Trimmed Mean ( 7 / 24 )10071.155172413851.3523338418098196.118743179966
Trimmed Mean ( 8 / 24 )10069.482142857149.9619010111083201.543214711112
Trimmed Mean ( 9 / 24 )10068.074074074148.6165982061719207.091290743496
Trimmed Mean ( 10 / 24 )10068.115384615447.469039317222212.098570551071
Trimmed Mean ( 11 / 24 )10068.946.2330586732666217.78572062813
Trimmed Mean ( 12 / 24 )10069.791666666744.7466762339221225.039992110807
Trimmed Mean ( 13 / 24 )10069.543478260943.2927424887234232.591951893177
Trimmed Mean ( 14 / 24 )10069.954545454542.10526116164239.16143179344
Trimmed Mean ( 15 / 24 )10070.023809523841.0922376546332245.059027793985
Trimmed Mean ( 16 / 24 )10069.77539.8331373372498252.79894261764
Trimmed Mean ( 17 / 24 )10069.078947368439.0458092851161257.878608017652
Trimmed Mean ( 18 / 24 )10068.055555555638.2563604929401263.173376291598
Trimmed Mean ( 19 / 24 )10066.470588235337.7501457374415266.660443068201
Trimmed Mean ( 20 / 24 )10064.6562536.9480511887047272.400192329409
Trimmed Mean ( 21 / 24 )10063.366666666736.1920319970657278.054757121196
Trimmed Mean ( 22 / 24 )10061.321428571435.3670120104703284.483219153283
Trimmed Mean ( 23 / 24 )10058.923076923134.4982908418072291.57743272119
Trimmed Mean ( 24 / 24 )10057.583333333334.1021970405892294.924790955919
Median10065
Midrange10072
Midmean - Weighted Average at Xnp10058.1351351351
Midmean - Weighted Average at X(n+1)p10068.0555555556
Midmean - Empirical Distribution Function10058.1351351351
Midmean - Empirical Distribution Function - Averaging10068.0555555556
Midmean - Empirical Distribution Function - Interpolation10068.0555555556
Midmean - Closest Observation10058.1351351351
Midmean - True Basic - Statistics Graphics Toolkit10068.0555555556
Midmean - MS Excel (old versions)10069.0789473684
Number of observations72



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')