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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 computationTue, 20 Oct 2009 11:29:56 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Oct/20/t1256059888e93lw79nsauqmpl.htm/, Retrieved Thu, 02 May 2024 21:17:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=48862, Retrieved Thu, 02 May 2024 21:17:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
F RMPD  [Univariate Explorative Data Analysis] [Colombia Coffee] [2008-01-07 14:21:11] [74be16979710d4c4e7c6647856088456]
F RMPD    [Univariate Data Series] [] [2009-10-14 08:30:28] [74be16979710d4c4e7c6647856088456]
- RMPD      [Central Tendency] [WS3 Part2 Vraag1] [2009-10-18 08:54:29] [42ad1186d39724f834063794eac7cea3]
- RMP         [Univariate Explorative Data Analysis] [WS3 Part2 Vraag1 TVD] [2009-10-20 17:08:04] [42ad1186d39724f834063794eac7cea3]
- RMPD            [Central Tendency] [WS3 Part2 Vraag1 C] [2009-10-20 17:29:56] [37de18e38c1490dd77c2b362ed87f3bb] [Current]
-                   [Central Tendency] [WS3 part 2 vraag 2c] [2009-10-21 06:17:21] [f5d341d4bbba73282fc6e80153a6d315]
-                   [Central Tendency] [BDM 6] [2009-10-21 08:35:49] [f5d341d4bbba73282fc6e80153a6d315]
-  M                  [Central Tendency] [bart] [2010-01-25 07:18:59] [f5d341d4bbba73282fc6e80153a6d315]
-                   [Central Tendency] [TG 6] [2009-10-21 09:00:29] [a21bac9c8d3d56fdec8be4e719e2c7ed]
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Dataseries X:
-17.676666666667
-12.676666666667
-24.976666666667
-16.176666666667
-16.976666666667
-13.876666666667
-26.576666666667
-37.576666666667
-13.176666666667
1.323333333333
-18.276666666667
-30.176666666667
-24.676666666667
-19.076666666667
-15.576666666667
-15.676666666667
-20.176666666667
-14.776666666667
-27.776666666667
-44.276666666667
-10.476666666667
-4.476666666667
-22.076666666667
-29.376666666667
-21.876666666667
-18.676666666667
3.623333333333
-3.576666666667
-9.976666666667
10.123333333333
-16.176666666667
-22.776666666667
8.723333333333
9.923333333333
7.523333333333
0.823333333333
-5.776666666667
-4.876666666667
15.123333333333
11.023333333333
2.823333333333
13.123333333333
-13.676666666667
-15.976666666667
-1.876666666667
7.323333333333
19.123333333333
0.523333333333
19.023333333333
16.523333333333
59.623333333333
43.223333333333
57.923333333333
85.923333333333
13.223333333333
23.523333333333
45.323333333333
55.923333333333
56.423333333333
24.023333333333




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=48862&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=48862&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=48862&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'George Udny Yule' @ 72.249.76.132







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-3.33361694730231e-133.43066461471851-9.71711700700838e-14
Geometric MeanNaN
Harmonic Mean21.7639958847098
Quadratic Mean26.3514349177084
Winsorized Mean ( 1 / 20 )-0.3266666666673.24521333728921-0.100661076088104
Winsorized Mean ( 2 / 20 )-0.1366666666670003.18382493911613-0.0429253081687778
Winsorized Mean ( 3 / 20 )-0.1716666666673.1544931858996-0.0544197297475042
Winsorized Mean ( 4 / 20 )-0.0983333333336673.12799649932855-0.0314365228205258
Winsorized Mean ( 5 / 20 )-0.8816666666672.85716408032876-0.308581041157969
Winsorized Mean ( 6 / 20 )-0.9316666666672.77612645737629-0.335599505631856
Winsorized Mean ( 7 / 20 )-3.1366666666672.22986179298611-1.40666416032294
Winsorized Mean ( 8 / 20 )-2.950000000000332.17578983212924-1.35582948152370
Winsorized Mean ( 9 / 20 )-3.505000000000332.02890425976484-1.72753346203068
Winsorized Mean ( 10 / 20 )-3.488333333333672.02059885354078-1.72638588170082
Winsorized Mean ( 11 / 20 )-3.635000000000331.88860438064496-1.92470166714268
Winsorized Mean ( 12 / 20 )-3.695000000000331.80632675258377-2.04558781777163
Winsorized Mean ( 13 / 20 )-4.020000000000331.72252010667242-2.33378988403578
Winsorized Mean ( 14 / 20 )-3.950000000000331.70518462752160-2.31646470197275
Winsorized Mean ( 15 / 20 )-4.325000000000331.59649243296429-2.70906388949798
Winsorized Mean ( 16 / 20 )-4.378333333333671.53142504380183-2.85899290406292
Winsorized Mean ( 17 / 20 )-4.208333333333671.49110070379275-2.82229987728488
Winsorized Mean ( 18 / 20 )-4.568333333333671.43389417158028-3.185962690886
Winsorized Mean ( 19 / 20 )-4.885000000000331.36607460994071-3.57593938460824
Winsorized Mean ( 20 / 20 )-4.8516666666671.3421010280495-3.61497872758358
Trimmed Mean ( 1 / 20 )-0.7180459770118283.12527025762554-0.229754842884331
Trimmed Mean ( 2 / 20 )-1.137380952381292.97616361459740-0.382163449214517
Trimmed Mean ( 3 / 20 )-1.693333333333672.83071867271425-0.598199089742114
Trimmed Mean ( 4 / 20 )-2.278589743590082.66048891840426-0.85645526573242
Trimmed Mean ( 5 / 20 )-2.9326666666672.45052124401053-1.19675219051249
Trimmed Mean ( 6 / 20 )-3.4454166666672.28819851608745-1.50573328425990
Trimmed Mean ( 7 / 20 )-3.991884057971352.10322725884091-1.89798037334838
Trimmed Mean ( 8 / 20 )-4.158484848485182.04893174024583-2.02958681678007
Trimmed Mean ( 9 / 20 )-4.374285714286051.99126573680049-2.19673629362725
Trimmed Mean ( 10 / 20 )-4.5191666666671.95487847186049-2.31173790684085
Trimmed Mean ( 11 / 20 )-4.681929824561741.90549832331289-2.45706320875778
Trimmed Mean ( 12 / 20 )-4.840555555555891.87176664185256-2.58608923106194
Trimmed Mean ( 13 / 20 )-5.009019607843471.84328874012441-2.71743623167003
Trimmed Mean ( 14 / 20 )-5.1516666666671.82178793780247-2.82780808883892
Trimmed Mean ( 15 / 20 )-5.323333333333671.78925100449549-2.97517414826584
Trimmed Mean ( 16 / 20 )-5.465952380952711.76864473931533-3.09047501708493
Trimmed Mean ( 17 / 20 )-5.622820512820851.74914687573669-3.21460741280099
Trimmed Mean ( 18 / 20 )-5.830833333333671.72081227835665-3.38841918242357
Trimmed Mean ( 19 / 20 )-6.022121212121551.68704931160051-3.56961777626307
Trimmed Mean ( 20 / 20 )-6.2016666666671.64772370895506-3.7637782553969
Median-5.326666666667
Midrange20.823333333333
Midmean - Weighted Average at Xnp-5.74118279569926
Midmean - Weighted Average at X(n+1)p-5.32333333333367
Midmean - Empirical Distribution Function-5.74118279569926
Midmean - Empirical Distribution Function - Averaging-5.32333333333367
Midmean - Empirical Distribution Function - Interpolation-5.32333333333367
Midmean - Closest Observation-5.74118279569926
Midmean - True Basic - Statistics Graphics Toolkit-5.32333333333367
Midmean - MS Excel (old versions)-5.151666666667
Number of observations60

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -3.33361694730231e-13 & 3.43066461471851 & -9.71711700700838e-14 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 21.7639958847098 &  &  \tabularnewline
Quadratic Mean & 26.3514349177084 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & -0.326666666667 & 3.24521333728921 & -0.100661076088104 \tabularnewline
Winsorized Mean ( 2 / 20 ) & -0.136666666667000 & 3.18382493911613 & -0.0429253081687778 \tabularnewline
Winsorized Mean ( 3 / 20 ) & -0.171666666667 & 3.1544931858996 & -0.0544197297475042 \tabularnewline
Winsorized Mean ( 4 / 20 ) & -0.098333333333667 & 3.12799649932855 & -0.0314365228205258 \tabularnewline
Winsorized Mean ( 5 / 20 ) & -0.881666666667 & 2.85716408032876 & -0.308581041157969 \tabularnewline
Winsorized Mean ( 6 / 20 ) & -0.931666666667 & 2.77612645737629 & -0.335599505631856 \tabularnewline
Winsorized Mean ( 7 / 20 ) & -3.136666666667 & 2.22986179298611 & -1.40666416032294 \tabularnewline
Winsorized Mean ( 8 / 20 ) & -2.95000000000033 & 2.17578983212924 & -1.35582948152370 \tabularnewline
Winsorized Mean ( 9 / 20 ) & -3.50500000000033 & 2.02890425976484 & -1.72753346203068 \tabularnewline
Winsorized Mean ( 10 / 20 ) & -3.48833333333367 & 2.02059885354078 & -1.72638588170082 \tabularnewline
Winsorized Mean ( 11 / 20 ) & -3.63500000000033 & 1.88860438064496 & -1.92470166714268 \tabularnewline
Winsorized Mean ( 12 / 20 ) & -3.69500000000033 & 1.80632675258377 & -2.04558781777163 \tabularnewline
Winsorized Mean ( 13 / 20 ) & -4.02000000000033 & 1.72252010667242 & -2.33378988403578 \tabularnewline
Winsorized Mean ( 14 / 20 ) & -3.95000000000033 & 1.70518462752160 & -2.31646470197275 \tabularnewline
Winsorized Mean ( 15 / 20 ) & -4.32500000000033 & 1.59649243296429 & -2.70906388949798 \tabularnewline
Winsorized Mean ( 16 / 20 ) & -4.37833333333367 & 1.53142504380183 & -2.85899290406292 \tabularnewline
Winsorized Mean ( 17 / 20 ) & -4.20833333333367 & 1.49110070379275 & -2.82229987728488 \tabularnewline
Winsorized Mean ( 18 / 20 ) & -4.56833333333367 & 1.43389417158028 & -3.185962690886 \tabularnewline
Winsorized Mean ( 19 / 20 ) & -4.88500000000033 & 1.36607460994071 & -3.57593938460824 \tabularnewline
Winsorized Mean ( 20 / 20 ) & -4.851666666667 & 1.3421010280495 & -3.61497872758358 \tabularnewline
Trimmed Mean ( 1 / 20 ) & -0.718045977011828 & 3.12527025762554 & -0.229754842884331 \tabularnewline
Trimmed Mean ( 2 / 20 ) & -1.13738095238129 & 2.97616361459740 & -0.382163449214517 \tabularnewline
Trimmed Mean ( 3 / 20 ) & -1.69333333333367 & 2.83071867271425 & -0.598199089742114 \tabularnewline
Trimmed Mean ( 4 / 20 ) & -2.27858974359008 & 2.66048891840426 & -0.85645526573242 \tabularnewline
Trimmed Mean ( 5 / 20 ) & -2.932666666667 & 2.45052124401053 & -1.19675219051249 \tabularnewline
Trimmed Mean ( 6 / 20 ) & -3.445416666667 & 2.28819851608745 & -1.50573328425990 \tabularnewline
Trimmed Mean ( 7 / 20 ) & -3.99188405797135 & 2.10322725884091 & -1.89798037334838 \tabularnewline
Trimmed Mean ( 8 / 20 ) & -4.15848484848518 & 2.04893174024583 & -2.02958681678007 \tabularnewline
Trimmed Mean ( 9 / 20 ) & -4.37428571428605 & 1.99126573680049 & -2.19673629362725 \tabularnewline
Trimmed Mean ( 10 / 20 ) & -4.519166666667 & 1.95487847186049 & -2.31173790684085 \tabularnewline
Trimmed Mean ( 11 / 20 ) & -4.68192982456174 & 1.90549832331289 & -2.45706320875778 \tabularnewline
Trimmed Mean ( 12 / 20 ) & -4.84055555555589 & 1.87176664185256 & -2.58608923106194 \tabularnewline
Trimmed Mean ( 13 / 20 ) & -5.00901960784347 & 1.84328874012441 & -2.71743623167003 \tabularnewline
Trimmed Mean ( 14 / 20 ) & -5.151666666667 & 1.82178793780247 & -2.82780808883892 \tabularnewline
Trimmed Mean ( 15 / 20 ) & -5.32333333333367 & 1.78925100449549 & -2.97517414826584 \tabularnewline
Trimmed Mean ( 16 / 20 ) & -5.46595238095271 & 1.76864473931533 & -3.09047501708493 \tabularnewline
Trimmed Mean ( 17 / 20 ) & -5.62282051282085 & 1.74914687573669 & -3.21460741280099 \tabularnewline
Trimmed Mean ( 18 / 20 ) & -5.83083333333367 & 1.72081227835665 & -3.38841918242357 \tabularnewline
Trimmed Mean ( 19 / 20 ) & -6.02212121212155 & 1.68704931160051 & -3.56961777626307 \tabularnewline
Trimmed Mean ( 20 / 20 ) & -6.201666666667 & 1.64772370895506 & -3.7637782553969 \tabularnewline
Median & -5.326666666667 &  &  \tabularnewline
Midrange & 20.823333333333 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -5.74118279569926 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -5.32333333333367 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -5.74118279569926 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -5.32333333333367 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -5.32333333333367 &  &  \tabularnewline
Midmean - Closest Observation & -5.74118279569926 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -5.32333333333367 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -5.151666666667 &  &  \tabularnewline
Number of observations & 60 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=48862&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]-3.33361694730231e-13[/C][C]3.43066461471851[/C][C]-9.71711700700838e-14[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]21.7639958847098[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]26.3514349177084[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]-0.326666666667[/C][C]3.24521333728921[/C][C]-0.100661076088104[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]-0.136666666667000[/C][C]3.18382493911613[/C][C]-0.0429253081687778[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]-0.171666666667[/C][C]3.1544931858996[/C][C]-0.0544197297475042[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]-0.098333333333667[/C][C]3.12799649932855[/C][C]-0.0314365228205258[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]-0.881666666667[/C][C]2.85716408032876[/C][C]-0.308581041157969[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]-0.931666666667[/C][C]2.77612645737629[/C][C]-0.335599505631856[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]-3.136666666667[/C][C]2.22986179298611[/C][C]-1.40666416032294[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]-2.95000000000033[/C][C]2.17578983212924[/C][C]-1.35582948152370[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]-3.50500000000033[/C][C]2.02890425976484[/C][C]-1.72753346203068[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]-3.48833333333367[/C][C]2.02059885354078[/C][C]-1.72638588170082[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]-3.63500000000033[/C][C]1.88860438064496[/C][C]-1.92470166714268[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]-3.69500000000033[/C][C]1.80632675258377[/C][C]-2.04558781777163[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]-4.02000000000033[/C][C]1.72252010667242[/C][C]-2.33378988403578[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]-3.95000000000033[/C][C]1.70518462752160[/C][C]-2.31646470197275[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]-4.32500000000033[/C][C]1.59649243296429[/C][C]-2.70906388949798[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]-4.37833333333367[/C][C]1.53142504380183[/C][C]-2.85899290406292[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]-4.20833333333367[/C][C]1.49110070379275[/C][C]-2.82229987728488[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]-4.56833333333367[/C][C]1.43389417158028[/C][C]-3.185962690886[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]-4.88500000000033[/C][C]1.36607460994071[/C][C]-3.57593938460824[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]-4.851666666667[/C][C]1.3421010280495[/C][C]-3.61497872758358[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]-0.718045977011828[/C][C]3.12527025762554[/C][C]-0.229754842884331[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]-1.13738095238129[/C][C]2.97616361459740[/C][C]-0.382163449214517[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]-1.69333333333367[/C][C]2.83071867271425[/C][C]-0.598199089742114[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]-2.27858974359008[/C][C]2.66048891840426[/C][C]-0.85645526573242[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]-2.932666666667[/C][C]2.45052124401053[/C][C]-1.19675219051249[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]-3.445416666667[/C][C]2.28819851608745[/C][C]-1.50573328425990[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]-3.99188405797135[/C][C]2.10322725884091[/C][C]-1.89798037334838[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]-4.15848484848518[/C][C]2.04893174024583[/C][C]-2.02958681678007[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]-4.37428571428605[/C][C]1.99126573680049[/C][C]-2.19673629362725[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]-4.519166666667[/C][C]1.95487847186049[/C][C]-2.31173790684085[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]-4.68192982456174[/C][C]1.90549832331289[/C][C]-2.45706320875778[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]-4.84055555555589[/C][C]1.87176664185256[/C][C]-2.58608923106194[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]-5.00901960784347[/C][C]1.84328874012441[/C][C]-2.71743623167003[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]-5.151666666667[/C][C]1.82178793780247[/C][C]-2.82780808883892[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]-5.32333333333367[/C][C]1.78925100449549[/C][C]-2.97517414826584[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]-5.46595238095271[/C][C]1.76864473931533[/C][C]-3.09047501708493[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]-5.62282051282085[/C][C]1.74914687573669[/C][C]-3.21460741280099[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]-5.83083333333367[/C][C]1.72081227835665[/C][C]-3.38841918242357[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]-6.02212121212155[/C][C]1.68704931160051[/C][C]-3.56961777626307[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]-6.201666666667[/C][C]1.64772370895506[/C][C]-3.7637782553969[/C][/ROW]
[ROW][C]Median[/C][C]-5.326666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]20.823333333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-5.74118279569926[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-5.32333333333367[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-5.74118279569926[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-5.32333333333367[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-5.32333333333367[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-5.74118279569926[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-5.32333333333367[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-5.151666666667[/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=48862&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=48862&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-3.33361694730231e-133.43066461471851-9.71711700700838e-14
Geometric MeanNaN
Harmonic Mean21.7639958847098
Quadratic Mean26.3514349177084
Winsorized Mean ( 1 / 20 )-0.3266666666673.24521333728921-0.100661076088104
Winsorized Mean ( 2 / 20 )-0.1366666666670003.18382493911613-0.0429253081687778
Winsorized Mean ( 3 / 20 )-0.1716666666673.1544931858996-0.0544197297475042
Winsorized Mean ( 4 / 20 )-0.0983333333336673.12799649932855-0.0314365228205258
Winsorized Mean ( 5 / 20 )-0.8816666666672.85716408032876-0.308581041157969
Winsorized Mean ( 6 / 20 )-0.9316666666672.77612645737629-0.335599505631856
Winsorized Mean ( 7 / 20 )-3.1366666666672.22986179298611-1.40666416032294
Winsorized Mean ( 8 / 20 )-2.950000000000332.17578983212924-1.35582948152370
Winsorized Mean ( 9 / 20 )-3.505000000000332.02890425976484-1.72753346203068
Winsorized Mean ( 10 / 20 )-3.488333333333672.02059885354078-1.72638588170082
Winsorized Mean ( 11 / 20 )-3.635000000000331.88860438064496-1.92470166714268
Winsorized Mean ( 12 / 20 )-3.695000000000331.80632675258377-2.04558781777163
Winsorized Mean ( 13 / 20 )-4.020000000000331.72252010667242-2.33378988403578
Winsorized Mean ( 14 / 20 )-3.950000000000331.70518462752160-2.31646470197275
Winsorized Mean ( 15 / 20 )-4.325000000000331.59649243296429-2.70906388949798
Winsorized Mean ( 16 / 20 )-4.378333333333671.53142504380183-2.85899290406292
Winsorized Mean ( 17 / 20 )-4.208333333333671.49110070379275-2.82229987728488
Winsorized Mean ( 18 / 20 )-4.568333333333671.43389417158028-3.185962690886
Winsorized Mean ( 19 / 20 )-4.885000000000331.36607460994071-3.57593938460824
Winsorized Mean ( 20 / 20 )-4.8516666666671.3421010280495-3.61497872758358
Trimmed Mean ( 1 / 20 )-0.7180459770118283.12527025762554-0.229754842884331
Trimmed Mean ( 2 / 20 )-1.137380952381292.97616361459740-0.382163449214517
Trimmed Mean ( 3 / 20 )-1.693333333333672.83071867271425-0.598199089742114
Trimmed Mean ( 4 / 20 )-2.278589743590082.66048891840426-0.85645526573242
Trimmed Mean ( 5 / 20 )-2.9326666666672.45052124401053-1.19675219051249
Trimmed Mean ( 6 / 20 )-3.4454166666672.28819851608745-1.50573328425990
Trimmed Mean ( 7 / 20 )-3.991884057971352.10322725884091-1.89798037334838
Trimmed Mean ( 8 / 20 )-4.158484848485182.04893174024583-2.02958681678007
Trimmed Mean ( 9 / 20 )-4.374285714286051.99126573680049-2.19673629362725
Trimmed Mean ( 10 / 20 )-4.5191666666671.95487847186049-2.31173790684085
Trimmed Mean ( 11 / 20 )-4.681929824561741.90549832331289-2.45706320875778
Trimmed Mean ( 12 / 20 )-4.840555555555891.87176664185256-2.58608923106194
Trimmed Mean ( 13 / 20 )-5.009019607843471.84328874012441-2.71743623167003
Trimmed Mean ( 14 / 20 )-5.1516666666671.82178793780247-2.82780808883892
Trimmed Mean ( 15 / 20 )-5.323333333333671.78925100449549-2.97517414826584
Trimmed Mean ( 16 / 20 )-5.465952380952711.76864473931533-3.09047501708493
Trimmed Mean ( 17 / 20 )-5.622820512820851.74914687573669-3.21460741280099
Trimmed Mean ( 18 / 20 )-5.830833333333671.72081227835665-3.38841918242357
Trimmed Mean ( 19 / 20 )-6.022121212121551.68704931160051-3.56961777626307
Trimmed Mean ( 20 / 20 )-6.2016666666671.64772370895506-3.7637782553969
Median-5.326666666667
Midrange20.823333333333
Midmean - Weighted Average at Xnp-5.74118279569926
Midmean - Weighted Average at X(n+1)p-5.32333333333367
Midmean - Empirical Distribution Function-5.74118279569926
Midmean - Empirical Distribution Function - Averaging-5.32333333333367
Midmean - Empirical Distribution Function - Interpolation-5.32333333333367
Midmean - Closest Observation-5.74118279569926
Midmean - True Basic - Statistics Graphics Toolkit-5.32333333333367
Midmean - MS Excel (old versions)-5.151666666667
Number of observations60



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')