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Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationThu, 13 Dec 2007 06:46:23 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Dec/13/t11975548207gj19bwqjxh03r5.htm/, Retrieved Sun, 05 May 2024 19:38:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3557, Retrieved Sun, 05 May 2024 19:38:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact189
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Central tendency ...] [2007-12-13 13:46:23] [9bb499d88394279c02e6a8b8cf177cf7] [Current]
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Dataseries X:
9041.46
9476.91
9420.10
9690.65
10084.25
10344.12
10086.71
9959.87
10256.23
10172.04
10258.34
10703.35
11484.51
11568.05
10991.80
10545.34
11462.71
11462.40
11285.57
11552.26
12171.38
12174.88
12531.67
13099.33
13331.94
13021.59
13040.64
13030.09
12362.41
12602.89
12794.66
12874.90
13015.84
13495.45
14123.82
14246.00
13652.94
13616.55
13934.98
13773.79
13585.12
13810.92
13657.18
14075.57
14663.08
15107.66
15358.34
16375.51
17602.60
17824.63
17892.97
19639.74
21790.73
19187.52
20357.82
20291.34
19264.86
18858.49
20156.19
20222.50
20251.14
21373.38
21091.86
21856.72
21532.48
21085.27
21388.73
21363.38
22842.24
24231.43




Summary of compuational 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 compuational 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=3557&T=0

[TABLE]
[ROW][C]Summary of compuational 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=3557&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3557&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 compuational 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 Mean14849.7402857143501.12778935043529.6326418156986
Geometric Mean14299.8855313357
Harmonic Mean13795.7137272746
Quadratic Mean15422.1493891109
Winsorized Mean ( 1 / 23 )14835.3038571429495.22515127343929.9566849926641
Winsorized Mean ( 2 / 23 )14808.7692857143488.72435786264430.3008619224096
Winsorized Mean ( 3 / 23 )14815.1014285714486.71197745035530.439155219028
Winsorized Mean ( 4 / 23 )14815.7282857143481.38857702146230.7770665797368
Winsorized Mean ( 5 / 23 )14814.3447142857478.0406347216130.9897185265703
Winsorized Mean ( 6 / 23 )14813.2398571429477.74836113487631.0063645680636
Winsorized Mean ( 7 / 23 )14820.7728571429476.33412032927231.1142373065734
Winsorized Mean ( 8 / 23 )14799.3637142857468.87119494964331.5638151238426
Winsorized Mean ( 9 / 23 )14798.7877142857468.66834770306831.5762474398244
Winsorized Mean ( 10 / 23 )14707.1205714286447.31432085945832.8787161188372
Winsorized Mean ( 11 / 23 )14728.294440.99431610574533.3979225175962
Winsorized Mean ( 12 / 23 )14748.49436.05123235944933.8228375601571
Winsorized Mean ( 13 / 23 )14796.7404285714428.02304013300234.5699624580340
Winsorized Mean ( 14 / 23 )14842.2324285714418.17587202326735.4927996126606
Winsorized Mean ( 15 / 23 )14769.4567142857393.40494307821537.5426312611159
Winsorized Mean ( 16 / 23 )14683.8407142857378.18481440643938.8271558109281
Winsorized Mean ( 17 / 23 )14670.3524285714374.23993165258439.2003930841626
Winsorized Mean ( 18 / 23 )14603.1661428571357.38498314948540.8611632591989
Winsorized Mean ( 19 / 23 )14345.3822857143312.61107018730345.8889132656727
Winsorized Mean ( 20 / 23 )14498.2365714286288.14731880438750.3153617100665
Winsorized Mean ( 21 / 23 )14432.6775714286276.92581401487852.117487215017
Winsorized Mean ( 22 / 23 )14105.9587142857207.04490382272568.1299488847281
Winsorized Mean ( 23 / 23 )13827.3597142857148.35584901644593.2040078362735
Trimmed Mean ( 1 / 23 )14797.1901470588489.3540386044530.2382099251858
Trimmed Mean ( 2 / 23 )14756.7665151515482.14497107536330.6064926535237
Trimmed Mean ( 3 / 23 )14728.3275477.39880936356130.8512028331929
Trimmed Mean ( 4 / 23 )14695.6706451613472.29139666795931.1156856738023
Trimmed Mean ( 5 / 23 )14660.6538333333467.7045808513431.3459701563052
Trimmed Mean ( 6 / 23 )14623.5560344828462.79488140795931.5983530111516
Trimmed Mean ( 7 / 23 )14584.0385714286456.49908795064231.9475743903467
Trimmed Mean ( 8 / 23 )14540.1988888889448.74099058734332.4022079415069
Trimmed Mean ( 9 / 23 )14496.5894230769440.64819016658932.8983296574903
Trimmed Mean ( 10 / 23 )14449.5808430.2145046716433.586921507978
Trimmed Mean ( 11 / 23 )14412.0229166667421.931594815734.1572498806634
Trimmed Mean ( 12 / 23 )14368.27412.38179506679534.8421539745049
Trimmed Mean ( 13 / 23 )14317.8620454545400.75905884503935.7268581444364
Trimmed Mean ( 14 / 23 )14256.4673809524386.91148233852736.8468449030901
Trimmed Mean ( 15 / 23 )14183.24675370.32283560764338.2996817539687
Trimmed Mean ( 16 / 23 )14111.2560526316354.3707757714339.8205975701941
Trimmed Mean ( 17 / 23 )14041.6711111111336.66764868215541.7078123368121
Trimmed Mean ( 18 / 23 )13965.5332352941312.54076699385244.6838771454376
Trimmed Mean ( 19 / 23 )13888.043125283.34450858246449.0146895539994
Trimmed Mean ( 20 / 23 )13831.8786666667258.47785403690853.5128191860168
Trimmed Mean ( 21 / 23 )13748.5839285714227.80239942536260.3531128875403
Trimmed Mean ( 22 / 23 )13660.8796153846182.72230440709874.7630655146988
Trimmed Mean ( 23 / 23 )13601.8729166667150.86124674113590.1614775861314
Median13600.835
Midrange16636.445
Midmean - Weighted Average at Xnp13894.6468571429
Midmean - Weighted Average at X(n+1)p14041.6711111111
Midmean - Empirical Distribution Function14041.6711111111
Midmean - Empirical Distribution Function - Averaging14041.6711111111
Midmean - Empirical Distribution Function - Interpolation13965.5332352941
Midmean - Closest Observation14041.6711111111
Midmean - True Basic - Statistics Graphics Toolkit14041.6711111111
Midmean - MS Excel (old versions)14041.6711111111
Number of observations70

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 14849.7402857143 & 501.127789350435 & 29.6326418156986 \tabularnewline
Geometric Mean & 14299.8855313357 &  &  \tabularnewline
Harmonic Mean & 13795.7137272746 &  &  \tabularnewline
Quadratic Mean & 15422.1493891109 &  &  \tabularnewline
Winsorized Mean ( 1 / 23 ) & 14835.3038571429 & 495.225151273439 & 29.9566849926641 \tabularnewline
Winsorized Mean ( 2 / 23 ) & 14808.7692857143 & 488.724357862644 & 30.3008619224096 \tabularnewline
Winsorized Mean ( 3 / 23 ) & 14815.1014285714 & 486.711977450355 & 30.439155219028 \tabularnewline
Winsorized Mean ( 4 / 23 ) & 14815.7282857143 & 481.388577021462 & 30.7770665797368 \tabularnewline
Winsorized Mean ( 5 / 23 ) & 14814.3447142857 & 478.04063472161 & 30.9897185265703 \tabularnewline
Winsorized Mean ( 6 / 23 ) & 14813.2398571429 & 477.748361134876 & 31.0063645680636 \tabularnewline
Winsorized Mean ( 7 / 23 ) & 14820.7728571429 & 476.334120329272 & 31.1142373065734 \tabularnewline
Winsorized Mean ( 8 / 23 ) & 14799.3637142857 & 468.871194949643 & 31.5638151238426 \tabularnewline
Winsorized Mean ( 9 / 23 ) & 14798.7877142857 & 468.668347703068 & 31.5762474398244 \tabularnewline
Winsorized Mean ( 10 / 23 ) & 14707.1205714286 & 447.314320859458 & 32.8787161188372 \tabularnewline
Winsorized Mean ( 11 / 23 ) & 14728.294 & 440.994316105745 & 33.3979225175962 \tabularnewline
Winsorized Mean ( 12 / 23 ) & 14748.49 & 436.051232359449 & 33.8228375601571 \tabularnewline
Winsorized Mean ( 13 / 23 ) & 14796.7404285714 & 428.023040133002 & 34.5699624580340 \tabularnewline
Winsorized Mean ( 14 / 23 ) & 14842.2324285714 & 418.175872023267 & 35.4927996126606 \tabularnewline
Winsorized Mean ( 15 / 23 ) & 14769.4567142857 & 393.404943078215 & 37.5426312611159 \tabularnewline
Winsorized Mean ( 16 / 23 ) & 14683.8407142857 & 378.184814406439 & 38.8271558109281 \tabularnewline
Winsorized Mean ( 17 / 23 ) & 14670.3524285714 & 374.239931652584 & 39.2003930841626 \tabularnewline
Winsorized Mean ( 18 / 23 ) & 14603.1661428571 & 357.384983149485 & 40.8611632591989 \tabularnewline
Winsorized Mean ( 19 / 23 ) & 14345.3822857143 & 312.611070187303 & 45.8889132656727 \tabularnewline
Winsorized Mean ( 20 / 23 ) & 14498.2365714286 & 288.147318804387 & 50.3153617100665 \tabularnewline
Winsorized Mean ( 21 / 23 ) & 14432.6775714286 & 276.925814014878 & 52.117487215017 \tabularnewline
Winsorized Mean ( 22 / 23 ) & 14105.9587142857 & 207.044903822725 & 68.1299488847281 \tabularnewline
Winsorized Mean ( 23 / 23 ) & 13827.3597142857 & 148.355849016445 & 93.2040078362735 \tabularnewline
Trimmed Mean ( 1 / 23 ) & 14797.1901470588 & 489.35403860445 & 30.2382099251858 \tabularnewline
Trimmed Mean ( 2 / 23 ) & 14756.7665151515 & 482.144971075363 & 30.6064926535237 \tabularnewline
Trimmed Mean ( 3 / 23 ) & 14728.3275 & 477.398809363561 & 30.8512028331929 \tabularnewline
Trimmed Mean ( 4 / 23 ) & 14695.6706451613 & 472.291396667959 & 31.1156856738023 \tabularnewline
Trimmed Mean ( 5 / 23 ) & 14660.6538333333 & 467.70458085134 & 31.3459701563052 \tabularnewline
Trimmed Mean ( 6 / 23 ) & 14623.5560344828 & 462.794881407959 & 31.5983530111516 \tabularnewline
Trimmed Mean ( 7 / 23 ) & 14584.0385714286 & 456.499087950642 & 31.9475743903467 \tabularnewline
Trimmed Mean ( 8 / 23 ) & 14540.1988888889 & 448.740990587343 & 32.4022079415069 \tabularnewline
Trimmed Mean ( 9 / 23 ) & 14496.5894230769 & 440.648190166589 & 32.8983296574903 \tabularnewline
Trimmed Mean ( 10 / 23 ) & 14449.5808 & 430.21450467164 & 33.586921507978 \tabularnewline
Trimmed Mean ( 11 / 23 ) & 14412.0229166667 & 421.9315948157 & 34.1572498806634 \tabularnewline
Trimmed Mean ( 12 / 23 ) & 14368.27 & 412.381795066795 & 34.8421539745049 \tabularnewline
Trimmed Mean ( 13 / 23 ) & 14317.8620454545 & 400.759058845039 & 35.7268581444364 \tabularnewline
Trimmed Mean ( 14 / 23 ) & 14256.4673809524 & 386.911482338527 & 36.8468449030901 \tabularnewline
Trimmed Mean ( 15 / 23 ) & 14183.24675 & 370.322835607643 & 38.2996817539687 \tabularnewline
Trimmed Mean ( 16 / 23 ) & 14111.2560526316 & 354.37077577143 & 39.8205975701941 \tabularnewline
Trimmed Mean ( 17 / 23 ) & 14041.6711111111 & 336.667648682155 & 41.7078123368121 \tabularnewline
Trimmed Mean ( 18 / 23 ) & 13965.5332352941 & 312.540766993852 & 44.6838771454376 \tabularnewline
Trimmed Mean ( 19 / 23 ) & 13888.043125 & 283.344508582464 & 49.0146895539994 \tabularnewline
Trimmed Mean ( 20 / 23 ) & 13831.8786666667 & 258.477854036908 & 53.5128191860168 \tabularnewline
Trimmed Mean ( 21 / 23 ) & 13748.5839285714 & 227.802399425362 & 60.3531128875403 \tabularnewline
Trimmed Mean ( 22 / 23 ) & 13660.8796153846 & 182.722304407098 & 74.7630655146988 \tabularnewline
Trimmed Mean ( 23 / 23 ) & 13601.8729166667 & 150.861246741135 & 90.1614775861314 \tabularnewline
Median & 13600.835 &  &  \tabularnewline
Midrange & 16636.445 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 13894.6468571429 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 14041.6711111111 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 14041.6711111111 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 14041.6711111111 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 13965.5332352941 &  &  \tabularnewline
Midmean - Closest Observation & 14041.6711111111 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 14041.6711111111 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 14041.6711111111 &  &  \tabularnewline
Number of observations & 70 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3557&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]14849.7402857143[/C][C]501.127789350435[/C][C]29.6326418156986[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]14299.8855313357[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]13795.7137272746[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]15422.1493891109[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 23 )[/C][C]14835.3038571429[/C][C]495.225151273439[/C][C]29.9566849926641[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 23 )[/C][C]14808.7692857143[/C][C]488.724357862644[/C][C]30.3008619224096[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 23 )[/C][C]14815.1014285714[/C][C]486.711977450355[/C][C]30.439155219028[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 23 )[/C][C]14815.7282857143[/C][C]481.388577021462[/C][C]30.7770665797368[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 23 )[/C][C]14814.3447142857[/C][C]478.04063472161[/C][C]30.9897185265703[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 23 )[/C][C]14813.2398571429[/C][C]477.748361134876[/C][C]31.0063645680636[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 23 )[/C][C]14820.7728571429[/C][C]476.334120329272[/C][C]31.1142373065734[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 23 )[/C][C]14799.3637142857[/C][C]468.871194949643[/C][C]31.5638151238426[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 23 )[/C][C]14798.7877142857[/C][C]468.668347703068[/C][C]31.5762474398244[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 23 )[/C][C]14707.1205714286[/C][C]447.314320859458[/C][C]32.8787161188372[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 23 )[/C][C]14728.294[/C][C]440.994316105745[/C][C]33.3979225175962[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 23 )[/C][C]14748.49[/C][C]436.051232359449[/C][C]33.8228375601571[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 23 )[/C][C]14796.7404285714[/C][C]428.023040133002[/C][C]34.5699624580340[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 23 )[/C][C]14842.2324285714[/C][C]418.175872023267[/C][C]35.4927996126606[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 23 )[/C][C]14769.4567142857[/C][C]393.404943078215[/C][C]37.5426312611159[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 23 )[/C][C]14683.8407142857[/C][C]378.184814406439[/C][C]38.8271558109281[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 23 )[/C][C]14670.3524285714[/C][C]374.239931652584[/C][C]39.2003930841626[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 23 )[/C][C]14603.1661428571[/C][C]357.384983149485[/C][C]40.8611632591989[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 23 )[/C][C]14345.3822857143[/C][C]312.611070187303[/C][C]45.8889132656727[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 23 )[/C][C]14498.2365714286[/C][C]288.147318804387[/C][C]50.3153617100665[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 23 )[/C][C]14432.6775714286[/C][C]276.925814014878[/C][C]52.117487215017[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 23 )[/C][C]14105.9587142857[/C][C]207.044903822725[/C][C]68.1299488847281[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 23 )[/C][C]13827.3597142857[/C][C]148.355849016445[/C][C]93.2040078362735[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 23 )[/C][C]14797.1901470588[/C][C]489.35403860445[/C][C]30.2382099251858[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 23 )[/C][C]14756.7665151515[/C][C]482.144971075363[/C][C]30.6064926535237[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 23 )[/C][C]14728.3275[/C][C]477.398809363561[/C][C]30.8512028331929[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 23 )[/C][C]14695.6706451613[/C][C]472.291396667959[/C][C]31.1156856738023[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 23 )[/C][C]14660.6538333333[/C][C]467.70458085134[/C][C]31.3459701563052[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 23 )[/C][C]14623.5560344828[/C][C]462.794881407959[/C][C]31.5983530111516[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 23 )[/C][C]14584.0385714286[/C][C]456.499087950642[/C][C]31.9475743903467[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 23 )[/C][C]14540.1988888889[/C][C]448.740990587343[/C][C]32.4022079415069[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 23 )[/C][C]14496.5894230769[/C][C]440.648190166589[/C][C]32.8983296574903[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 23 )[/C][C]14449.5808[/C][C]430.21450467164[/C][C]33.586921507978[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 23 )[/C][C]14412.0229166667[/C][C]421.9315948157[/C][C]34.1572498806634[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 23 )[/C][C]14368.27[/C][C]412.381795066795[/C][C]34.8421539745049[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 23 )[/C][C]14317.8620454545[/C][C]400.759058845039[/C][C]35.7268581444364[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 23 )[/C][C]14256.4673809524[/C][C]386.911482338527[/C][C]36.8468449030901[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 23 )[/C][C]14183.24675[/C][C]370.322835607643[/C][C]38.2996817539687[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 23 )[/C][C]14111.2560526316[/C][C]354.37077577143[/C][C]39.8205975701941[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 23 )[/C][C]14041.6711111111[/C][C]336.667648682155[/C][C]41.7078123368121[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 23 )[/C][C]13965.5332352941[/C][C]312.540766993852[/C][C]44.6838771454376[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 23 )[/C][C]13888.043125[/C][C]283.344508582464[/C][C]49.0146895539994[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 23 )[/C][C]13831.8786666667[/C][C]258.477854036908[/C][C]53.5128191860168[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 23 )[/C][C]13748.5839285714[/C][C]227.802399425362[/C][C]60.3531128875403[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 23 )[/C][C]13660.8796153846[/C][C]182.722304407098[/C][C]74.7630655146988[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 23 )[/C][C]13601.8729166667[/C][C]150.861246741135[/C][C]90.1614775861314[/C][/ROW]
[ROW][C]Median[/C][C]13600.835[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]16636.445[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]13894.6468571429[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]14041.6711111111[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]14041.6711111111[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]14041.6711111111[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]13965.5332352941[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]14041.6711111111[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]14041.6711111111[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]14041.6711111111[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]70[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3557&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3557&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 Mean14849.7402857143501.12778935043529.6326418156986
Geometric Mean14299.8855313357
Harmonic Mean13795.7137272746
Quadratic Mean15422.1493891109
Winsorized Mean ( 1 / 23 )14835.3038571429495.22515127343929.9566849926641
Winsorized Mean ( 2 / 23 )14808.7692857143488.72435786264430.3008619224096
Winsorized Mean ( 3 / 23 )14815.1014285714486.71197745035530.439155219028
Winsorized Mean ( 4 / 23 )14815.7282857143481.38857702146230.7770665797368
Winsorized Mean ( 5 / 23 )14814.3447142857478.0406347216130.9897185265703
Winsorized Mean ( 6 / 23 )14813.2398571429477.74836113487631.0063645680636
Winsorized Mean ( 7 / 23 )14820.7728571429476.33412032927231.1142373065734
Winsorized Mean ( 8 / 23 )14799.3637142857468.87119494964331.5638151238426
Winsorized Mean ( 9 / 23 )14798.7877142857468.66834770306831.5762474398244
Winsorized Mean ( 10 / 23 )14707.1205714286447.31432085945832.8787161188372
Winsorized Mean ( 11 / 23 )14728.294440.99431610574533.3979225175962
Winsorized Mean ( 12 / 23 )14748.49436.05123235944933.8228375601571
Winsorized Mean ( 13 / 23 )14796.7404285714428.02304013300234.5699624580340
Winsorized Mean ( 14 / 23 )14842.2324285714418.17587202326735.4927996126606
Winsorized Mean ( 15 / 23 )14769.4567142857393.40494307821537.5426312611159
Winsorized Mean ( 16 / 23 )14683.8407142857378.18481440643938.8271558109281
Winsorized Mean ( 17 / 23 )14670.3524285714374.23993165258439.2003930841626
Winsorized Mean ( 18 / 23 )14603.1661428571357.38498314948540.8611632591989
Winsorized Mean ( 19 / 23 )14345.3822857143312.61107018730345.8889132656727
Winsorized Mean ( 20 / 23 )14498.2365714286288.14731880438750.3153617100665
Winsorized Mean ( 21 / 23 )14432.6775714286276.92581401487852.117487215017
Winsorized Mean ( 22 / 23 )14105.9587142857207.04490382272568.1299488847281
Winsorized Mean ( 23 / 23 )13827.3597142857148.35584901644593.2040078362735
Trimmed Mean ( 1 / 23 )14797.1901470588489.3540386044530.2382099251858
Trimmed Mean ( 2 / 23 )14756.7665151515482.14497107536330.6064926535237
Trimmed Mean ( 3 / 23 )14728.3275477.39880936356130.8512028331929
Trimmed Mean ( 4 / 23 )14695.6706451613472.29139666795931.1156856738023
Trimmed Mean ( 5 / 23 )14660.6538333333467.7045808513431.3459701563052
Trimmed Mean ( 6 / 23 )14623.5560344828462.79488140795931.5983530111516
Trimmed Mean ( 7 / 23 )14584.0385714286456.49908795064231.9475743903467
Trimmed Mean ( 8 / 23 )14540.1988888889448.74099058734332.4022079415069
Trimmed Mean ( 9 / 23 )14496.5894230769440.64819016658932.8983296574903
Trimmed Mean ( 10 / 23 )14449.5808430.2145046716433.586921507978
Trimmed Mean ( 11 / 23 )14412.0229166667421.931594815734.1572498806634
Trimmed Mean ( 12 / 23 )14368.27412.38179506679534.8421539745049
Trimmed Mean ( 13 / 23 )14317.8620454545400.75905884503935.7268581444364
Trimmed Mean ( 14 / 23 )14256.4673809524386.91148233852736.8468449030901
Trimmed Mean ( 15 / 23 )14183.24675370.32283560764338.2996817539687
Trimmed Mean ( 16 / 23 )14111.2560526316354.3707757714339.8205975701941
Trimmed Mean ( 17 / 23 )14041.6711111111336.66764868215541.7078123368121
Trimmed Mean ( 18 / 23 )13965.5332352941312.54076699385244.6838771454376
Trimmed Mean ( 19 / 23 )13888.043125283.34450858246449.0146895539994
Trimmed Mean ( 20 / 23 )13831.8786666667258.47785403690853.5128191860168
Trimmed Mean ( 21 / 23 )13748.5839285714227.80239942536260.3531128875403
Trimmed Mean ( 22 / 23 )13660.8796153846182.72230440709874.7630655146988
Trimmed Mean ( 23 / 23 )13601.8729166667150.86124674113590.1614775861314
Median13600.835
Midrange16636.445
Midmean - Weighted Average at Xnp13894.6468571429
Midmean - Weighted Average at X(n+1)p14041.6711111111
Midmean - Empirical Distribution Function14041.6711111111
Midmean - Empirical Distribution Function - Averaging14041.6711111111
Midmean - Empirical Distribution Function - Interpolation13965.5332352941
Midmean - Closest Observation14041.6711111111
Midmean - True Basic - Statistics Graphics Toolkit14041.6711111111
Midmean - MS Excel (old versions)14041.6711111111
Number of observations70



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')