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Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 08 Mar 2016 21:43:34 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Mar/08/t1457473426sj7zccnbf31y9ur.htm/, Retrieved Sun, 28 Apr 2024 22:33:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=293785, Retrieved Sun, 28 Apr 2024 22:33:19 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact71
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2016-03-08 21:43:34] [66b954879edaa66f79d20403c5a86347] [Current]
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Dataseries X:
89,8
89,2
89,9
88,9
84
86,3
89,3
90,6
88,3
91,6
95,4
96,8
92,5
93,6
93,8
92,7
88,3
90,4
91,2
91,5
88,9
88,6
89,1
89,4
86,7
89,8
90,9
91,4
90,2
92,2
94
95,8
95,1
96,2
96,8
97,1
96,5
97,2
97,8
99,9
101,2
103,3
104,5
100,8
95
93,4
93,1
94,9
96,9
100,9
100,2
101,8
105,4
106,4
105,6
107,5
109,5
108,6
109,2
110,3
110,3
107,9
107,7
108,1
108
105,9
105,9
104,7





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
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=293785&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]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=293785&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293785&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
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean96.83382352941180.886783779171335109.196656280632
Geometric Mean96.5661833739597
Harmonic Mean96.303413902051
Quadratic Mean97.1054952403949
Winsorized Mean ( 1 / 22 )96.86764705882350.880097571154384110.064668093296
Winsorized Mean ( 2 / 22 )96.85588235294120.872797321245044110.971791497683
Winsorized Mean ( 3 / 22 )96.91323529411770.858531282585086112.882590605559
Winsorized Mean ( 4 / 22 )96.87794117647060.851133741623028113.82223079505
Winsorized Mean ( 5 / 22 )96.86323529411760.840408112980949115.257377693013
Winsorized Mean ( 6 / 22 )96.88088235294120.834819662548095116.050072487793
Winsorized Mean ( 7 / 22 )96.87058823529410.832779016521129116.322081024524
Winsorized Mean ( 8 / 22 )96.87058823529410.82481290299658117.445529626609
Winsorized Mean ( 9 / 22 )96.85735294117650.817793011114381118.437491669429
Winsorized Mean ( 10 / 22 )96.71029411764710.785103684249051123.181556854048
Winsorized Mean ( 11 / 22 )96.64558823529410.768101526705403125.823976225947
Winsorized Mean ( 12 / 22 )96.71617647058820.758326939177171127.53889051539
Winsorized Mean ( 13 / 22 )96.65882352941180.748027066403689129.21835033874
Winsorized Mean ( 14 / 22 )96.63823529411760.73789329898284130.965053385537
Winsorized Mean ( 15 / 22 )96.550.701842864533741137.566405357902
Winsorized Mean ( 16 / 22 )96.550.687383161114943140.460234497736
Winsorized Mean ( 17 / 22 )96.30.629850798280688152.89335230323
Winsorized Mean ( 18 / 22 )95.98235294117650.554951932112623172.956155996764
Winsorized Mean ( 19 / 22 )95.89852941176470.517602753461525185.274380343676
Winsorized Mean ( 20 / 22 )95.86911764705880.496242498181582193.1900592923
Winsorized Mean ( 21 / 22 )95.86911764705880.487433196399601196.681552170002
Winsorized Mean ( 22 / 22 )95.70735294117650.45408745612179210.768546126733
Trimmed Mean ( 1 / 22 )96.82424242424240.868608351920429111.470540445727
Trimmed Mean ( 2 / 22 )96.7781250.854526546573951113.253503227035
Trimmed Mean ( 3 / 22 )96.73548387096770.841905800498316114.900602672782
Trimmed Mean ( 4 / 22 )96.66833333333330.832583249995613116.106507467983
Trimmed Mean ( 5 / 22 )96.60689655172410.823376189159344117.330204375182
Trimmed Mean ( 6 / 22 )96.54464285714290.814813816845572118.486752263113
Trimmed Mean ( 7 / 22 )96.47407407407410.80506426941201119.834002997717
Trimmed Mean ( 8 / 22 )96.40.792769930620434121.598961157061
Trimmed Mean ( 9 / 22 )96.320.778653993000952123.700643502489
Trimmed Mean ( 10 / 22 )96.23541666666670.761847846814715126.318420494364
Trimmed Mean ( 11 / 22 )96.16521739130440.747867935016045128.585827642472
Trimmed Mean ( 12 / 22 )96.09772727272730.733172669413619131.071071361109
Trimmed Mean ( 13 / 22 )96.01428571428570.715268777633631134.235253539146
Trimmed Mean ( 14 / 22 )95.930.693469537903432138.333401478636
Trimmed Mean ( 15 / 22 )95.83947368421050.666112685028778143.87876982116
Trimmed Mean ( 16 / 22 )95.750.638232927575246150.023597754146
Trimmed Mean ( 17 / 22 )95.650.602819430341415158.671063316302
Trimmed Mean ( 18 / 22 )95.568750.571049498942023167.356332817136
Trimmed Mean ( 19 / 22 )95.51666666666670.549588839697739173.796590773566
Trimmed Mean ( 20 / 22 )95.46785714285710.529276574548539180.374234820971
Trimmed Mean ( 21 / 22 )95.41538461538460.504828754139379189.005447556264
Trimmed Mean ( 22 / 22 )95.35416666666670.468654378330666203.463727376912
Median95.25
Midrange97.15
Midmean - Weighted Average at Xnp95.5
Midmean - Weighted Average at X(n+1)p95.65
Midmean - Empirical Distribution Function95.5
Midmean - Empirical Distribution Function - Averaging95.65
Midmean - Empirical Distribution Function - Interpolation95.65
Midmean - Closest Observation95.5
Midmean - True Basic - Statistics Graphics Toolkit95.65
Midmean - MS Excel (old versions)95.75
Number of observations68

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 96.8338235294118 & 0.886783779171335 & 109.196656280632 \tabularnewline
Geometric Mean & 96.5661833739597 &  &  \tabularnewline
Harmonic Mean & 96.303413902051 &  &  \tabularnewline
Quadratic Mean & 97.1054952403949 &  &  \tabularnewline
Winsorized Mean ( 1 / 22 ) & 96.8676470588235 & 0.880097571154384 & 110.064668093296 \tabularnewline
Winsorized Mean ( 2 / 22 ) & 96.8558823529412 & 0.872797321245044 & 110.971791497683 \tabularnewline
Winsorized Mean ( 3 / 22 ) & 96.9132352941177 & 0.858531282585086 & 112.882590605559 \tabularnewline
Winsorized Mean ( 4 / 22 ) & 96.8779411764706 & 0.851133741623028 & 113.82223079505 \tabularnewline
Winsorized Mean ( 5 / 22 ) & 96.8632352941176 & 0.840408112980949 & 115.257377693013 \tabularnewline
Winsorized Mean ( 6 / 22 ) & 96.8808823529412 & 0.834819662548095 & 116.050072487793 \tabularnewline
Winsorized Mean ( 7 / 22 ) & 96.8705882352941 & 0.832779016521129 & 116.322081024524 \tabularnewline
Winsorized Mean ( 8 / 22 ) & 96.8705882352941 & 0.82481290299658 & 117.445529626609 \tabularnewline
Winsorized Mean ( 9 / 22 ) & 96.8573529411765 & 0.817793011114381 & 118.437491669429 \tabularnewline
Winsorized Mean ( 10 / 22 ) & 96.7102941176471 & 0.785103684249051 & 123.181556854048 \tabularnewline
Winsorized Mean ( 11 / 22 ) & 96.6455882352941 & 0.768101526705403 & 125.823976225947 \tabularnewline
Winsorized Mean ( 12 / 22 ) & 96.7161764705882 & 0.758326939177171 & 127.53889051539 \tabularnewline
Winsorized Mean ( 13 / 22 ) & 96.6588235294118 & 0.748027066403689 & 129.21835033874 \tabularnewline
Winsorized Mean ( 14 / 22 ) & 96.6382352941176 & 0.73789329898284 & 130.965053385537 \tabularnewline
Winsorized Mean ( 15 / 22 ) & 96.55 & 0.701842864533741 & 137.566405357902 \tabularnewline
Winsorized Mean ( 16 / 22 ) & 96.55 & 0.687383161114943 & 140.460234497736 \tabularnewline
Winsorized Mean ( 17 / 22 ) & 96.3 & 0.629850798280688 & 152.89335230323 \tabularnewline
Winsorized Mean ( 18 / 22 ) & 95.9823529411765 & 0.554951932112623 & 172.956155996764 \tabularnewline
Winsorized Mean ( 19 / 22 ) & 95.8985294117647 & 0.517602753461525 & 185.274380343676 \tabularnewline
Winsorized Mean ( 20 / 22 ) & 95.8691176470588 & 0.496242498181582 & 193.1900592923 \tabularnewline
Winsorized Mean ( 21 / 22 ) & 95.8691176470588 & 0.487433196399601 & 196.681552170002 \tabularnewline
Winsorized Mean ( 22 / 22 ) & 95.7073529411765 & 0.45408745612179 & 210.768546126733 \tabularnewline
Trimmed Mean ( 1 / 22 ) & 96.8242424242424 & 0.868608351920429 & 111.470540445727 \tabularnewline
Trimmed Mean ( 2 / 22 ) & 96.778125 & 0.854526546573951 & 113.253503227035 \tabularnewline
Trimmed Mean ( 3 / 22 ) & 96.7354838709677 & 0.841905800498316 & 114.900602672782 \tabularnewline
Trimmed Mean ( 4 / 22 ) & 96.6683333333333 & 0.832583249995613 & 116.106507467983 \tabularnewline
Trimmed Mean ( 5 / 22 ) & 96.6068965517241 & 0.823376189159344 & 117.330204375182 \tabularnewline
Trimmed Mean ( 6 / 22 ) & 96.5446428571429 & 0.814813816845572 & 118.486752263113 \tabularnewline
Trimmed Mean ( 7 / 22 ) & 96.4740740740741 & 0.80506426941201 & 119.834002997717 \tabularnewline
Trimmed Mean ( 8 / 22 ) & 96.4 & 0.792769930620434 & 121.598961157061 \tabularnewline
Trimmed Mean ( 9 / 22 ) & 96.32 & 0.778653993000952 & 123.700643502489 \tabularnewline
Trimmed Mean ( 10 / 22 ) & 96.2354166666667 & 0.761847846814715 & 126.318420494364 \tabularnewline
Trimmed Mean ( 11 / 22 ) & 96.1652173913044 & 0.747867935016045 & 128.585827642472 \tabularnewline
Trimmed Mean ( 12 / 22 ) & 96.0977272727273 & 0.733172669413619 & 131.071071361109 \tabularnewline
Trimmed Mean ( 13 / 22 ) & 96.0142857142857 & 0.715268777633631 & 134.235253539146 \tabularnewline
Trimmed Mean ( 14 / 22 ) & 95.93 & 0.693469537903432 & 138.333401478636 \tabularnewline
Trimmed Mean ( 15 / 22 ) & 95.8394736842105 & 0.666112685028778 & 143.87876982116 \tabularnewline
Trimmed Mean ( 16 / 22 ) & 95.75 & 0.638232927575246 & 150.023597754146 \tabularnewline
Trimmed Mean ( 17 / 22 ) & 95.65 & 0.602819430341415 & 158.671063316302 \tabularnewline
Trimmed Mean ( 18 / 22 ) & 95.56875 & 0.571049498942023 & 167.356332817136 \tabularnewline
Trimmed Mean ( 19 / 22 ) & 95.5166666666667 & 0.549588839697739 & 173.796590773566 \tabularnewline
Trimmed Mean ( 20 / 22 ) & 95.4678571428571 & 0.529276574548539 & 180.374234820971 \tabularnewline
Trimmed Mean ( 21 / 22 ) & 95.4153846153846 & 0.504828754139379 & 189.005447556264 \tabularnewline
Trimmed Mean ( 22 / 22 ) & 95.3541666666667 & 0.468654378330666 & 203.463727376912 \tabularnewline
Median & 95.25 &  &  \tabularnewline
Midrange & 97.15 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 95.5 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 95.65 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 95.5 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 95.65 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 95.65 &  &  \tabularnewline
Midmean - Closest Observation & 95.5 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 95.65 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 95.75 &  &  \tabularnewline
Number of observations & 68 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293785&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]96.8338235294118[/C][C]0.886783779171335[/C][C]109.196656280632[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]96.5661833739597[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]96.303413902051[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]97.1054952403949[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 22 )[/C][C]96.8676470588235[/C][C]0.880097571154384[/C][C]110.064668093296[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 22 )[/C][C]96.8558823529412[/C][C]0.872797321245044[/C][C]110.971791497683[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 22 )[/C][C]96.9132352941177[/C][C]0.858531282585086[/C][C]112.882590605559[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 22 )[/C][C]96.8779411764706[/C][C]0.851133741623028[/C][C]113.82223079505[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 22 )[/C][C]96.8632352941176[/C][C]0.840408112980949[/C][C]115.257377693013[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 22 )[/C][C]96.8808823529412[/C][C]0.834819662548095[/C][C]116.050072487793[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 22 )[/C][C]96.8705882352941[/C][C]0.832779016521129[/C][C]116.322081024524[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 22 )[/C][C]96.8705882352941[/C][C]0.82481290299658[/C][C]117.445529626609[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 22 )[/C][C]96.8573529411765[/C][C]0.817793011114381[/C][C]118.437491669429[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 22 )[/C][C]96.7102941176471[/C][C]0.785103684249051[/C][C]123.181556854048[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 22 )[/C][C]96.6455882352941[/C][C]0.768101526705403[/C][C]125.823976225947[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 22 )[/C][C]96.7161764705882[/C][C]0.758326939177171[/C][C]127.53889051539[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 22 )[/C][C]96.6588235294118[/C][C]0.748027066403689[/C][C]129.21835033874[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 22 )[/C][C]96.6382352941176[/C][C]0.73789329898284[/C][C]130.965053385537[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 22 )[/C][C]96.55[/C][C]0.701842864533741[/C][C]137.566405357902[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 22 )[/C][C]96.55[/C][C]0.687383161114943[/C][C]140.460234497736[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 22 )[/C][C]96.3[/C][C]0.629850798280688[/C][C]152.89335230323[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 22 )[/C][C]95.9823529411765[/C][C]0.554951932112623[/C][C]172.956155996764[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 22 )[/C][C]95.8985294117647[/C][C]0.517602753461525[/C][C]185.274380343676[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 22 )[/C][C]95.8691176470588[/C][C]0.496242498181582[/C][C]193.1900592923[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 22 )[/C][C]95.8691176470588[/C][C]0.487433196399601[/C][C]196.681552170002[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 22 )[/C][C]95.7073529411765[/C][C]0.45408745612179[/C][C]210.768546126733[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 22 )[/C][C]96.8242424242424[/C][C]0.868608351920429[/C][C]111.470540445727[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 22 )[/C][C]96.778125[/C][C]0.854526546573951[/C][C]113.253503227035[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 22 )[/C][C]96.7354838709677[/C][C]0.841905800498316[/C][C]114.900602672782[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 22 )[/C][C]96.6683333333333[/C][C]0.832583249995613[/C][C]116.106507467983[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 22 )[/C][C]96.6068965517241[/C][C]0.823376189159344[/C][C]117.330204375182[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 22 )[/C][C]96.5446428571429[/C][C]0.814813816845572[/C][C]118.486752263113[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 22 )[/C][C]96.4740740740741[/C][C]0.80506426941201[/C][C]119.834002997717[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 22 )[/C][C]96.4[/C][C]0.792769930620434[/C][C]121.598961157061[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 22 )[/C][C]96.32[/C][C]0.778653993000952[/C][C]123.700643502489[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 22 )[/C][C]96.2354166666667[/C][C]0.761847846814715[/C][C]126.318420494364[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 22 )[/C][C]96.1652173913044[/C][C]0.747867935016045[/C][C]128.585827642472[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 22 )[/C][C]96.0977272727273[/C][C]0.733172669413619[/C][C]131.071071361109[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 22 )[/C][C]96.0142857142857[/C][C]0.715268777633631[/C][C]134.235253539146[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 22 )[/C][C]95.93[/C][C]0.693469537903432[/C][C]138.333401478636[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 22 )[/C][C]95.8394736842105[/C][C]0.666112685028778[/C][C]143.87876982116[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 22 )[/C][C]95.75[/C][C]0.638232927575246[/C][C]150.023597754146[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 22 )[/C][C]95.65[/C][C]0.602819430341415[/C][C]158.671063316302[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 22 )[/C][C]95.56875[/C][C]0.571049498942023[/C][C]167.356332817136[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 22 )[/C][C]95.5166666666667[/C][C]0.549588839697739[/C][C]173.796590773566[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 22 )[/C][C]95.4678571428571[/C][C]0.529276574548539[/C][C]180.374234820971[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 22 )[/C][C]95.4153846153846[/C][C]0.504828754139379[/C][C]189.005447556264[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 22 )[/C][C]95.3541666666667[/C][C]0.468654378330666[/C][C]203.463727376912[/C][/ROW]
[ROW][C]Median[/C][C]95.25[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]97.15[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]95.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]95.65[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]95.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]95.65[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]95.65[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]95.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]95.65[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]95.75[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]68[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293785&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293785&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 Mean96.83382352941180.886783779171335109.196656280632
Geometric Mean96.5661833739597
Harmonic Mean96.303413902051
Quadratic Mean97.1054952403949
Winsorized Mean ( 1 / 22 )96.86764705882350.880097571154384110.064668093296
Winsorized Mean ( 2 / 22 )96.85588235294120.872797321245044110.971791497683
Winsorized Mean ( 3 / 22 )96.91323529411770.858531282585086112.882590605559
Winsorized Mean ( 4 / 22 )96.87794117647060.851133741623028113.82223079505
Winsorized Mean ( 5 / 22 )96.86323529411760.840408112980949115.257377693013
Winsorized Mean ( 6 / 22 )96.88088235294120.834819662548095116.050072487793
Winsorized Mean ( 7 / 22 )96.87058823529410.832779016521129116.322081024524
Winsorized Mean ( 8 / 22 )96.87058823529410.82481290299658117.445529626609
Winsorized Mean ( 9 / 22 )96.85735294117650.817793011114381118.437491669429
Winsorized Mean ( 10 / 22 )96.71029411764710.785103684249051123.181556854048
Winsorized Mean ( 11 / 22 )96.64558823529410.768101526705403125.823976225947
Winsorized Mean ( 12 / 22 )96.71617647058820.758326939177171127.53889051539
Winsorized Mean ( 13 / 22 )96.65882352941180.748027066403689129.21835033874
Winsorized Mean ( 14 / 22 )96.63823529411760.73789329898284130.965053385537
Winsorized Mean ( 15 / 22 )96.550.701842864533741137.566405357902
Winsorized Mean ( 16 / 22 )96.550.687383161114943140.460234497736
Winsorized Mean ( 17 / 22 )96.30.629850798280688152.89335230323
Winsorized Mean ( 18 / 22 )95.98235294117650.554951932112623172.956155996764
Winsorized Mean ( 19 / 22 )95.89852941176470.517602753461525185.274380343676
Winsorized Mean ( 20 / 22 )95.86911764705880.496242498181582193.1900592923
Winsorized Mean ( 21 / 22 )95.86911764705880.487433196399601196.681552170002
Winsorized Mean ( 22 / 22 )95.70735294117650.45408745612179210.768546126733
Trimmed Mean ( 1 / 22 )96.82424242424240.868608351920429111.470540445727
Trimmed Mean ( 2 / 22 )96.7781250.854526546573951113.253503227035
Trimmed Mean ( 3 / 22 )96.73548387096770.841905800498316114.900602672782
Trimmed Mean ( 4 / 22 )96.66833333333330.832583249995613116.106507467983
Trimmed Mean ( 5 / 22 )96.60689655172410.823376189159344117.330204375182
Trimmed Mean ( 6 / 22 )96.54464285714290.814813816845572118.486752263113
Trimmed Mean ( 7 / 22 )96.47407407407410.80506426941201119.834002997717
Trimmed Mean ( 8 / 22 )96.40.792769930620434121.598961157061
Trimmed Mean ( 9 / 22 )96.320.778653993000952123.700643502489
Trimmed Mean ( 10 / 22 )96.23541666666670.761847846814715126.318420494364
Trimmed Mean ( 11 / 22 )96.16521739130440.747867935016045128.585827642472
Trimmed Mean ( 12 / 22 )96.09772727272730.733172669413619131.071071361109
Trimmed Mean ( 13 / 22 )96.01428571428570.715268777633631134.235253539146
Trimmed Mean ( 14 / 22 )95.930.693469537903432138.333401478636
Trimmed Mean ( 15 / 22 )95.83947368421050.666112685028778143.87876982116
Trimmed Mean ( 16 / 22 )95.750.638232927575246150.023597754146
Trimmed Mean ( 17 / 22 )95.650.602819430341415158.671063316302
Trimmed Mean ( 18 / 22 )95.568750.571049498942023167.356332817136
Trimmed Mean ( 19 / 22 )95.51666666666670.549588839697739173.796590773566
Trimmed Mean ( 20 / 22 )95.46785714285710.529276574548539180.374234820971
Trimmed Mean ( 21 / 22 )95.41538461538460.504828754139379189.005447556264
Trimmed Mean ( 22 / 22 )95.35416666666670.468654378330666203.463727376912
Median95.25
Midrange97.15
Midmean - Weighted Average at Xnp95.5
Midmean - Weighted Average at X(n+1)p95.65
Midmean - Empirical Distribution Function95.5
Midmean - Empirical Distribution Function - Averaging95.65
Midmean - Empirical Distribution Function - Interpolation95.65
Midmean - Closest Observation95.5
Midmean - True Basic - Statistics Graphics Toolkit95.65
Midmean - MS Excel (old versions)95.75
Number of observations68



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')