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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 11:41:39 -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/t1322498521pbbjmphfpfbvgef.htm/, Retrieved Thu, 25 Apr 2024 14:45:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147856, Retrieved Thu, 25 Apr 2024 14:45:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact94
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]
- RMPD        [Central Tendency] [] [2011-11-28 16:37:14] [d6b4d011b409693eac2700c83288e3e7]
- R               [Central Tendency] [] [2011-11-28 16:41:39] [e232377fd09030116200e3da7df6eeaf] [Current]
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Dataseries X:
9676
8642
9402
9610
9294
9448
10319
9548
9801
9596
8923
9746
9829
9125
9782
9441
9162
9915
10444
10209
9985
9842
9429
10132
9849
9172
10313
9819
9955
10048
10082
10541
10208
10233
9439
9963
10158
9225
10474
9757
10490
10281
10444
10640
10695
10786
9832
9747
10411
9511
10402
9701
10540
10112
10915
11183
10384
10834
9886
10216
10943
9867
10203
10837
10573
10647
11502
10656
10866
10835
9945
10331




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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147856&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147856&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147856&T=0

As an alternative you can also use a QR Code:  

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

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







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic 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=147856&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=147856&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147856&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')