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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, 21 Oct 2009 03:03:03 -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/21/t1256115807it3i6u8lctysdj6.htm/, Retrieved Thu, 02 May 2024 02:50:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=49292, Retrieved Thu, 02 May 2024 02:50:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77
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 Vraag2 C] [2009-10-20 17:34:45] [42ad1186d39724f834063794eac7cea3]
-                   [Central Tendency] [TG 9] [2009-10-21 09:03:03] [81cf732ffd29c90ba583bd04c2d9af10] [Current]
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Post a new message
Dataseries X:
18.54166666666670
22.54166666666670
9.44166666666668
19.24166666666670
21.84166666666670
26.54166666666670
15.54166666666670
5.94166666666668
31.94166666666670
44.94166666666670
13.44166666666670
0.54166666666667
8.54166666666667
18.94166666666670
26.74166666666670
27.84166666666670
25.04166666666670
28.94166666666670
12.64166666666670
-2.95833333333333
30.64166666666670
36.54166666666670
10.14166666666670
2.94166666666666
3.34166666666667
-4.55833333333334
14.24166666666670
12.44166666666670
5.64166666666666
29.84166666666670
-1.45833333333333
-6.05833333333332
18.14166666666670
25.64166666666670
19.24166666666670
12.54166666666670
2.34166666666667
1.14166666666666
18.04166666666670
15.84166666666670
9.34166666666667
12.54166666666670
-22.05833333333330
-28.55833333333330
-16.75833333333330
-15.35833333333330
-3.55833333333332
-29.85833333333330
-26.55833333333330
-29.85833333333330
-3.65833333333335
-46.15833333333330
-45.05833333333330
-8.55833333333332
-86.65833333333330
-71.65833333333330
-48.85833333333330
-50.65833333333330
-41.55833333333330
-69.35833333333330




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49292&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=49292&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49292&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean2.4187943314935e-143.694836289628586.54641814113135e-15
Geometric MeanNaN
Harmonic Mean17.6511276741620
Quadratic Mean28.3805760551512
Winsorized Mean ( 1 / 20 )0.1100000000000243.575951133138050.0307610467549914
Winsorized Mean ( 2 / 20 )0.03333333333335753.525108718655750.00945597313267227
Winsorized Mean ( 3 / 20 )0.9033333333333583.231357738517190.279552252158834
Winsorized Mean ( 4 / 20 )0.9700000000000253.190999074610010.303980031745566
Winsorized Mean ( 5 / 20 )1.120000000000023.120910966953960.358869577459672
Winsorized Mean ( 6 / 20 )1.120000000000023.07638636394450.364063504222525
Winsorized Mean ( 7 / 20 )1.400000000000022.955334439252900.473719651287229
Winsorized Mean ( 8 / 20 )2.933333333333362.590172966833831.13248550227864
Winsorized Mean ( 9 / 20 )2.798333333333362.569573561167761.08902635659967
Winsorized Mean ( 10 / 20 )2.915000000000022.508183066993271.16219586933677
Winsorized Mean ( 11 / 20 )2.823333333333362.363835927449721.19438633644061
Winsorized Mean ( 12 / 20 )3.583333333333362.158301921547921.66025582313498
Winsorized Mean ( 13 / 20 )4.168333333333361.853009259151432.24949406633953
Winsorized Mean ( 14 / 20 )4.495000000000021.791048783221572.50970271837869
Winsorized Mean ( 15 / 20 )6.120000000000021.475747616079854.14705057512279
Winsorized Mean ( 16 / 20 )6.680000000000021.350338086284064.94690927246407
Winsorized Mean ( 17 / 20 )6.991666666666681.266590467526655.52006891408217
Winsorized Mean ( 18 / 20 )7.231666666666681.220816851665615.92362945907914
Winsorized Mean ( 19 / 20 )6.566666666666691.114429308487455.89240305926558
Winsorized Mean ( 20 / 20 )6.666666666666681.069691927243096.2323239961702
Trimmed Mean ( 1 / 20 )0.7192528735632423.424406230940430.210037251732753
Trimmed Mean ( 2 / 20 )1.372023809523833.234472316547490.424187835061871
Trimmed Mean ( 3 / 20 )2.115740740740763.028817087623620.698536979795222
Trimmed Mean ( 4 / 20 )2.582051282051312.922134619788130.88361818260054
Trimmed Mean ( 5 / 20 )3.065666666666692.802636601196691.09385093499374
Trimmed Mean ( 6 / 20 )3.552083333333362.674765913372911.32799783172582
Trimmed Mean ( 7 / 20 )4.08079710144932.522789802776661.61757317116069
Trimmed Mean ( 8 / 20 )4.603030303030322.363169244580591.94782083999542
Trimmed Mean ( 9 / 20 )4.90119047619052.272567964058232.15667498341313
Trimmed Mean ( 10 / 20 )5.251666666666692.155802545546462.43606107503480
Trimmed Mean ( 11 / 20 )5.620614035087742.015258854057782.78902832942303
Trimmed Mean ( 12 / 20 )6.044444444444461.864852375582603.24124553964017
Trimmed Mean ( 13 / 20 )6.406372549019631.724856977474963.71414710476343
Trimmed Mean ( 14 / 20 )6.729166666666681.629310350345184.1300705327509
Trimmed Mean ( 15 / 20 )7.048333333333351.510856751186354.66512349883527
Trimmed Mean ( 16 / 20 )7.18095238095241.454979947549184.93543048002017
Trimmed Mean ( 17 / 20 )7.253205128205141.41200704861045.13680518474978
Trimmed Mean ( 18 / 20 )7.291666666666681.371183768696325.31778951380046
Trimmed Mean ( 19 / 20 )7.300757575757591.317853743320545.5398845378412
Trimmed Mean ( 20 / 20 )7.416666666666681.268274314508545.84784110331892
Median8.94166666666667
Midrange-20.8583333333333
Midmean - Weighted Average at Xnp6.32553763440862
Midmean - Weighted Average at X(n+1)p7.04833333333335
Midmean - Empirical Distribution Function6.32553763440862
Midmean - Empirical Distribution Function - Averaging7.04833333333335
Midmean - Empirical Distribution Function - Interpolation7.04833333333335
Midmean - Closest Observation6.32553763440862
Midmean - True Basic - Statistics Graphics Toolkit7.04833333333335
Midmean - MS Excel (old versions)7.10833333333335
Number of observations60

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 2.4187943314935e-14 & 3.69483628962858 & 6.54641814113135e-15 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 17.6511276741620 &  &  \tabularnewline
Quadratic Mean & 28.3805760551512 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & 0.110000000000024 & 3.57595113313805 & 0.0307610467549914 \tabularnewline
Winsorized Mean ( 2 / 20 ) & 0.0333333333333575 & 3.52510871865575 & 0.00945597313267227 \tabularnewline
Winsorized Mean ( 3 / 20 ) & 0.903333333333358 & 3.23135773851719 & 0.279552252158834 \tabularnewline
Winsorized Mean ( 4 / 20 ) & 0.970000000000025 & 3.19099907461001 & 0.303980031745566 \tabularnewline
Winsorized Mean ( 5 / 20 ) & 1.12000000000002 & 3.12091096695396 & 0.358869577459672 \tabularnewline
Winsorized Mean ( 6 / 20 ) & 1.12000000000002 & 3.0763863639445 & 0.364063504222525 \tabularnewline
Winsorized Mean ( 7 / 20 ) & 1.40000000000002 & 2.95533443925290 & 0.473719651287229 \tabularnewline
Winsorized Mean ( 8 / 20 ) & 2.93333333333336 & 2.59017296683383 & 1.13248550227864 \tabularnewline
Winsorized Mean ( 9 / 20 ) & 2.79833333333336 & 2.56957356116776 & 1.08902635659967 \tabularnewline
Winsorized Mean ( 10 / 20 ) & 2.91500000000002 & 2.50818306699327 & 1.16219586933677 \tabularnewline
Winsorized Mean ( 11 / 20 ) & 2.82333333333336 & 2.36383592744972 & 1.19438633644061 \tabularnewline
Winsorized Mean ( 12 / 20 ) & 3.58333333333336 & 2.15830192154792 & 1.66025582313498 \tabularnewline
Winsorized Mean ( 13 / 20 ) & 4.16833333333336 & 1.85300925915143 & 2.24949406633953 \tabularnewline
Winsorized Mean ( 14 / 20 ) & 4.49500000000002 & 1.79104878322157 & 2.50970271837869 \tabularnewline
Winsorized Mean ( 15 / 20 ) & 6.12000000000002 & 1.47574761607985 & 4.14705057512279 \tabularnewline
Winsorized Mean ( 16 / 20 ) & 6.68000000000002 & 1.35033808628406 & 4.94690927246407 \tabularnewline
Winsorized Mean ( 17 / 20 ) & 6.99166666666668 & 1.26659046752665 & 5.52006891408217 \tabularnewline
Winsorized Mean ( 18 / 20 ) & 7.23166666666668 & 1.22081685166561 & 5.92362945907914 \tabularnewline
Winsorized Mean ( 19 / 20 ) & 6.56666666666669 & 1.11442930848745 & 5.89240305926558 \tabularnewline
Winsorized Mean ( 20 / 20 ) & 6.66666666666668 & 1.06969192724309 & 6.2323239961702 \tabularnewline
Trimmed Mean ( 1 / 20 ) & 0.719252873563242 & 3.42440623094043 & 0.210037251732753 \tabularnewline
Trimmed Mean ( 2 / 20 ) & 1.37202380952383 & 3.23447231654749 & 0.424187835061871 \tabularnewline
Trimmed Mean ( 3 / 20 ) & 2.11574074074076 & 3.02881708762362 & 0.698536979795222 \tabularnewline
Trimmed Mean ( 4 / 20 ) & 2.58205128205131 & 2.92213461978813 & 0.88361818260054 \tabularnewline
Trimmed Mean ( 5 / 20 ) & 3.06566666666669 & 2.80263660119669 & 1.09385093499374 \tabularnewline
Trimmed Mean ( 6 / 20 ) & 3.55208333333336 & 2.67476591337291 & 1.32799783172582 \tabularnewline
Trimmed Mean ( 7 / 20 ) & 4.0807971014493 & 2.52278980277666 & 1.61757317116069 \tabularnewline
Trimmed Mean ( 8 / 20 ) & 4.60303030303032 & 2.36316924458059 & 1.94782083999542 \tabularnewline
Trimmed Mean ( 9 / 20 ) & 4.9011904761905 & 2.27256796405823 & 2.15667498341313 \tabularnewline
Trimmed Mean ( 10 / 20 ) & 5.25166666666669 & 2.15580254554646 & 2.43606107503480 \tabularnewline
Trimmed Mean ( 11 / 20 ) & 5.62061403508774 & 2.01525885405778 & 2.78902832942303 \tabularnewline
Trimmed Mean ( 12 / 20 ) & 6.04444444444446 & 1.86485237558260 & 3.24124553964017 \tabularnewline
Trimmed Mean ( 13 / 20 ) & 6.40637254901963 & 1.72485697747496 & 3.71414710476343 \tabularnewline
Trimmed Mean ( 14 / 20 ) & 6.72916666666668 & 1.62931035034518 & 4.1300705327509 \tabularnewline
Trimmed Mean ( 15 / 20 ) & 7.04833333333335 & 1.51085675118635 & 4.66512349883527 \tabularnewline
Trimmed Mean ( 16 / 20 ) & 7.1809523809524 & 1.45497994754918 & 4.93543048002017 \tabularnewline
Trimmed Mean ( 17 / 20 ) & 7.25320512820514 & 1.4120070486104 & 5.13680518474978 \tabularnewline
Trimmed Mean ( 18 / 20 ) & 7.29166666666668 & 1.37118376869632 & 5.31778951380046 \tabularnewline
Trimmed Mean ( 19 / 20 ) & 7.30075757575759 & 1.31785374332054 & 5.5398845378412 \tabularnewline
Trimmed Mean ( 20 / 20 ) & 7.41666666666668 & 1.26827431450854 & 5.84784110331892 \tabularnewline
Median & 8.94166666666667 &  &  \tabularnewline
Midrange & -20.8583333333333 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 6.32553763440862 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 7.04833333333335 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 6.32553763440862 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 7.04833333333335 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 7.04833333333335 &  &  \tabularnewline
Midmean - Closest Observation & 6.32553763440862 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 7.04833333333335 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 7.10833333333335 &  &  \tabularnewline
Number of observations & 60 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49292&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]2.4187943314935e-14[/C][C]3.69483628962858[/C][C]6.54641814113135e-15[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]17.6511276741620[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]28.3805760551512[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]0.110000000000024[/C][C]3.57595113313805[/C][C]0.0307610467549914[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]0.0333333333333575[/C][C]3.52510871865575[/C][C]0.00945597313267227[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]0.903333333333358[/C][C]3.23135773851719[/C][C]0.279552252158834[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]0.970000000000025[/C][C]3.19099907461001[/C][C]0.303980031745566[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]1.12000000000002[/C][C]3.12091096695396[/C][C]0.358869577459672[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]1.12000000000002[/C][C]3.0763863639445[/C][C]0.364063504222525[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]1.40000000000002[/C][C]2.95533443925290[/C][C]0.473719651287229[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]2.93333333333336[/C][C]2.59017296683383[/C][C]1.13248550227864[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]2.79833333333336[/C][C]2.56957356116776[/C][C]1.08902635659967[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]2.91500000000002[/C][C]2.50818306699327[/C][C]1.16219586933677[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]2.82333333333336[/C][C]2.36383592744972[/C][C]1.19438633644061[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]3.58333333333336[/C][C]2.15830192154792[/C][C]1.66025582313498[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]4.16833333333336[/C][C]1.85300925915143[/C][C]2.24949406633953[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]4.49500000000002[/C][C]1.79104878322157[/C][C]2.50970271837869[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]6.12000000000002[/C][C]1.47574761607985[/C][C]4.14705057512279[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]6.68000000000002[/C][C]1.35033808628406[/C][C]4.94690927246407[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]6.99166666666668[/C][C]1.26659046752665[/C][C]5.52006891408217[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]7.23166666666668[/C][C]1.22081685166561[/C][C]5.92362945907914[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]6.56666666666669[/C][C]1.11442930848745[/C][C]5.89240305926558[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]6.66666666666668[/C][C]1.06969192724309[/C][C]6.2323239961702[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]0.719252873563242[/C][C]3.42440623094043[/C][C]0.210037251732753[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]1.37202380952383[/C][C]3.23447231654749[/C][C]0.424187835061871[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]2.11574074074076[/C][C]3.02881708762362[/C][C]0.698536979795222[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]2.58205128205131[/C][C]2.92213461978813[/C][C]0.88361818260054[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]3.06566666666669[/C][C]2.80263660119669[/C][C]1.09385093499374[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]3.55208333333336[/C][C]2.67476591337291[/C][C]1.32799783172582[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]4.0807971014493[/C][C]2.52278980277666[/C][C]1.61757317116069[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]4.60303030303032[/C][C]2.36316924458059[/C][C]1.94782083999542[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]4.9011904761905[/C][C]2.27256796405823[/C][C]2.15667498341313[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]5.25166666666669[/C][C]2.15580254554646[/C][C]2.43606107503480[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]5.62061403508774[/C][C]2.01525885405778[/C][C]2.78902832942303[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]6.04444444444446[/C][C]1.86485237558260[/C][C]3.24124553964017[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]6.40637254901963[/C][C]1.72485697747496[/C][C]3.71414710476343[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]6.72916666666668[/C][C]1.62931035034518[/C][C]4.1300705327509[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]7.04833333333335[/C][C]1.51085675118635[/C][C]4.66512349883527[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]7.1809523809524[/C][C]1.45497994754918[/C][C]4.93543048002017[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]7.25320512820514[/C][C]1.4120070486104[/C][C]5.13680518474978[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]7.29166666666668[/C][C]1.37118376869632[/C][C]5.31778951380046[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]7.30075757575759[/C][C]1.31785374332054[/C][C]5.5398845378412[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]7.41666666666668[/C][C]1.26827431450854[/C][C]5.84784110331892[/C][/ROW]
[ROW][C]Median[/C][C]8.94166666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-20.8583333333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]6.32553763440862[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]7.04833333333335[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]6.32553763440862[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]7.04833333333335[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]7.04833333333335[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]6.32553763440862[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]7.04833333333335[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]7.10833333333335[/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=49292&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49292&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 Mean2.4187943314935e-143.694836289628586.54641814113135e-15
Geometric MeanNaN
Harmonic Mean17.6511276741620
Quadratic Mean28.3805760551512
Winsorized Mean ( 1 / 20 )0.1100000000000243.575951133138050.0307610467549914
Winsorized Mean ( 2 / 20 )0.03333333333335753.525108718655750.00945597313267227
Winsorized Mean ( 3 / 20 )0.9033333333333583.231357738517190.279552252158834
Winsorized Mean ( 4 / 20 )0.9700000000000253.190999074610010.303980031745566
Winsorized Mean ( 5 / 20 )1.120000000000023.120910966953960.358869577459672
Winsorized Mean ( 6 / 20 )1.120000000000023.07638636394450.364063504222525
Winsorized Mean ( 7 / 20 )1.400000000000022.955334439252900.473719651287229
Winsorized Mean ( 8 / 20 )2.933333333333362.590172966833831.13248550227864
Winsorized Mean ( 9 / 20 )2.798333333333362.569573561167761.08902635659967
Winsorized Mean ( 10 / 20 )2.915000000000022.508183066993271.16219586933677
Winsorized Mean ( 11 / 20 )2.823333333333362.363835927449721.19438633644061
Winsorized Mean ( 12 / 20 )3.583333333333362.158301921547921.66025582313498
Winsorized Mean ( 13 / 20 )4.168333333333361.853009259151432.24949406633953
Winsorized Mean ( 14 / 20 )4.495000000000021.791048783221572.50970271837869
Winsorized Mean ( 15 / 20 )6.120000000000021.475747616079854.14705057512279
Winsorized Mean ( 16 / 20 )6.680000000000021.350338086284064.94690927246407
Winsorized Mean ( 17 / 20 )6.991666666666681.266590467526655.52006891408217
Winsorized Mean ( 18 / 20 )7.231666666666681.220816851665615.92362945907914
Winsorized Mean ( 19 / 20 )6.566666666666691.114429308487455.89240305926558
Winsorized Mean ( 20 / 20 )6.666666666666681.069691927243096.2323239961702
Trimmed Mean ( 1 / 20 )0.7192528735632423.424406230940430.210037251732753
Trimmed Mean ( 2 / 20 )1.372023809523833.234472316547490.424187835061871
Trimmed Mean ( 3 / 20 )2.115740740740763.028817087623620.698536979795222
Trimmed Mean ( 4 / 20 )2.582051282051312.922134619788130.88361818260054
Trimmed Mean ( 5 / 20 )3.065666666666692.802636601196691.09385093499374
Trimmed Mean ( 6 / 20 )3.552083333333362.674765913372911.32799783172582
Trimmed Mean ( 7 / 20 )4.08079710144932.522789802776661.61757317116069
Trimmed Mean ( 8 / 20 )4.603030303030322.363169244580591.94782083999542
Trimmed Mean ( 9 / 20 )4.90119047619052.272567964058232.15667498341313
Trimmed Mean ( 10 / 20 )5.251666666666692.155802545546462.43606107503480
Trimmed Mean ( 11 / 20 )5.620614035087742.015258854057782.78902832942303
Trimmed Mean ( 12 / 20 )6.044444444444461.864852375582603.24124553964017
Trimmed Mean ( 13 / 20 )6.406372549019631.724856977474963.71414710476343
Trimmed Mean ( 14 / 20 )6.729166666666681.629310350345184.1300705327509
Trimmed Mean ( 15 / 20 )7.048333333333351.510856751186354.66512349883527
Trimmed Mean ( 16 / 20 )7.18095238095241.454979947549184.93543048002017
Trimmed Mean ( 17 / 20 )7.253205128205141.41200704861045.13680518474978
Trimmed Mean ( 18 / 20 )7.291666666666681.371183768696325.31778951380046
Trimmed Mean ( 19 / 20 )7.300757575757591.317853743320545.5398845378412
Trimmed Mean ( 20 / 20 )7.416666666666681.268274314508545.84784110331892
Median8.94166666666667
Midrange-20.8583333333333
Midmean - Weighted Average at Xnp6.32553763440862
Midmean - Weighted Average at X(n+1)p7.04833333333335
Midmean - Empirical Distribution Function6.32553763440862
Midmean - Empirical Distribution Function - Averaging7.04833333333335
Midmean - Empirical Distribution Function - Interpolation7.04833333333335
Midmean - Closest Observation6.32553763440862
Midmean - True Basic - Statistics Graphics Toolkit7.04833333333335
Midmean - MS Excel (old versions)7.10833333333335
Number of observations60



Parameters (Session):
Parameters (R input):
par1 = ; par2 = ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')