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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 computationSat, 11 Dec 2010 14:54:55 +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/2010/Dec/11/t1292079488xb62e2oluru2m9c.htm/, Retrieved Mon, 06 May 2024 20:59:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=108191, Retrieved Mon, 06 May 2024 20:59:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [paper] [2007-12-11 21:01:08] [b3bb3ec527e23fa7d74d4348b38c8499]
- RMPD  [Univariate Explorative Data Analysis] [PAPER] [2009-12-30 15:50:30] [23722951c28e05bb35cc9a97084fe0d9]
- RMPD    [(Partial) Autocorrelation Function] [Paper ACF] [2010-12-11 12:03:59] [6e6854a111a7f2438dd668bfaa6f3aa0]
- RM        [Spectral Analysis] [Paper Spectraal] [2010-12-11 13:44:53] [6e6854a111a7f2438dd668bfaa6f3aa0]
- RM D          [Central Tendency] [Paper robustness ...] [2010-12-11 14:54:55] [81b44bf7e2a3251743773b0d7e91dd87] [Current]
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Post a new message
Dataseries X:
0.197299870124694
-7.4891834722532
-2.46357571004573
-11.1352144478093
-8.30666563148338
2.52543893701216
-9.07701600470547
6.13368551812671
-2.75736870709027
6.27193132285353
-4.86579008662195
-16.1915786204687
-6.04877252914152
-16.7022801433001
-12.2750854582395
11.9019305464657
8.86105500160429
-23.4303488204468
4.62806867714669
-9.0040358913486
-4.57543505507405
-1.10614123623148
-20.6385954015612
-14.4684198267564
-3.99999999999997
-4.25613735429343
12.7228091968775
-12.3192977007806
5.36140459843875
6.29824425195156
0.212282472462960
-17.6807022992194
1.63859540156125
5.34035114960969
-14.1070152283177
0.489473275585482
-4.85087787402421
14.8929847716824
-9.17017557480486
14.6807022992194
-30.0421068976581
-4.46841982675639
-6.38245804726782
3.76491609453564
4.02105344882906
0.680702299219377
9.17017557480483
12.4894732755855
-2
-14.5315801732436
-0.212282472462960
-11.6596488503903
3.21228247246296
19.6596488503903
7.04210689765813
-8.17017557480484
6.59648850390312




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108191&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108191&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108191&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-2.554268073833161.36918870107418-1.86553399968116
Geometric MeanNaN
Harmonic Mean8.09894378765704
Quadratic Mean10.5596513458238
Winsorized Mean ( 1 / 19 )-2.521898003683981.30967690547008-1.9255879012227
Winsorized Mean ( 2 / 19 )-2.431390251177921.28149886846426-1.89730191029485
Winsorized Mean ( 3 / 19 )-2.378758672230561.22057674826254-1.94888086768542
Winsorized Mean ( 4 / 19 )-2.326471918923381.20194509396104-1.93558918008179
Winsorized Mean ( 5 / 19 )-2.333212375615341.18124879426455-1.97520826005838
Winsorized Mean ( 6 / 19 )-2.446028851871741.08703838729695-2.25017706868116
Winsorized Mean ( 7 / 19 )-2.476234493748821.07831228215773-2.29639830197780
Winsorized Mean ( 8 / 19 )-2.680802003293731.02251504378808-2.62177267667598
Winsorized Mean ( 9 / 19 )-2.468891613749180.95639144311639-2.58146560335622
Winsorized Mean ( 10 / 19 )-2.513458632944000.946184285157688-2.65641553381445
Winsorized Mean ( 11 / 19 )-2.399768098448160.923762573932258-2.59781914332475
Winsorized Mean ( 12 / 19 )-2.318465235742020.899332277061342-2.5779851283864
Winsorized Mean ( 13 / 19 )-2.046432720073350.794571231891497-2.57551826436223
Winsorized Mean ( 14 / 19 )-2.028722444673620.790055902818086-2.56782138762242
Winsorized Mean ( 15 / 19 )-2.196959907596280.756258038855424-2.90504007193275
Winsorized Mean ( 16 / 19 )-2.171597091723280.697909104249756-3.11157581768147
Winsorized Mean ( 17 / 19 )-2.207281373468060.679476490840712-3.24850293309929
Winsorized Mean ( 18 / 19 )-2.166747116474710.618850657235862-3.5012439449489
Winsorized Mean ( 19 / 19 )-2.026786486629850.527842443801366-3.83975656075235
Trimmed Mean ( 1 / 19 )-2.458378584749501.26256994521541-1.94712268739302
Trimmed Mean ( 2 / 19 )-2.390065247404871.20372026005246-1.98556535660594
Trimmed Mean ( 3 / 19 )-2.366971862943451.14939681983871-2.05931652331837
Trimmed Mean ( 4 / 19 )-2.36240146750561.11166997245764-2.12509245192877
Trimmed Mean ( 5 / 19 )-2.373295000852331.07110945166500-2.21573528005297
Trimmed Mean ( 6 / 19 )-2.383449265912371.02633944816696-2.32228164879485
Trimmed Mean ( 7 / 19 )-2.369623543432970.999614078769522-2.37053838452322
Trimmed Mean ( 8 / 19 )-2.348449940060140.96653736007956-2.42975598984278
Trimmed Mean ( 9 / 19 )-2.287731774661700.938560909114663-2.43748887519692
Trimmed Mean ( 10 / 19 )-2.256722432835910.919382328074321-2.45460714647702
Trimmed Mean ( 11 / 19 )-2.214911108818310.894556473920055-2.47598801572840
Trimmed Mean ( 12 / 19 )-2.185883978215270.865488267982962-2.52560786677042
Trimmed Mean ( 13 / 19 )-2.165569108110370.830661941510113-2.60704024091129
Trimmed Mean ( 14 / 19 )-2.183581771553630.812441781650941-2.68767783842485
Trimmed Mean ( 15 / 19 )-2.206933574813320.784306844815098-2.81386499353274
Trimmed Mean ( 16 / 19 )-2.208449572230300.751563281975605-2.93847454392003
Trimmed Mean ( 17 / 19 )-2.214157701004490.720826166995358-3.07169440065395
Trimmed Mean ( 18 / 19 )-2.215255602039720.675575990600925-3.27906206386827
Trimmed Mean ( 19 / 19 )-2.223340349633890.626919273886752-3.54645397301267
Median-2.46357571004573
Midrange-5.1912290236339
Midmean - Weighted Average at Xnp-2.45229366159518
Midmean - Weighted Average at X(n+1)p-2.18358177155363
Midmean - Empirical Distribution Function-2.18358177155363
Midmean - Empirical Distribution Function - Averaging-2.18358177155363
Midmean - Empirical Distribution Function - Interpolation-2.18358177155363
Midmean - Closest Observation-2.41646823166201
Midmean - True Basic - Statistics Graphics Toolkit-2.18358177155363
Midmean - MS Excel (old versions)-2.18358177155363
Number of observations57

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -2.55426807383316 & 1.36918870107418 & -1.86553399968116 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 8.09894378765704 &  &  \tabularnewline
Quadratic Mean & 10.5596513458238 &  &  \tabularnewline
Winsorized Mean ( 1 / 19 ) & -2.52189800368398 & 1.30967690547008 & -1.9255879012227 \tabularnewline
Winsorized Mean ( 2 / 19 ) & -2.43139025117792 & 1.28149886846426 & -1.89730191029485 \tabularnewline
Winsorized Mean ( 3 / 19 ) & -2.37875867223056 & 1.22057674826254 & -1.94888086768542 \tabularnewline
Winsorized Mean ( 4 / 19 ) & -2.32647191892338 & 1.20194509396104 & -1.93558918008179 \tabularnewline
Winsorized Mean ( 5 / 19 ) & -2.33321237561534 & 1.18124879426455 & -1.97520826005838 \tabularnewline
Winsorized Mean ( 6 / 19 ) & -2.44602885187174 & 1.08703838729695 & -2.25017706868116 \tabularnewline
Winsorized Mean ( 7 / 19 ) & -2.47623449374882 & 1.07831228215773 & -2.29639830197780 \tabularnewline
Winsorized Mean ( 8 / 19 ) & -2.68080200329373 & 1.02251504378808 & -2.62177267667598 \tabularnewline
Winsorized Mean ( 9 / 19 ) & -2.46889161374918 & 0.95639144311639 & -2.58146560335622 \tabularnewline
Winsorized Mean ( 10 / 19 ) & -2.51345863294400 & 0.946184285157688 & -2.65641553381445 \tabularnewline
Winsorized Mean ( 11 / 19 ) & -2.39976809844816 & 0.923762573932258 & -2.59781914332475 \tabularnewline
Winsorized Mean ( 12 / 19 ) & -2.31846523574202 & 0.899332277061342 & -2.5779851283864 \tabularnewline
Winsorized Mean ( 13 / 19 ) & -2.04643272007335 & 0.794571231891497 & -2.57551826436223 \tabularnewline
Winsorized Mean ( 14 / 19 ) & -2.02872244467362 & 0.790055902818086 & -2.56782138762242 \tabularnewline
Winsorized Mean ( 15 / 19 ) & -2.19695990759628 & 0.756258038855424 & -2.90504007193275 \tabularnewline
Winsorized Mean ( 16 / 19 ) & -2.17159709172328 & 0.697909104249756 & -3.11157581768147 \tabularnewline
Winsorized Mean ( 17 / 19 ) & -2.20728137346806 & 0.679476490840712 & -3.24850293309929 \tabularnewline
Winsorized Mean ( 18 / 19 ) & -2.16674711647471 & 0.618850657235862 & -3.5012439449489 \tabularnewline
Winsorized Mean ( 19 / 19 ) & -2.02678648662985 & 0.527842443801366 & -3.83975656075235 \tabularnewline
Trimmed Mean ( 1 / 19 ) & -2.45837858474950 & 1.26256994521541 & -1.94712268739302 \tabularnewline
Trimmed Mean ( 2 / 19 ) & -2.39006524740487 & 1.20372026005246 & -1.98556535660594 \tabularnewline
Trimmed Mean ( 3 / 19 ) & -2.36697186294345 & 1.14939681983871 & -2.05931652331837 \tabularnewline
Trimmed Mean ( 4 / 19 ) & -2.3624014675056 & 1.11166997245764 & -2.12509245192877 \tabularnewline
Trimmed Mean ( 5 / 19 ) & -2.37329500085233 & 1.07110945166500 & -2.21573528005297 \tabularnewline
Trimmed Mean ( 6 / 19 ) & -2.38344926591237 & 1.02633944816696 & -2.32228164879485 \tabularnewline
Trimmed Mean ( 7 / 19 ) & -2.36962354343297 & 0.999614078769522 & -2.37053838452322 \tabularnewline
Trimmed Mean ( 8 / 19 ) & -2.34844994006014 & 0.96653736007956 & -2.42975598984278 \tabularnewline
Trimmed Mean ( 9 / 19 ) & -2.28773177466170 & 0.938560909114663 & -2.43748887519692 \tabularnewline
Trimmed Mean ( 10 / 19 ) & -2.25672243283591 & 0.919382328074321 & -2.45460714647702 \tabularnewline
Trimmed Mean ( 11 / 19 ) & -2.21491110881831 & 0.894556473920055 & -2.47598801572840 \tabularnewline
Trimmed Mean ( 12 / 19 ) & -2.18588397821527 & 0.865488267982962 & -2.52560786677042 \tabularnewline
Trimmed Mean ( 13 / 19 ) & -2.16556910811037 & 0.830661941510113 & -2.60704024091129 \tabularnewline
Trimmed Mean ( 14 / 19 ) & -2.18358177155363 & 0.812441781650941 & -2.68767783842485 \tabularnewline
Trimmed Mean ( 15 / 19 ) & -2.20693357481332 & 0.784306844815098 & -2.81386499353274 \tabularnewline
Trimmed Mean ( 16 / 19 ) & -2.20844957223030 & 0.751563281975605 & -2.93847454392003 \tabularnewline
Trimmed Mean ( 17 / 19 ) & -2.21415770100449 & 0.720826166995358 & -3.07169440065395 \tabularnewline
Trimmed Mean ( 18 / 19 ) & -2.21525560203972 & 0.675575990600925 & -3.27906206386827 \tabularnewline
Trimmed Mean ( 19 / 19 ) & -2.22334034963389 & 0.626919273886752 & -3.54645397301267 \tabularnewline
Median & -2.46357571004573 &  &  \tabularnewline
Midrange & -5.1912290236339 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -2.45229366159518 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -2.18358177155363 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -2.18358177155363 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -2.18358177155363 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -2.18358177155363 &  &  \tabularnewline
Midmean - Closest Observation & -2.41646823166201 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -2.18358177155363 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -2.18358177155363 &  &  \tabularnewline
Number of observations & 57 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108191&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]-2.55426807383316[/C][C]1.36918870107418[/C][C]-1.86553399968116[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]8.09894378765704[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]10.5596513458238[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 19 )[/C][C]-2.52189800368398[/C][C]1.30967690547008[/C][C]-1.9255879012227[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 19 )[/C][C]-2.43139025117792[/C][C]1.28149886846426[/C][C]-1.89730191029485[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 19 )[/C][C]-2.37875867223056[/C][C]1.22057674826254[/C][C]-1.94888086768542[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 19 )[/C][C]-2.32647191892338[/C][C]1.20194509396104[/C][C]-1.93558918008179[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 19 )[/C][C]-2.33321237561534[/C][C]1.18124879426455[/C][C]-1.97520826005838[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 19 )[/C][C]-2.44602885187174[/C][C]1.08703838729695[/C][C]-2.25017706868116[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 19 )[/C][C]-2.47623449374882[/C][C]1.07831228215773[/C][C]-2.29639830197780[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 19 )[/C][C]-2.68080200329373[/C][C]1.02251504378808[/C][C]-2.62177267667598[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 19 )[/C][C]-2.46889161374918[/C][C]0.95639144311639[/C][C]-2.58146560335622[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 19 )[/C][C]-2.51345863294400[/C][C]0.946184285157688[/C][C]-2.65641553381445[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 19 )[/C][C]-2.39976809844816[/C][C]0.923762573932258[/C][C]-2.59781914332475[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 19 )[/C][C]-2.31846523574202[/C][C]0.899332277061342[/C][C]-2.5779851283864[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 19 )[/C][C]-2.04643272007335[/C][C]0.794571231891497[/C][C]-2.57551826436223[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 19 )[/C][C]-2.02872244467362[/C][C]0.790055902818086[/C][C]-2.56782138762242[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 19 )[/C][C]-2.19695990759628[/C][C]0.756258038855424[/C][C]-2.90504007193275[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 19 )[/C][C]-2.17159709172328[/C][C]0.697909104249756[/C][C]-3.11157581768147[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 19 )[/C][C]-2.20728137346806[/C][C]0.679476490840712[/C][C]-3.24850293309929[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 19 )[/C][C]-2.16674711647471[/C][C]0.618850657235862[/C][C]-3.5012439449489[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 19 )[/C][C]-2.02678648662985[/C][C]0.527842443801366[/C][C]-3.83975656075235[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 19 )[/C][C]-2.45837858474950[/C][C]1.26256994521541[/C][C]-1.94712268739302[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 19 )[/C][C]-2.39006524740487[/C][C]1.20372026005246[/C][C]-1.98556535660594[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 19 )[/C][C]-2.36697186294345[/C][C]1.14939681983871[/C][C]-2.05931652331837[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 19 )[/C][C]-2.3624014675056[/C][C]1.11166997245764[/C][C]-2.12509245192877[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 19 )[/C][C]-2.37329500085233[/C][C]1.07110945166500[/C][C]-2.21573528005297[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 19 )[/C][C]-2.38344926591237[/C][C]1.02633944816696[/C][C]-2.32228164879485[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 19 )[/C][C]-2.36962354343297[/C][C]0.999614078769522[/C][C]-2.37053838452322[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 19 )[/C][C]-2.34844994006014[/C][C]0.96653736007956[/C][C]-2.42975598984278[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 19 )[/C][C]-2.28773177466170[/C][C]0.938560909114663[/C][C]-2.43748887519692[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 19 )[/C][C]-2.25672243283591[/C][C]0.919382328074321[/C][C]-2.45460714647702[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 19 )[/C][C]-2.21491110881831[/C][C]0.894556473920055[/C][C]-2.47598801572840[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 19 )[/C][C]-2.18588397821527[/C][C]0.865488267982962[/C][C]-2.52560786677042[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 19 )[/C][C]-2.16556910811037[/C][C]0.830661941510113[/C][C]-2.60704024091129[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 19 )[/C][C]-2.18358177155363[/C][C]0.812441781650941[/C][C]-2.68767783842485[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 19 )[/C][C]-2.20693357481332[/C][C]0.784306844815098[/C][C]-2.81386499353274[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 19 )[/C][C]-2.20844957223030[/C][C]0.751563281975605[/C][C]-2.93847454392003[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 19 )[/C][C]-2.21415770100449[/C][C]0.720826166995358[/C][C]-3.07169440065395[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 19 )[/C][C]-2.21525560203972[/C][C]0.675575990600925[/C][C]-3.27906206386827[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 19 )[/C][C]-2.22334034963389[/C][C]0.626919273886752[/C][C]-3.54645397301267[/C][/ROW]
[ROW][C]Median[/C][C]-2.46357571004573[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-5.1912290236339[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-2.45229366159518[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-2.18358177155363[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-2.18358177155363[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-2.18358177155363[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-2.18358177155363[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-2.41646823166201[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-2.18358177155363[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-2.18358177155363[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]57[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108191&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108191&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-2.554268073833161.36918870107418-1.86553399968116
Geometric MeanNaN
Harmonic Mean8.09894378765704
Quadratic Mean10.5596513458238
Winsorized Mean ( 1 / 19 )-2.521898003683981.30967690547008-1.9255879012227
Winsorized Mean ( 2 / 19 )-2.431390251177921.28149886846426-1.89730191029485
Winsorized Mean ( 3 / 19 )-2.378758672230561.22057674826254-1.94888086768542
Winsorized Mean ( 4 / 19 )-2.326471918923381.20194509396104-1.93558918008179
Winsorized Mean ( 5 / 19 )-2.333212375615341.18124879426455-1.97520826005838
Winsorized Mean ( 6 / 19 )-2.446028851871741.08703838729695-2.25017706868116
Winsorized Mean ( 7 / 19 )-2.476234493748821.07831228215773-2.29639830197780
Winsorized Mean ( 8 / 19 )-2.680802003293731.02251504378808-2.62177267667598
Winsorized Mean ( 9 / 19 )-2.468891613749180.95639144311639-2.58146560335622
Winsorized Mean ( 10 / 19 )-2.513458632944000.946184285157688-2.65641553381445
Winsorized Mean ( 11 / 19 )-2.399768098448160.923762573932258-2.59781914332475
Winsorized Mean ( 12 / 19 )-2.318465235742020.899332277061342-2.5779851283864
Winsorized Mean ( 13 / 19 )-2.046432720073350.794571231891497-2.57551826436223
Winsorized Mean ( 14 / 19 )-2.028722444673620.790055902818086-2.56782138762242
Winsorized Mean ( 15 / 19 )-2.196959907596280.756258038855424-2.90504007193275
Winsorized Mean ( 16 / 19 )-2.171597091723280.697909104249756-3.11157581768147
Winsorized Mean ( 17 / 19 )-2.207281373468060.679476490840712-3.24850293309929
Winsorized Mean ( 18 / 19 )-2.166747116474710.618850657235862-3.5012439449489
Winsorized Mean ( 19 / 19 )-2.026786486629850.527842443801366-3.83975656075235
Trimmed Mean ( 1 / 19 )-2.458378584749501.26256994521541-1.94712268739302
Trimmed Mean ( 2 / 19 )-2.390065247404871.20372026005246-1.98556535660594
Trimmed Mean ( 3 / 19 )-2.366971862943451.14939681983871-2.05931652331837
Trimmed Mean ( 4 / 19 )-2.36240146750561.11166997245764-2.12509245192877
Trimmed Mean ( 5 / 19 )-2.373295000852331.07110945166500-2.21573528005297
Trimmed Mean ( 6 / 19 )-2.383449265912371.02633944816696-2.32228164879485
Trimmed Mean ( 7 / 19 )-2.369623543432970.999614078769522-2.37053838452322
Trimmed Mean ( 8 / 19 )-2.348449940060140.96653736007956-2.42975598984278
Trimmed Mean ( 9 / 19 )-2.287731774661700.938560909114663-2.43748887519692
Trimmed Mean ( 10 / 19 )-2.256722432835910.919382328074321-2.45460714647702
Trimmed Mean ( 11 / 19 )-2.214911108818310.894556473920055-2.47598801572840
Trimmed Mean ( 12 / 19 )-2.185883978215270.865488267982962-2.52560786677042
Trimmed Mean ( 13 / 19 )-2.165569108110370.830661941510113-2.60704024091129
Trimmed Mean ( 14 / 19 )-2.183581771553630.812441781650941-2.68767783842485
Trimmed Mean ( 15 / 19 )-2.206933574813320.784306844815098-2.81386499353274
Trimmed Mean ( 16 / 19 )-2.208449572230300.751563281975605-2.93847454392003
Trimmed Mean ( 17 / 19 )-2.214157701004490.720826166995358-3.07169440065395
Trimmed Mean ( 18 / 19 )-2.215255602039720.675575990600925-3.27906206386827
Trimmed Mean ( 19 / 19 )-2.223340349633890.626919273886752-3.54645397301267
Median-2.46357571004573
Midrange-5.1912290236339
Midmean - Weighted Average at Xnp-2.45229366159518
Midmean - Weighted Average at X(n+1)p-2.18358177155363
Midmean - Empirical Distribution Function-2.18358177155363
Midmean - Empirical Distribution Function - Averaging-2.18358177155363
Midmean - Empirical Distribution Function - Interpolation-2.18358177155363
Midmean - Closest Observation-2.41646823166201
Midmean - True Basic - Statistics Graphics Toolkit-2.18358177155363
Midmean - MS Excel (old versions)-2.18358177155363
Number of observations57



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')