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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 computationWed, 26 Nov 2014 11:36:03 +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/2014/Nov/26/t1417001769hkaph8ahpp0t9bw.htm/, Retrieved Sun, 12 May 2024 13:53:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=258861, Retrieved Sun, 12 May 2024 13:53:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact119
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2008-12-14 11:54:22] [d2d412c7f4d35ffbf5ee5ee89db327d4]
- RMP   [ARIMA Backward Selection] [] [2011-12-06 20:20:50] [b98453cac15ba1066b407e146608df68]
- RM      [ARIMA Backward Selection] [] [2014-11-26 11:14:51] [69bf0eb8b9b38defaaf4848d8c317571]
- RM D        [Central Tendency] [] [2014-11-26 11:36:03] [a36dddfa959c0d492544a38e0b694048] [Current]
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Dataseries X:
0.0589999409993744
-1.41417283069462
-18.3846258098951
4.24266274248771
-9.89939578474574
-1.41416434537675
-4.94967561841345
8.48526113798155
5.6568405229511
2.12134904898943
-12.7277987220306
-1.41417070936515
-5.65677971150633
5.71546032640338
11.4309039149365
4.08248670852126
-5.71542072585406
-4.8989269769415
5.30721957568224
-8.981389599054
-0.816479052257997
-3.67418839459477
2.4495000271965
-7.34840577481171
-12.2473531641919
13.5676634482613
-7.50549289979428
-10.1035485891738
4.61878873300742
-12.9902871076992
3.75277141979087
-14.1449840741378
-2.30937834467888
-11.2582458437863
-4.33008309713321
1.29910498821225e-05
16.4543982163007
7.82620221319958
4.02490961908129
-8.72059740556087
-0.894410396719857
-0.22359398826078
-6.93175537131864
-2.01244027251896
-7.15536769640425
0.223617694327785
8.2734152404356
15.2051806732589
2.90688309324049
-12.7801062066758
-3.10373286137738
-7.12033826025114
-3.46887932113659
-8.39835251454256
2.55603398508167
0.182580170109542
10.5892440586814
15.7012952305094
6.75521553624911
5.1120551863574
8.76351814514721




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=258861&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=258861&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=258861&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-0.7693454405027111.02890998543482-0.747728617073904
Geometric MeanNaN
Harmonic Mean0.000792268479706982
Quadratic Mean8.00694935006283
Winsorized Mean ( 1 / 20 )-0.7121890675524491.00785373073561-0.706639312663594
Winsorized Mean ( 2 / 20 )-0.6905962016774290.995375979341177-0.693804367405493
Winsorized Mean ( 3 / 20 )-0.7607930700696030.972633480295022-0.782199138198325
Winsorized Mean ( 4 / 20 )-0.8974784503108880.939362513547602-0.955412247526746
Winsorized Mean ( 5 / 20 )-0.9270861796892820.916400716459549-1.01166025193762
Winsorized Mean ( 6 / 20 )-1.009376533111770.860870305338299-1.17250708597169
Winsorized Mean ( 7 / 20 )-0.9088014227490140.829431911601758-1.09569141244395
Winsorized Mean ( 8 / 20 )-0.9098103529939830.819292721940547-1.11048265000944
Winsorized Mean ( 9 / 20 )-0.8403490673201880.782905197191206-1.07337270251248
Winsorized Mean ( 10 / 20 )-0.973167835100080.744072927671641-1.30789308266506
Winsorized Mean ( 11 / 20 )-1.102554941773880.702579883625919-1.56929477696364
Winsorized Mean ( 12 / 20 )-0.938442192010730.671161894570401-1.39823520912404
Winsorized Mean ( 13 / 20 )-0.979473990202890.653638582455434-1.49849475917324
Winsorized Mean ( 14 / 20 )-0.9799619959872060.639327467363008-1.53280133579931
Winsorized Mean ( 15 / 20 )-1.092643229724140.618971753550012-1.76525539890546
Winsorized Mean ( 16 / 20 )-1.141834862927340.595935274189355-1.91603838937135
Winsorized Mean ( 17 / 20 )-0.8474955777557350.535958954914856-1.5812695542896
Winsorized Mean ( 18 / 20 )-0.8471816327009850.530740430669773-1.59622592089296
Winsorized Mean ( 19 / 20 )-0.7117004526641540.485060629956722-1.46724019372105
Winsorized Mean ( 20 / 20 )-0.9724019887554420.440967107789572-2.20515764459119
Trimmed Mean ( 1 / 20 )-0.7627092250351010.977197956907072-0.780506364799566
Trimmed Mean ( 2 / 20 )-0.8167746567270630.939492525937663-0.869378557228945
Trimmed Mean ( 3 / 20 )-0.8867463454364050.901222504999877-0.983937196992796
Trimmed Mean ( 4 / 20 )-0.9350680422752410.86492158106949-1.08110152728414
Trimmed Mean ( 5 / 20 )-0.9463080673234060.83307651469779-1.1359197512208
Trimmed Mean ( 6 / 20 )-0.9510939250608810.800976847501508-1.1874174990546
Trimmed Mean ( 7 / 20 )-0.9384866942413640.777915505612531-1.20641211991577
Trimmed Mean ( 8 / 20 )-0.9442352706255960.75729879763238-1.24684638821249
Trimmed Mean ( 9 / 20 )-0.9503396891591090.733010345646829-1.29648878055125
Trimmed Mean ( 10 / 20 )-0.9685224206826170.710904748081982-1.36238001405348
Trimmed Mean ( 11 / 20 )-0.9677958302224490.691709876834442-1.39913547953297
Trimmed Mean ( 12 / 20 )-0.9475985186631440.676274975194577-1.40120299200854
Trimmed Mean ( 13 / 20 )-0.9489283661055190.662667559262281-1.43198252704859
Trimmed Mean ( 14 / 20 )-0.9445850489261720.647306006154836-1.4592558078323
Trimmed Mean ( 15 / 20 )-0.939612713048930.628372082427641-1.49531263295283
Trimmed Mean ( 16 / 20 )-0.918153261285280.605904162072526-1.51534404078805
Trimmed Mean ( 17 / 20 )-0.8865685906830440.578923445831909-1.53140902664436
Trimmed Mean ( 18 / 20 )-0.8921767172443760.558669318140597-1.59696745153964
Trimmed Mean ( 19 / 20 )-0.8988064277688850.526729512540343-1.706390863565
Trimmed Mean ( 20 / 20 )-0.9274116019077030.493584441850342-1.87893199881065
Median-0.894410396719857
Midrange-0.965113796797199
Midmean - Weighted Average at Xnp-1.12489276125081
Midmean - Weighted Average at X(n+1)p-0.93961271304893
Midmean - Empirical Distribution Function-0.93961271304893
Midmean - Empirical Distribution Function - Averaging-0.93961271304893
Midmean - Empirical Distribution Function - Interpolation-0.93961271304893
Midmean - Closest Observation-1.13385505627878
Midmean - True Basic - Statistics Graphics Toolkit-0.93961271304893
Midmean - MS Excel (old versions)-0.93961271304893
Number of observations61

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -0.769345440502711 & 1.02890998543482 & -0.747728617073904 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 0.000792268479706982 &  &  \tabularnewline
Quadratic Mean & 8.00694935006283 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & -0.712189067552449 & 1.00785373073561 & -0.706639312663594 \tabularnewline
Winsorized Mean ( 2 / 20 ) & -0.690596201677429 & 0.995375979341177 & -0.693804367405493 \tabularnewline
Winsorized Mean ( 3 / 20 ) & -0.760793070069603 & 0.972633480295022 & -0.782199138198325 \tabularnewline
Winsorized Mean ( 4 / 20 ) & -0.897478450310888 & 0.939362513547602 & -0.955412247526746 \tabularnewline
Winsorized Mean ( 5 / 20 ) & -0.927086179689282 & 0.916400716459549 & -1.01166025193762 \tabularnewline
Winsorized Mean ( 6 / 20 ) & -1.00937653311177 & 0.860870305338299 & -1.17250708597169 \tabularnewline
Winsorized Mean ( 7 / 20 ) & -0.908801422749014 & 0.829431911601758 & -1.09569141244395 \tabularnewline
Winsorized Mean ( 8 / 20 ) & -0.909810352993983 & 0.819292721940547 & -1.11048265000944 \tabularnewline
Winsorized Mean ( 9 / 20 ) & -0.840349067320188 & 0.782905197191206 & -1.07337270251248 \tabularnewline
Winsorized Mean ( 10 / 20 ) & -0.97316783510008 & 0.744072927671641 & -1.30789308266506 \tabularnewline
Winsorized Mean ( 11 / 20 ) & -1.10255494177388 & 0.702579883625919 & -1.56929477696364 \tabularnewline
Winsorized Mean ( 12 / 20 ) & -0.93844219201073 & 0.671161894570401 & -1.39823520912404 \tabularnewline
Winsorized Mean ( 13 / 20 ) & -0.97947399020289 & 0.653638582455434 & -1.49849475917324 \tabularnewline
Winsorized Mean ( 14 / 20 ) & -0.979961995987206 & 0.639327467363008 & -1.53280133579931 \tabularnewline
Winsorized Mean ( 15 / 20 ) & -1.09264322972414 & 0.618971753550012 & -1.76525539890546 \tabularnewline
Winsorized Mean ( 16 / 20 ) & -1.14183486292734 & 0.595935274189355 & -1.91603838937135 \tabularnewline
Winsorized Mean ( 17 / 20 ) & -0.847495577755735 & 0.535958954914856 & -1.5812695542896 \tabularnewline
Winsorized Mean ( 18 / 20 ) & -0.847181632700985 & 0.530740430669773 & -1.59622592089296 \tabularnewline
Winsorized Mean ( 19 / 20 ) & -0.711700452664154 & 0.485060629956722 & -1.46724019372105 \tabularnewline
Winsorized Mean ( 20 / 20 ) & -0.972401988755442 & 0.440967107789572 & -2.20515764459119 \tabularnewline
Trimmed Mean ( 1 / 20 ) & -0.762709225035101 & 0.977197956907072 & -0.780506364799566 \tabularnewline
Trimmed Mean ( 2 / 20 ) & -0.816774656727063 & 0.939492525937663 & -0.869378557228945 \tabularnewline
Trimmed Mean ( 3 / 20 ) & -0.886746345436405 & 0.901222504999877 & -0.983937196992796 \tabularnewline
Trimmed Mean ( 4 / 20 ) & -0.935068042275241 & 0.86492158106949 & -1.08110152728414 \tabularnewline
Trimmed Mean ( 5 / 20 ) & -0.946308067323406 & 0.83307651469779 & -1.1359197512208 \tabularnewline
Trimmed Mean ( 6 / 20 ) & -0.951093925060881 & 0.800976847501508 & -1.1874174990546 \tabularnewline
Trimmed Mean ( 7 / 20 ) & -0.938486694241364 & 0.777915505612531 & -1.20641211991577 \tabularnewline
Trimmed Mean ( 8 / 20 ) & -0.944235270625596 & 0.75729879763238 & -1.24684638821249 \tabularnewline
Trimmed Mean ( 9 / 20 ) & -0.950339689159109 & 0.733010345646829 & -1.29648878055125 \tabularnewline
Trimmed Mean ( 10 / 20 ) & -0.968522420682617 & 0.710904748081982 & -1.36238001405348 \tabularnewline
Trimmed Mean ( 11 / 20 ) & -0.967795830222449 & 0.691709876834442 & -1.39913547953297 \tabularnewline
Trimmed Mean ( 12 / 20 ) & -0.947598518663144 & 0.676274975194577 & -1.40120299200854 \tabularnewline
Trimmed Mean ( 13 / 20 ) & -0.948928366105519 & 0.662667559262281 & -1.43198252704859 \tabularnewline
Trimmed Mean ( 14 / 20 ) & -0.944585048926172 & 0.647306006154836 & -1.4592558078323 \tabularnewline
Trimmed Mean ( 15 / 20 ) & -0.93961271304893 & 0.628372082427641 & -1.49531263295283 \tabularnewline
Trimmed Mean ( 16 / 20 ) & -0.91815326128528 & 0.605904162072526 & -1.51534404078805 \tabularnewline
Trimmed Mean ( 17 / 20 ) & -0.886568590683044 & 0.578923445831909 & -1.53140902664436 \tabularnewline
Trimmed Mean ( 18 / 20 ) & -0.892176717244376 & 0.558669318140597 & -1.59696745153964 \tabularnewline
Trimmed Mean ( 19 / 20 ) & -0.898806427768885 & 0.526729512540343 & -1.706390863565 \tabularnewline
Trimmed Mean ( 20 / 20 ) & -0.927411601907703 & 0.493584441850342 & -1.87893199881065 \tabularnewline
Median & -0.894410396719857 &  &  \tabularnewline
Midrange & -0.965113796797199 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -1.12489276125081 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -0.93961271304893 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -0.93961271304893 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -0.93961271304893 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -0.93961271304893 &  &  \tabularnewline
Midmean - Closest Observation & -1.13385505627878 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -0.93961271304893 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -0.93961271304893 &  &  \tabularnewline
Number of observations & 61 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=258861&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]-0.769345440502711[/C][C]1.02890998543482[/C][C]-0.747728617073904[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]0.000792268479706982[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]8.00694935006283[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]-0.712189067552449[/C][C]1.00785373073561[/C][C]-0.706639312663594[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]-0.690596201677429[/C][C]0.995375979341177[/C][C]-0.693804367405493[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]-0.760793070069603[/C][C]0.972633480295022[/C][C]-0.782199138198325[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]-0.897478450310888[/C][C]0.939362513547602[/C][C]-0.955412247526746[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]-0.927086179689282[/C][C]0.916400716459549[/C][C]-1.01166025193762[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]-1.00937653311177[/C][C]0.860870305338299[/C][C]-1.17250708597169[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]-0.908801422749014[/C][C]0.829431911601758[/C][C]-1.09569141244395[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]-0.909810352993983[/C][C]0.819292721940547[/C][C]-1.11048265000944[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]-0.840349067320188[/C][C]0.782905197191206[/C][C]-1.07337270251248[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]-0.97316783510008[/C][C]0.744072927671641[/C][C]-1.30789308266506[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]-1.10255494177388[/C][C]0.702579883625919[/C][C]-1.56929477696364[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]-0.93844219201073[/C][C]0.671161894570401[/C][C]-1.39823520912404[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]-0.97947399020289[/C][C]0.653638582455434[/C][C]-1.49849475917324[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]-0.979961995987206[/C][C]0.639327467363008[/C][C]-1.53280133579931[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]-1.09264322972414[/C][C]0.618971753550012[/C][C]-1.76525539890546[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]-1.14183486292734[/C][C]0.595935274189355[/C][C]-1.91603838937135[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]-0.847495577755735[/C][C]0.535958954914856[/C][C]-1.5812695542896[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]-0.847181632700985[/C][C]0.530740430669773[/C][C]-1.59622592089296[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]-0.711700452664154[/C][C]0.485060629956722[/C][C]-1.46724019372105[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]-0.972401988755442[/C][C]0.440967107789572[/C][C]-2.20515764459119[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]-0.762709225035101[/C][C]0.977197956907072[/C][C]-0.780506364799566[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]-0.816774656727063[/C][C]0.939492525937663[/C][C]-0.869378557228945[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]-0.886746345436405[/C][C]0.901222504999877[/C][C]-0.983937196992796[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]-0.935068042275241[/C][C]0.86492158106949[/C][C]-1.08110152728414[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]-0.946308067323406[/C][C]0.83307651469779[/C][C]-1.1359197512208[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]-0.951093925060881[/C][C]0.800976847501508[/C][C]-1.1874174990546[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]-0.938486694241364[/C][C]0.777915505612531[/C][C]-1.20641211991577[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]-0.944235270625596[/C][C]0.75729879763238[/C][C]-1.24684638821249[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]-0.950339689159109[/C][C]0.733010345646829[/C][C]-1.29648878055125[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]-0.968522420682617[/C][C]0.710904748081982[/C][C]-1.36238001405348[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]-0.967795830222449[/C][C]0.691709876834442[/C][C]-1.39913547953297[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]-0.947598518663144[/C][C]0.676274975194577[/C][C]-1.40120299200854[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]-0.948928366105519[/C][C]0.662667559262281[/C][C]-1.43198252704859[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]-0.944585048926172[/C][C]0.647306006154836[/C][C]-1.4592558078323[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]-0.93961271304893[/C][C]0.628372082427641[/C][C]-1.49531263295283[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]-0.91815326128528[/C][C]0.605904162072526[/C][C]-1.51534404078805[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]-0.886568590683044[/C][C]0.578923445831909[/C][C]-1.53140902664436[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]-0.892176717244376[/C][C]0.558669318140597[/C][C]-1.59696745153964[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]-0.898806427768885[/C][C]0.526729512540343[/C][C]-1.706390863565[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]-0.927411601907703[/C][C]0.493584441850342[/C][C]-1.87893199881065[/C][/ROW]
[ROW][C]Median[/C][C]-0.894410396719857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-0.965113796797199[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-1.12489276125081[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-0.93961271304893[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-0.93961271304893[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-0.93961271304893[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-0.93961271304893[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-1.13385505627878[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-0.93961271304893[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-0.93961271304893[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]61[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=258861&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=258861&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 Mean-0.7693454405027111.02890998543482-0.747728617073904
Geometric MeanNaN
Harmonic Mean0.000792268479706982
Quadratic Mean8.00694935006283
Winsorized Mean ( 1 / 20 )-0.7121890675524491.00785373073561-0.706639312663594
Winsorized Mean ( 2 / 20 )-0.6905962016774290.995375979341177-0.693804367405493
Winsorized Mean ( 3 / 20 )-0.7607930700696030.972633480295022-0.782199138198325
Winsorized Mean ( 4 / 20 )-0.8974784503108880.939362513547602-0.955412247526746
Winsorized Mean ( 5 / 20 )-0.9270861796892820.916400716459549-1.01166025193762
Winsorized Mean ( 6 / 20 )-1.009376533111770.860870305338299-1.17250708597169
Winsorized Mean ( 7 / 20 )-0.9088014227490140.829431911601758-1.09569141244395
Winsorized Mean ( 8 / 20 )-0.9098103529939830.819292721940547-1.11048265000944
Winsorized Mean ( 9 / 20 )-0.8403490673201880.782905197191206-1.07337270251248
Winsorized Mean ( 10 / 20 )-0.973167835100080.744072927671641-1.30789308266506
Winsorized Mean ( 11 / 20 )-1.102554941773880.702579883625919-1.56929477696364
Winsorized Mean ( 12 / 20 )-0.938442192010730.671161894570401-1.39823520912404
Winsorized Mean ( 13 / 20 )-0.979473990202890.653638582455434-1.49849475917324
Winsorized Mean ( 14 / 20 )-0.9799619959872060.639327467363008-1.53280133579931
Winsorized Mean ( 15 / 20 )-1.092643229724140.618971753550012-1.76525539890546
Winsorized Mean ( 16 / 20 )-1.141834862927340.595935274189355-1.91603838937135
Winsorized Mean ( 17 / 20 )-0.8474955777557350.535958954914856-1.5812695542896
Winsorized Mean ( 18 / 20 )-0.8471816327009850.530740430669773-1.59622592089296
Winsorized Mean ( 19 / 20 )-0.7117004526641540.485060629956722-1.46724019372105
Winsorized Mean ( 20 / 20 )-0.9724019887554420.440967107789572-2.20515764459119
Trimmed Mean ( 1 / 20 )-0.7627092250351010.977197956907072-0.780506364799566
Trimmed Mean ( 2 / 20 )-0.8167746567270630.939492525937663-0.869378557228945
Trimmed Mean ( 3 / 20 )-0.8867463454364050.901222504999877-0.983937196992796
Trimmed Mean ( 4 / 20 )-0.9350680422752410.86492158106949-1.08110152728414
Trimmed Mean ( 5 / 20 )-0.9463080673234060.83307651469779-1.1359197512208
Trimmed Mean ( 6 / 20 )-0.9510939250608810.800976847501508-1.1874174990546
Trimmed Mean ( 7 / 20 )-0.9384866942413640.777915505612531-1.20641211991577
Trimmed Mean ( 8 / 20 )-0.9442352706255960.75729879763238-1.24684638821249
Trimmed Mean ( 9 / 20 )-0.9503396891591090.733010345646829-1.29648878055125
Trimmed Mean ( 10 / 20 )-0.9685224206826170.710904748081982-1.36238001405348
Trimmed Mean ( 11 / 20 )-0.9677958302224490.691709876834442-1.39913547953297
Trimmed Mean ( 12 / 20 )-0.9475985186631440.676274975194577-1.40120299200854
Trimmed Mean ( 13 / 20 )-0.9489283661055190.662667559262281-1.43198252704859
Trimmed Mean ( 14 / 20 )-0.9445850489261720.647306006154836-1.4592558078323
Trimmed Mean ( 15 / 20 )-0.939612713048930.628372082427641-1.49531263295283
Trimmed Mean ( 16 / 20 )-0.918153261285280.605904162072526-1.51534404078805
Trimmed Mean ( 17 / 20 )-0.8865685906830440.578923445831909-1.53140902664436
Trimmed Mean ( 18 / 20 )-0.8921767172443760.558669318140597-1.59696745153964
Trimmed Mean ( 19 / 20 )-0.8988064277688850.526729512540343-1.706390863565
Trimmed Mean ( 20 / 20 )-0.9274116019077030.493584441850342-1.87893199881065
Median-0.894410396719857
Midrange-0.965113796797199
Midmean - Weighted Average at Xnp-1.12489276125081
Midmean - Weighted Average at X(n+1)p-0.93961271304893
Midmean - Empirical Distribution Function-0.93961271304893
Midmean - Empirical Distribution Function - Averaging-0.93961271304893
Midmean - Empirical Distribution Function - Interpolation-0.93961271304893
Midmean - Closest Observation-1.13385505627878
Midmean - True Basic - Statistics Graphics Toolkit-0.93961271304893
Midmean - MS Excel (old versions)-0.93961271304893
Number of observations61



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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')