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Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationThu, 31 Jan 2019 15:42:05 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2019/Jan/31/t1548945745kv6wvbi49i3eqtk.htm/, Retrieved Sun, 05 May 2024 10:42:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=318182, Retrieved Sun, 05 May 2024 10:42:50 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact19
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2019-01-31 14:42:05] [23a8c4e2b29930b56218fe862c106e41] [Current]
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Dataseries X:
-41.3595108897757
-387.129682371266
13.9484713282546
169.87927586997
-27.8671455235496
-31.1843768059098
-103.039017853765
-9.37565390540148
-126.215439485854
188.524230930017
191.284005758707
202.637739833286
-253.766440293332
855.649399822356
237.488490967571
-47.5819803969269
-75.3617179222965
-60.4590783121464
-2.85257454545707
-114.226031973744
-60.9106247857234
-164.123552863937
145.236228046181
100.582746174375
4.62533509248441
-330.778674478512
-88.4307502664657
74.3476036835657
-122.435237210785
11.0286692350419
-111.428610521214
-96.2667653110901
-111.802499926871
-107.89743986771
-138.963560192061
19.2362266944854
68.3892642971164
-28.9203149932851
-166.675278759561
-98.6294906905193
141.905242923579
25.0960679978961
121.083658664582
85.3166421980945
139.510954662882
50.9613982052512
-219.230955912971
39.2880382555886
222.111351793507
-108.820727979293
3.66906673020089
-98.0154084660891
83.7588577330526
55.5187178851181
96.2365442558538
134.551808992141
159.417609535566
32.5353635963789
21.6742823001448
-361.744750957735




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time3 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=318182&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]3 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=318182&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=318182&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R ServerBig Analytics Cloud Computing Center







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean1.26464e-1423.09725.47529e-16
Geometric MeanNaN
Harmonic Mean262.036
Quadratic Mean177.413
Winsorized Mean ( 1 / 20 )-9.879618.3185-0.539323
Winsorized Mean ( 2 / 20 )-9.3599717.8782-0.523541
Winsorized Mean ( 3 / 20 )-6.4830416.5904-0.39077
Winsorized Mean ( 4 / 20 )-4.9375915.8754-0.31102
Winsorized Mean ( 5 / 20 )-0.78792914.9099-0.0528459
Winsorized Mean ( 6 / 20 )-2.3972514.4728-0.165638
Winsorized Mean ( 7 / 20 )-0.68244713.6989-0.0498176
Winsorized Mean ( 8 / 20 )-0.87354813.0481-0.0669485
Winsorized Mean ( 9 / 20 )-0.80616612.8621-0.0626778
Winsorized Mean ( 10 / 20 )0.16298712.57190.0129644
Winsorized Mean ( 11 / 20 )-0.30187512.3339-0.0244752
Winsorized Mean ( 12 / 20 )-2.9207311.8334-0.246822
Winsorized Mean ( 13 / 20 )-6.7975510.9814-0.619003
Winsorized Mean ( 14 / 20 )-7.5962310.7807-0.704616
Winsorized Mean ( 15 / 20 )-9.111610.1514-0.897572
Winsorized Mean ( 16 / 20 )-8.351149.90283-0.843308
Winsorized Mean ( 17 / 20 )-10.84379.46201-1.14602
Winsorized Mean ( 18 / 20 )-12.10669.10969-1.32898
Winsorized Mean ( 19 / 20 )-13.70088.12168-1.68695
Winsorized Mean ( 20 / 20 )-10.86367.2324-1.50208
Trimmed Mean ( 1 / 20 )-8.0779317.4156-0.463832
Trimmed Mean ( 2 / 20 )-6.1475616.2881-0.377426
Trimmed Mean ( 3 / 20 )-4.3628915.1797-0.287416
Trimmed Mean ( 4 / 20 )-3.5474514.4584-0.245356
Trimmed Mean ( 5 / 20 )-3.1304113.849-0.226038
Trimmed Mean ( 6 / 20 )-3.7160313.4218-0.276866
Trimmed Mean ( 7 / 20 )-4.0027213.0131-0.307592
Trimmed Mean ( 8 / 20 )-4.6495312.7091-0.365844
Trimmed Mean ( 9 / 20 )-5.3238112.483-0.426483
Trimmed Mean ( 10 / 20 )-6.0767512.2191-0.497315
Trimmed Mean ( 11 / 20 )-7.0619711.9265-0.592127
Trimmed Mean ( 12 / 20 )-8.0862311.5788-0.698364
Trimmed Mean ( 13 / 20 )-8.8458611.2318-0.787576
Trimmed Mean ( 14 / 20 )-9.1412910.9788-0.832628
Trimmed Mean ( 15 / 20 )-9.3620110.6519-0.878909
Trimmed Mean ( 16 / 20 )-9.3977910.3492-0.908067
Trimmed Mean ( 17 / 20 )-9.548759.94844-0.959824
Trimmed Mean ( 18 / 20 )-9.358329.46634-0.988589
Trimmed Mean ( 19 / 20 )-8.941918.81066-1.0149
Trimmed Mean ( 20 / 20 )-8.19058.17233-1.00222
Median0.408246
Midrange234.26
Midmean - Weighted Average at Xnp-12.5406
Midmean - Weighted Average at X(n+1)p-9.36201
Midmean - Empirical Distribution Function-12.5406
Midmean - Empirical Distribution Function - Averaging-9.36201
Midmean - Empirical Distribution Function - Interpolation-9.36201
Midmean - Closest Observation-12.5406
Midmean - True Basic - Statistics Graphics Toolkit-9.36201
Midmean - MS Excel (old versions)-9.14129
Number of observations60

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 1.26464e-14 & 23.0972 & 5.47529e-16 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 262.036 &  &  \tabularnewline
Quadratic Mean & 177.413 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & -9.8796 & 18.3185 & -0.539323 \tabularnewline
Winsorized Mean ( 2 / 20 ) & -9.35997 & 17.8782 & -0.523541 \tabularnewline
Winsorized Mean ( 3 / 20 ) & -6.48304 & 16.5904 & -0.39077 \tabularnewline
Winsorized Mean ( 4 / 20 ) & -4.93759 & 15.8754 & -0.31102 \tabularnewline
Winsorized Mean ( 5 / 20 ) & -0.787929 & 14.9099 & -0.0528459 \tabularnewline
Winsorized Mean ( 6 / 20 ) & -2.39725 & 14.4728 & -0.165638 \tabularnewline
Winsorized Mean ( 7 / 20 ) & -0.682447 & 13.6989 & -0.0498176 \tabularnewline
Winsorized Mean ( 8 / 20 ) & -0.873548 & 13.0481 & -0.0669485 \tabularnewline
Winsorized Mean ( 9 / 20 ) & -0.806166 & 12.8621 & -0.0626778 \tabularnewline
Winsorized Mean ( 10 / 20 ) & 0.162987 & 12.5719 & 0.0129644 \tabularnewline
Winsorized Mean ( 11 / 20 ) & -0.301875 & 12.3339 & -0.0244752 \tabularnewline
Winsorized Mean ( 12 / 20 ) & -2.92073 & 11.8334 & -0.246822 \tabularnewline
Winsorized Mean ( 13 / 20 ) & -6.79755 & 10.9814 & -0.619003 \tabularnewline
Winsorized Mean ( 14 / 20 ) & -7.59623 & 10.7807 & -0.704616 \tabularnewline
Winsorized Mean ( 15 / 20 ) & -9.1116 & 10.1514 & -0.897572 \tabularnewline
Winsorized Mean ( 16 / 20 ) & -8.35114 & 9.90283 & -0.843308 \tabularnewline
Winsorized Mean ( 17 / 20 ) & -10.8437 & 9.46201 & -1.14602 \tabularnewline
Winsorized Mean ( 18 / 20 ) & -12.1066 & 9.10969 & -1.32898 \tabularnewline
Winsorized Mean ( 19 / 20 ) & -13.7008 & 8.12168 & -1.68695 \tabularnewline
Winsorized Mean ( 20 / 20 ) & -10.8636 & 7.2324 & -1.50208 \tabularnewline
Trimmed Mean ( 1 / 20 ) & -8.07793 & 17.4156 & -0.463832 \tabularnewline
Trimmed Mean ( 2 / 20 ) & -6.14756 & 16.2881 & -0.377426 \tabularnewline
Trimmed Mean ( 3 / 20 ) & -4.36289 & 15.1797 & -0.287416 \tabularnewline
Trimmed Mean ( 4 / 20 ) & -3.54745 & 14.4584 & -0.245356 \tabularnewline
Trimmed Mean ( 5 / 20 ) & -3.13041 & 13.849 & -0.226038 \tabularnewline
Trimmed Mean ( 6 / 20 ) & -3.71603 & 13.4218 & -0.276866 \tabularnewline
Trimmed Mean ( 7 / 20 ) & -4.00272 & 13.0131 & -0.307592 \tabularnewline
Trimmed Mean ( 8 / 20 ) & -4.64953 & 12.7091 & -0.365844 \tabularnewline
Trimmed Mean ( 9 / 20 ) & -5.32381 & 12.483 & -0.426483 \tabularnewline
Trimmed Mean ( 10 / 20 ) & -6.07675 & 12.2191 & -0.497315 \tabularnewline
Trimmed Mean ( 11 / 20 ) & -7.06197 & 11.9265 & -0.592127 \tabularnewline
Trimmed Mean ( 12 / 20 ) & -8.08623 & 11.5788 & -0.698364 \tabularnewline
Trimmed Mean ( 13 / 20 ) & -8.84586 & 11.2318 & -0.787576 \tabularnewline
Trimmed Mean ( 14 / 20 ) & -9.14129 & 10.9788 & -0.832628 \tabularnewline
Trimmed Mean ( 15 / 20 ) & -9.36201 & 10.6519 & -0.878909 \tabularnewline
Trimmed Mean ( 16 / 20 ) & -9.39779 & 10.3492 & -0.908067 \tabularnewline
Trimmed Mean ( 17 / 20 ) & -9.54875 & 9.94844 & -0.959824 \tabularnewline
Trimmed Mean ( 18 / 20 ) & -9.35832 & 9.46634 & -0.988589 \tabularnewline
Trimmed Mean ( 19 / 20 ) & -8.94191 & 8.81066 & -1.0149 \tabularnewline
Trimmed Mean ( 20 / 20 ) & -8.1905 & 8.17233 & -1.00222 \tabularnewline
Median & 0.408246 &  &  \tabularnewline
Midrange & 234.26 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -12.5406 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -9.36201 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -12.5406 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -9.36201 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -9.36201 &  &  \tabularnewline
Midmean - Closest Observation & -12.5406 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -9.36201 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -9.14129 &  &  \tabularnewline
Number of observations & 60 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=318182&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]1.26464e-14[/C][C]23.0972[/C][C]5.47529e-16[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]262.036[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]177.413[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]-9.8796[/C][C]18.3185[/C][C]-0.539323[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]-9.35997[/C][C]17.8782[/C][C]-0.523541[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]-6.48304[/C][C]16.5904[/C][C]-0.39077[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]-4.93759[/C][C]15.8754[/C][C]-0.31102[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]-0.787929[/C][C]14.9099[/C][C]-0.0528459[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]-2.39725[/C][C]14.4728[/C][C]-0.165638[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]-0.682447[/C][C]13.6989[/C][C]-0.0498176[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]-0.873548[/C][C]13.0481[/C][C]-0.0669485[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]-0.806166[/C][C]12.8621[/C][C]-0.0626778[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]0.162987[/C][C]12.5719[/C][C]0.0129644[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]-0.301875[/C][C]12.3339[/C][C]-0.0244752[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]-2.92073[/C][C]11.8334[/C][C]-0.246822[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]-6.79755[/C][C]10.9814[/C][C]-0.619003[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]-7.59623[/C][C]10.7807[/C][C]-0.704616[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]-9.1116[/C][C]10.1514[/C][C]-0.897572[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]-8.35114[/C][C]9.90283[/C][C]-0.843308[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]-10.8437[/C][C]9.46201[/C][C]-1.14602[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]-12.1066[/C][C]9.10969[/C][C]-1.32898[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]-13.7008[/C][C]8.12168[/C][C]-1.68695[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]-10.8636[/C][C]7.2324[/C][C]-1.50208[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]-8.07793[/C][C]17.4156[/C][C]-0.463832[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]-6.14756[/C][C]16.2881[/C][C]-0.377426[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]-4.36289[/C][C]15.1797[/C][C]-0.287416[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]-3.54745[/C][C]14.4584[/C][C]-0.245356[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]-3.13041[/C][C]13.849[/C][C]-0.226038[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]-3.71603[/C][C]13.4218[/C][C]-0.276866[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]-4.00272[/C][C]13.0131[/C][C]-0.307592[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]-4.64953[/C][C]12.7091[/C][C]-0.365844[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]-5.32381[/C][C]12.483[/C][C]-0.426483[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]-6.07675[/C][C]12.2191[/C][C]-0.497315[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]-7.06197[/C][C]11.9265[/C][C]-0.592127[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]-8.08623[/C][C]11.5788[/C][C]-0.698364[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]-8.84586[/C][C]11.2318[/C][C]-0.787576[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]-9.14129[/C][C]10.9788[/C][C]-0.832628[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]-9.36201[/C][C]10.6519[/C][C]-0.878909[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]-9.39779[/C][C]10.3492[/C][C]-0.908067[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]-9.54875[/C][C]9.94844[/C][C]-0.959824[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]-9.35832[/C][C]9.46634[/C][C]-0.988589[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]-8.94191[/C][C]8.81066[/C][C]-1.0149[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]-8.1905[/C][C]8.17233[/C][C]-1.00222[/C][/ROW]
[ROW][C]Median[/C][C]0.408246[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]234.26[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-12.5406[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-9.36201[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-12.5406[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-9.36201[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-9.36201[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-12.5406[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-9.36201[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-9.14129[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]60[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=318182&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=318182&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 Mean1.26464e-1423.09725.47529e-16
Geometric MeanNaN
Harmonic Mean262.036
Quadratic Mean177.413
Winsorized Mean ( 1 / 20 )-9.879618.3185-0.539323
Winsorized Mean ( 2 / 20 )-9.3599717.8782-0.523541
Winsorized Mean ( 3 / 20 )-6.4830416.5904-0.39077
Winsorized Mean ( 4 / 20 )-4.9375915.8754-0.31102
Winsorized Mean ( 5 / 20 )-0.78792914.9099-0.0528459
Winsorized Mean ( 6 / 20 )-2.3972514.4728-0.165638
Winsorized Mean ( 7 / 20 )-0.68244713.6989-0.0498176
Winsorized Mean ( 8 / 20 )-0.87354813.0481-0.0669485
Winsorized Mean ( 9 / 20 )-0.80616612.8621-0.0626778
Winsorized Mean ( 10 / 20 )0.16298712.57190.0129644
Winsorized Mean ( 11 / 20 )-0.30187512.3339-0.0244752
Winsorized Mean ( 12 / 20 )-2.9207311.8334-0.246822
Winsorized Mean ( 13 / 20 )-6.7975510.9814-0.619003
Winsorized Mean ( 14 / 20 )-7.5962310.7807-0.704616
Winsorized Mean ( 15 / 20 )-9.111610.1514-0.897572
Winsorized Mean ( 16 / 20 )-8.351149.90283-0.843308
Winsorized Mean ( 17 / 20 )-10.84379.46201-1.14602
Winsorized Mean ( 18 / 20 )-12.10669.10969-1.32898
Winsorized Mean ( 19 / 20 )-13.70088.12168-1.68695
Winsorized Mean ( 20 / 20 )-10.86367.2324-1.50208
Trimmed Mean ( 1 / 20 )-8.0779317.4156-0.463832
Trimmed Mean ( 2 / 20 )-6.1475616.2881-0.377426
Trimmed Mean ( 3 / 20 )-4.3628915.1797-0.287416
Trimmed Mean ( 4 / 20 )-3.5474514.4584-0.245356
Trimmed Mean ( 5 / 20 )-3.1304113.849-0.226038
Trimmed Mean ( 6 / 20 )-3.7160313.4218-0.276866
Trimmed Mean ( 7 / 20 )-4.0027213.0131-0.307592
Trimmed Mean ( 8 / 20 )-4.6495312.7091-0.365844
Trimmed Mean ( 9 / 20 )-5.3238112.483-0.426483
Trimmed Mean ( 10 / 20 )-6.0767512.2191-0.497315
Trimmed Mean ( 11 / 20 )-7.0619711.9265-0.592127
Trimmed Mean ( 12 / 20 )-8.0862311.5788-0.698364
Trimmed Mean ( 13 / 20 )-8.8458611.2318-0.787576
Trimmed Mean ( 14 / 20 )-9.1412910.9788-0.832628
Trimmed Mean ( 15 / 20 )-9.3620110.6519-0.878909
Trimmed Mean ( 16 / 20 )-9.3977910.3492-0.908067
Trimmed Mean ( 17 / 20 )-9.548759.94844-0.959824
Trimmed Mean ( 18 / 20 )-9.358329.46634-0.988589
Trimmed Mean ( 19 / 20 )-8.941918.81066-1.0149
Trimmed Mean ( 20 / 20 )-8.19058.17233-1.00222
Median0.408246
Midrange234.26
Midmean - Weighted Average at Xnp-12.5406
Midmean - Weighted Average at X(n+1)p-9.36201
Midmean - Empirical Distribution Function-12.5406
Midmean - Empirical Distribution Function - Averaging-9.36201
Midmean - Empirical Distribution Function - Interpolation-9.36201
Midmean - Closest Observation-12.5406
Midmean - True Basic - Statistics Graphics Toolkit-9.36201
Midmean - MS Excel (old versions)-9.14129
Number of observations60



Parameters (Session):
par1 = 12 ; par2 = Triple ; par3 = additive ; par4 = 12 ;
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,'Arithmetic Mean',header=TRUE)
a<-table.element(a,signif(arm,6))
a<-table.element(a, signif(armse,6))
a<-table.element(a,signif(armose,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Geometric Mean',header=TRUE)
a<-table.element(a,signif(geo,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Harmonic Mean',header=TRUE)
a<-table.element(a,signif(har,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Quadratic Mean',header=TRUE)
a<-table.element(a,signif(qua,6))
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, mylabel,header=TRUE)
a<-table.element(a,signif(win[j,1],6))
a<-table.element(a,signif(win[j,2],6))
a<-table.element(a,signif(win[j,1]/win[j,2],6))
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, mylabel,header=TRUE)
a<-table.element(a,signif(tri[j,1],6))
a<-table.element(a,signif(tri[j,2],6))
a<-table.element(a,signif(tri[j,1]/tri[j,2],6))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'Median',header=TRUE)
a<-table.element(a,signif(median(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Midrange',header=TRUE)
a<-table.element(a,signif(midr,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Weighted Average at Xnp',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[1],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Weighted Average at X(n+1)p',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[2],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[3],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Averaging',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[4],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Interpolation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[5],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Closest Observation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[6],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'True Basic - Statistics Graphics Toolkit',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[7],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'MS Excel (old versions)',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[8],6))
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,signif(length(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')