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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 computationMon, 20 Oct 2008 15:11:22 -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/2008/Oct/20/t1224537198102pk1gd76m03uu.htm/, Retrieved Sun, 19 May 2024 13:04:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18161, Retrieved Sun, 19 May 2024 13:04:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact140
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [uitvoer van belgi...] [2008-10-13 19:23:12] [1e1d8320a8a1170c475bf6e4ce119de6]
- RMP   [Central Tendency] [Central Tendency ...] [2008-10-18 10:47:17] [1e1d8320a8a1170c475bf6e4ce119de6]
F    D      [Central Tendency] [Central Tendency ...] [2008-10-20 21:11:22] [02e7fb326979b65614900650d62c19a6] [Current]
-    D        [Central Tendency] [] [2008-10-20 21:17:29] [3754dd41128068acfc463ebbabce5a9c]
-    D          [Central Tendency] [Central Tendency ...] [2008-10-20 21:22:30] [3754dd41128068acfc463ebbabce5a9c]
-    D            [Central Tendency] [Central Tendency ...] [2008-10-20 21:26:01] [3754dd41128068acfc463ebbabce5a9c]
Feedback Forum
2008-10-26 11:58:09 [Lindsay Heyndrickx] [reply
De student kiest hier voor central tendancy dit is op zich niet verkeerd maar met het back to back histogram kan je twee tijdreeksen makkelijker controleren op spreiding. De student vergelijkt hier ook geen twee tijdreeksen hij geeft enkel weer wat de gemiddeldes en de mediaan zijn voor deze tijdreeksen zonder uitleg.
Dit is voor alle 4 de tijdreeksen zo.

Post a new message
Dataseries X:
2333.3
2282.2
2458.2
2345.5
2065.2
2332.5
2077.5
1691.4
2381.9
2526
2212.1
2459.9
2178.8
2318.2
2661.8
2407.9
2040.6
2601.6
2106.3
1829.9
2546.1
2363
2435.8
2668
2316.9
2324.2
2610.8
2413.2
2345.2
2590.8
2132.1
1990.7
2641.7
2437.1
2649.2
2819.4
2405.6
2451.3
2878.5
2534.1
2670.6
2909.7
2261.8
2135.3
2870.4
2803.2
2775.1
2633.7
2930.6
2779.7
3039.2
2752.7
2743.1
2914
2711.9
2295.8
2840.6
3230.5
2761.1
2769.6




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18161&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18161&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18161&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean2494.88539.587527199179363.0219964850879
Geometric Mean2475.72432999958
Harmonic Mean2455.8346085226
Quadratic Mean2513.34723615739
Winsorized Mean ( 1 / 20 )2494.00537.954439712984265.7104944470252
Winsorized Mean ( 2 / 20 )2495.74535.695844400796569.916962097255
Winsorized Mean ( 3 / 20 )2497.4134.950540736018971.4555468215189
Winsorized Mean ( 4 / 20 )2498.7633333333334.536505125046472.351366308955
Winsorized Mean ( 5 / 20 )2497.1883333333333.808787435554773.8621087222781
Winsorized Mean ( 6 / 20 )2499.2583333333333.061089517224275.5951594405643
Winsorized Mean ( 7 / 20 )2498.7916666666731.816174003193878.5384083710326
Winsorized Mean ( 8 / 20 )2496.3916666666731.227468016315179.9421735173151
Winsorized Mean ( 9 / 20 )2500.4866666666729.561340560669484.586375964069
Winsorized Mean ( 10 / 20 )2502.1227.88922121334789.7163811373318
Winsorized Mean ( 11 / 20 )2510.3883333333326.208343443541395.7858454022964
Winsorized Mean ( 12 / 20 )2513.3683333333325.376925936949499.0414812092669
Winsorized Mean ( 13 / 20 )2514.4733333333324.6135152881486102.158237208159
Winsorized Mean ( 14 / 20 )2517.4366666666723.5549368638325106.875118418682
Winsorized Mean ( 15 / 20 )2515.3616666666723.1043366794904108.869676786676
Winsorized Mean ( 16 / 20 )2508.6416666666721.5100900369861116.626274569429
Winsorized Mean ( 17 / 20 )2499.2916666666719.3492943989756129.167070133523
Winsorized Mean ( 18 / 20 )2498.7516666666719.1974326631681130.160720472833
Winsorized Mean ( 19 / 20 )2500.5566666666718.3590211459869136.203158479027
Winsorized Mean ( 20 / 20 )2496.4566666666717.7252049093152140.842189381669
Trimmed Mean ( 1 / 20 )2496.0551724137936.319617771141668.7247092781102
Trimmed Mean ( 2 / 20 )2498.2517857142934.292258790126972.851771036837
Trimmed Mean ( 3 / 20 )2499.6444444444433.319259258016475.0210088732104
Trimmed Mean ( 4 / 20 )2500.5038461538532.463371279382977.0253903895029
Trimmed Mean ( 5 / 20 )2501.02631.544720029099779.2850910609707
Trimmed Mean ( 6 / 20 )2501.9854166666730.625966910424881.6949036738825
Trimmed Mean ( 7 / 20 )2502.5782608695729.681908137069484.313254030462
Trimmed Mean ( 8 / 20 )2503.3159090909128.82627907222786.841451261143
Trimmed Mean ( 9 / 20 )2504.5523809523827.861827077705489.8918930896848
Trimmed Mean ( 10 / 20 )2505.2327.049731075965592.6157081918636
Trimmed Mean ( 11 / 20 )2505.7210526315826.403223314446494.9020891422973
Trimmed Mean ( 12 / 20 )2505.0138888888925.943842941091696.555236422638
Trimmed Mean ( 13 / 20 )2503.7852941176525.479036201977798.2684460381315
Trimmed Mean ( 14 / 20 )2502.2437524.9765337195365100.183787634341
Trimmed Mean ( 15 / 20 )2500.0733333333324.4858546701397102.102759614193
Trimmed Mean ( 16 / 20 )2497.8892857142923.8308974997267104.817256074511
Trimmed Mean ( 17 / 20 )2496.3384615384623.3142459433138107.073523527548
Trimmed Mean ( 18 / 20 )2495.9041666666723.1604160677993107.765946836197
Trimmed Mean ( 19 / 20 )2495.4727272727322.7937440929672109.480597706749
Trimmed Mean ( 20 / 20 )2494.6722.3474219636416111.631220999842
Median2459.05
Midrange2460.95
Midmean - Weighted Average at Xnp2494.16451612903
Midmean - Weighted Average at X(n+1)p2500.07333333333
Midmean - Empirical Distribution Function2494.16451612903
Midmean - Empirical Distribution Function - Averaging2500.07333333333
Midmean - Empirical Distribution Function - Interpolation2500.07333333333
Midmean - Closest Observation2494.16451612903
Midmean - True Basic - Statistics Graphics Toolkit2500.07333333333
Midmean - MS Excel (old versions)2502.24375
Number of observations60

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 2494.885 & 39.5875271991793 & 63.0219964850879 \tabularnewline
Geometric Mean & 2475.72432999958 &  &  \tabularnewline
Harmonic Mean & 2455.8346085226 &  &  \tabularnewline
Quadratic Mean & 2513.34723615739 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & 2494.005 & 37.9544397129842 & 65.7104944470252 \tabularnewline
Winsorized Mean ( 2 / 20 ) & 2495.745 & 35.6958444007965 & 69.916962097255 \tabularnewline
Winsorized Mean ( 3 / 20 ) & 2497.41 & 34.9505407360189 & 71.4555468215189 \tabularnewline
Winsorized Mean ( 4 / 20 ) & 2498.76333333333 & 34.5365051250464 & 72.351366308955 \tabularnewline
Winsorized Mean ( 5 / 20 ) & 2497.18833333333 & 33.8087874355547 & 73.8621087222781 \tabularnewline
Winsorized Mean ( 6 / 20 ) & 2499.25833333333 & 33.0610895172242 & 75.5951594405643 \tabularnewline
Winsorized Mean ( 7 / 20 ) & 2498.79166666667 & 31.8161740031938 & 78.5384083710326 \tabularnewline
Winsorized Mean ( 8 / 20 ) & 2496.39166666667 & 31.2274680163151 & 79.9421735173151 \tabularnewline
Winsorized Mean ( 9 / 20 ) & 2500.48666666667 & 29.5613405606694 & 84.586375964069 \tabularnewline
Winsorized Mean ( 10 / 20 ) & 2502.12 & 27.889221213347 & 89.7163811373318 \tabularnewline
Winsorized Mean ( 11 / 20 ) & 2510.38833333333 & 26.2083434435413 & 95.7858454022964 \tabularnewline
Winsorized Mean ( 12 / 20 ) & 2513.36833333333 & 25.3769259369494 & 99.0414812092669 \tabularnewline
Winsorized Mean ( 13 / 20 ) & 2514.47333333333 & 24.6135152881486 & 102.158237208159 \tabularnewline
Winsorized Mean ( 14 / 20 ) & 2517.43666666667 & 23.5549368638325 & 106.875118418682 \tabularnewline
Winsorized Mean ( 15 / 20 ) & 2515.36166666667 & 23.1043366794904 & 108.869676786676 \tabularnewline
Winsorized Mean ( 16 / 20 ) & 2508.64166666667 & 21.5100900369861 & 116.626274569429 \tabularnewline
Winsorized Mean ( 17 / 20 ) & 2499.29166666667 & 19.3492943989756 & 129.167070133523 \tabularnewline
Winsorized Mean ( 18 / 20 ) & 2498.75166666667 & 19.1974326631681 & 130.160720472833 \tabularnewline
Winsorized Mean ( 19 / 20 ) & 2500.55666666667 & 18.3590211459869 & 136.203158479027 \tabularnewline
Winsorized Mean ( 20 / 20 ) & 2496.45666666667 & 17.7252049093152 & 140.842189381669 \tabularnewline
Trimmed Mean ( 1 / 20 ) & 2496.05517241379 & 36.3196177711416 & 68.7247092781102 \tabularnewline
Trimmed Mean ( 2 / 20 ) & 2498.25178571429 & 34.2922587901269 & 72.851771036837 \tabularnewline
Trimmed Mean ( 3 / 20 ) & 2499.64444444444 & 33.3192592580164 & 75.0210088732104 \tabularnewline
Trimmed Mean ( 4 / 20 ) & 2500.50384615385 & 32.4633712793829 & 77.0253903895029 \tabularnewline
Trimmed Mean ( 5 / 20 ) & 2501.026 & 31.5447200290997 & 79.2850910609707 \tabularnewline
Trimmed Mean ( 6 / 20 ) & 2501.98541666667 & 30.6259669104248 & 81.6949036738825 \tabularnewline
Trimmed Mean ( 7 / 20 ) & 2502.57826086957 & 29.6819081370694 & 84.313254030462 \tabularnewline
Trimmed Mean ( 8 / 20 ) & 2503.31590909091 & 28.826279072227 & 86.841451261143 \tabularnewline
Trimmed Mean ( 9 / 20 ) & 2504.55238095238 & 27.8618270777054 & 89.8918930896848 \tabularnewline
Trimmed Mean ( 10 / 20 ) & 2505.23 & 27.0497310759655 & 92.6157081918636 \tabularnewline
Trimmed Mean ( 11 / 20 ) & 2505.72105263158 & 26.4032233144464 & 94.9020891422973 \tabularnewline
Trimmed Mean ( 12 / 20 ) & 2505.01388888889 & 25.9438429410916 & 96.555236422638 \tabularnewline
Trimmed Mean ( 13 / 20 ) & 2503.78529411765 & 25.4790362019777 & 98.2684460381315 \tabularnewline
Trimmed Mean ( 14 / 20 ) & 2502.24375 & 24.9765337195365 & 100.183787634341 \tabularnewline
Trimmed Mean ( 15 / 20 ) & 2500.07333333333 & 24.4858546701397 & 102.102759614193 \tabularnewline
Trimmed Mean ( 16 / 20 ) & 2497.88928571429 & 23.8308974997267 & 104.817256074511 \tabularnewline
Trimmed Mean ( 17 / 20 ) & 2496.33846153846 & 23.3142459433138 & 107.073523527548 \tabularnewline
Trimmed Mean ( 18 / 20 ) & 2495.90416666667 & 23.1604160677993 & 107.765946836197 \tabularnewline
Trimmed Mean ( 19 / 20 ) & 2495.47272727273 & 22.7937440929672 & 109.480597706749 \tabularnewline
Trimmed Mean ( 20 / 20 ) & 2494.67 & 22.3474219636416 & 111.631220999842 \tabularnewline
Median & 2459.05 &  &  \tabularnewline
Midrange & 2460.95 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 2494.16451612903 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 2500.07333333333 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 2494.16451612903 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 2500.07333333333 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 2500.07333333333 &  &  \tabularnewline
Midmean - Closest Observation & 2494.16451612903 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 2500.07333333333 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 2502.24375 &  &  \tabularnewline
Number of observations & 60 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18161&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]2494.885[/C][C]39.5875271991793[/C][C]63.0219964850879[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]2475.72432999958[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]2455.8346085226[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]2513.34723615739[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]2494.005[/C][C]37.9544397129842[/C][C]65.7104944470252[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]2495.745[/C][C]35.6958444007965[/C][C]69.916962097255[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]2497.41[/C][C]34.9505407360189[/C][C]71.4555468215189[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]2498.76333333333[/C][C]34.5365051250464[/C][C]72.351366308955[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]2497.18833333333[/C][C]33.8087874355547[/C][C]73.8621087222781[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]2499.25833333333[/C][C]33.0610895172242[/C][C]75.5951594405643[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]2498.79166666667[/C][C]31.8161740031938[/C][C]78.5384083710326[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]2496.39166666667[/C][C]31.2274680163151[/C][C]79.9421735173151[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]2500.48666666667[/C][C]29.5613405606694[/C][C]84.586375964069[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]2502.12[/C][C]27.889221213347[/C][C]89.7163811373318[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]2510.38833333333[/C][C]26.2083434435413[/C][C]95.7858454022964[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]2513.36833333333[/C][C]25.3769259369494[/C][C]99.0414812092669[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]2514.47333333333[/C][C]24.6135152881486[/C][C]102.158237208159[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]2517.43666666667[/C][C]23.5549368638325[/C][C]106.875118418682[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]2515.36166666667[/C][C]23.1043366794904[/C][C]108.869676786676[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]2508.64166666667[/C][C]21.5100900369861[/C][C]116.626274569429[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]2499.29166666667[/C][C]19.3492943989756[/C][C]129.167070133523[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]2498.75166666667[/C][C]19.1974326631681[/C][C]130.160720472833[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]2500.55666666667[/C][C]18.3590211459869[/C][C]136.203158479027[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]2496.45666666667[/C][C]17.7252049093152[/C][C]140.842189381669[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]2496.05517241379[/C][C]36.3196177711416[/C][C]68.7247092781102[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]2498.25178571429[/C][C]34.2922587901269[/C][C]72.851771036837[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]2499.64444444444[/C][C]33.3192592580164[/C][C]75.0210088732104[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]2500.50384615385[/C][C]32.4633712793829[/C][C]77.0253903895029[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]2501.026[/C][C]31.5447200290997[/C][C]79.2850910609707[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]2501.98541666667[/C][C]30.6259669104248[/C][C]81.6949036738825[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]2502.57826086957[/C][C]29.6819081370694[/C][C]84.313254030462[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]2503.31590909091[/C][C]28.826279072227[/C][C]86.841451261143[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]2504.55238095238[/C][C]27.8618270777054[/C][C]89.8918930896848[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]2505.23[/C][C]27.0497310759655[/C][C]92.6157081918636[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]2505.72105263158[/C][C]26.4032233144464[/C][C]94.9020891422973[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]2505.01388888889[/C][C]25.9438429410916[/C][C]96.555236422638[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]2503.78529411765[/C][C]25.4790362019777[/C][C]98.2684460381315[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]2502.24375[/C][C]24.9765337195365[/C][C]100.183787634341[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]2500.07333333333[/C][C]24.4858546701397[/C][C]102.102759614193[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]2497.88928571429[/C][C]23.8308974997267[/C][C]104.817256074511[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]2496.33846153846[/C][C]23.3142459433138[/C][C]107.073523527548[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]2495.90416666667[/C][C]23.1604160677993[/C][C]107.765946836197[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]2495.47272727273[/C][C]22.7937440929672[/C][C]109.480597706749[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]2494.67[/C][C]22.3474219636416[/C][C]111.631220999842[/C][/ROW]
[ROW][C]Median[/C][C]2459.05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]2460.95[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]2494.16451612903[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]2500.07333333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]2494.16451612903[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]2500.07333333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]2500.07333333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]2494.16451612903[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]2500.07333333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]2502.24375[/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=18161&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18161&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 Mean2494.88539.587527199179363.0219964850879
Geometric Mean2475.72432999958
Harmonic Mean2455.8346085226
Quadratic Mean2513.34723615739
Winsorized Mean ( 1 / 20 )2494.00537.954439712984265.7104944470252
Winsorized Mean ( 2 / 20 )2495.74535.695844400796569.916962097255
Winsorized Mean ( 3 / 20 )2497.4134.950540736018971.4555468215189
Winsorized Mean ( 4 / 20 )2498.7633333333334.536505125046472.351366308955
Winsorized Mean ( 5 / 20 )2497.1883333333333.808787435554773.8621087222781
Winsorized Mean ( 6 / 20 )2499.2583333333333.061089517224275.5951594405643
Winsorized Mean ( 7 / 20 )2498.7916666666731.816174003193878.5384083710326
Winsorized Mean ( 8 / 20 )2496.3916666666731.227468016315179.9421735173151
Winsorized Mean ( 9 / 20 )2500.4866666666729.561340560669484.586375964069
Winsorized Mean ( 10 / 20 )2502.1227.88922121334789.7163811373318
Winsorized Mean ( 11 / 20 )2510.3883333333326.208343443541395.7858454022964
Winsorized Mean ( 12 / 20 )2513.3683333333325.376925936949499.0414812092669
Winsorized Mean ( 13 / 20 )2514.4733333333324.6135152881486102.158237208159
Winsorized Mean ( 14 / 20 )2517.4366666666723.5549368638325106.875118418682
Winsorized Mean ( 15 / 20 )2515.3616666666723.1043366794904108.869676786676
Winsorized Mean ( 16 / 20 )2508.6416666666721.5100900369861116.626274569429
Winsorized Mean ( 17 / 20 )2499.2916666666719.3492943989756129.167070133523
Winsorized Mean ( 18 / 20 )2498.7516666666719.1974326631681130.160720472833
Winsorized Mean ( 19 / 20 )2500.5566666666718.3590211459869136.203158479027
Winsorized Mean ( 20 / 20 )2496.4566666666717.7252049093152140.842189381669
Trimmed Mean ( 1 / 20 )2496.0551724137936.319617771141668.7247092781102
Trimmed Mean ( 2 / 20 )2498.2517857142934.292258790126972.851771036837
Trimmed Mean ( 3 / 20 )2499.6444444444433.319259258016475.0210088732104
Trimmed Mean ( 4 / 20 )2500.5038461538532.463371279382977.0253903895029
Trimmed Mean ( 5 / 20 )2501.02631.544720029099779.2850910609707
Trimmed Mean ( 6 / 20 )2501.9854166666730.625966910424881.6949036738825
Trimmed Mean ( 7 / 20 )2502.5782608695729.681908137069484.313254030462
Trimmed Mean ( 8 / 20 )2503.3159090909128.82627907222786.841451261143
Trimmed Mean ( 9 / 20 )2504.5523809523827.861827077705489.8918930896848
Trimmed Mean ( 10 / 20 )2505.2327.049731075965592.6157081918636
Trimmed Mean ( 11 / 20 )2505.7210526315826.403223314446494.9020891422973
Trimmed Mean ( 12 / 20 )2505.0138888888925.943842941091696.555236422638
Trimmed Mean ( 13 / 20 )2503.7852941176525.479036201977798.2684460381315
Trimmed Mean ( 14 / 20 )2502.2437524.9765337195365100.183787634341
Trimmed Mean ( 15 / 20 )2500.0733333333324.4858546701397102.102759614193
Trimmed Mean ( 16 / 20 )2497.8892857142923.8308974997267104.817256074511
Trimmed Mean ( 17 / 20 )2496.3384615384623.3142459433138107.073523527548
Trimmed Mean ( 18 / 20 )2495.9041666666723.1604160677993107.765946836197
Trimmed Mean ( 19 / 20 )2495.4727272727322.7937440929672109.480597706749
Trimmed Mean ( 20 / 20 )2494.6722.3474219636416111.631220999842
Median2459.05
Midrange2460.95
Midmean - Weighted Average at Xnp2494.16451612903
Midmean - Weighted Average at X(n+1)p2500.07333333333
Midmean - Empirical Distribution Function2494.16451612903
Midmean - Empirical Distribution Function - Averaging2500.07333333333
Midmean - Empirical Distribution Function - Interpolation2500.07333333333
Midmean - Closest Observation2494.16451612903
Midmean - True Basic - Statistics Graphics Toolkit2500.07333333333
Midmean - MS Excel (old versions)2502.24375
Number of observations60



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
geomean <- function(x) {
return(exp(mean(log(x))))
}
harmean <- function(x) {
return(1/mean(1/x))
}
quamean <- function(x) {
return(sqrt(mean(x*x)))
}
winmean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
win <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n
win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn
}
return(win)
}
trimean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
tri <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
tri[j,1] <- mean(x,trim=j/n)
tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2)
}
return(tri)
}
midrange <- function(x) {
return((max(x)+min(x))/2)
}
q1 <- function(data,n,p,i,f) {
np <- n*p;
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q2 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q3 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
q4 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- (data[i]+data[i+1])/2
} else {
qvalue <- data[i+1]
}
}
q5 <- function(data,n,p,i,f) {
np <- (n-1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i+1]
} else {
qvalue <- data[i+1] + f*(data[i+2]-data[i+1])
}
}
q6 <- function(data,n,p,i,f) {
np <- n*p+0.5
i <<- floor(np)
f <<- np - i
qvalue <- data[i]
}
q7 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- f*data[i] + (1-f)*data[i+1]
}
}
q8 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
if (f == 0.5) {
qvalue <- (data[i]+data[i+1])/2
} else {
if (f < 0.5) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
}
}
midmean <- function(x,def) {
x <-sort(x[!is.na(x)])
n<-length(x)
if (def==1) {
qvalue1 <- q1(x,n,0.25,i,f)
qvalue3 <- q1(x,n,0.75,i,f)
}
if (def==2) {
qvalue1 <- q2(x,n,0.25,i,f)
qvalue3 <- q2(x,n,0.75,i,f)
}
if (def==3) {
qvalue1 <- q3(x,n,0.25,i,f)
qvalue3 <- q3(x,n,0.75,i,f)
}
if (def==4) {
qvalue1 <- q4(x,n,0.25,i,f)
qvalue3 <- q4(x,n,0.75,i,f)
}
if (def==5) {
qvalue1 <- q5(x,n,0.25,i,f)
qvalue3 <- q5(x,n,0.75,i,f)
}
if (def==6) {
qvalue1 <- q6(x,n,0.25,i,f)
qvalue3 <- q6(x,n,0.75,i,f)
}
if (def==7) {
qvalue1 <- q7(x,n,0.25,i,f)
qvalue3 <- q7(x,n,0.75,i,f)
}
if (def==8) {
qvalue1 <- q8(x,n,0.25,i,f)
qvalue3 <- q8(x,n,0.75,i,f)
}
midm <- 0
myn <- 0
roundno4 <- round(n/4)
round3no4 <- round(3*n/4)
for (i in 1:n) {
if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){
midm = midm + x[i]
myn = myn + 1
}
}
midm = midm / myn
return(midm)
}
(arm <- mean(x))
sqrtn <- sqrt(length(x))
(armse <- sd(x) / sqrtn)
(armose <- arm / armse)
(geo <- geomean(x))
(har <- harmean(x))
(qua <- quamean(x))
(win <- winmean(x))
(tri <- trimean(x))
(midr <- midrange(x))
midm <- array(NA,dim=8)
for (j in 1:8) midm[j] <- midmean(x,j)
midm
bitmap(file='test1.png')
lb <- win[,1] - 2*win[,2]
ub <- win[,1] + 2*win[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
bitmap(file='test2.png')
lb <- tri[,1] - 2*tri[,2]
ub <- tri[,1] + 2*tri[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Measure',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.element(a,'S.E.',header=TRUE)
a<-table.element(a,'Value/S.E.',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE)
a<-table.element(a,arm)
a<-table.element(a,hyperlink('arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean'))
a<-table.element(a,armose)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE)
a<-table.element(a,geo)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE)
a<-table.element(a,har)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE)
a<-table.element(a,qua)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
for (j in 1:length(win[,1])) {
a<-table.row.start(a)
mylabel <- paste('Winsorized Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(win[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE)
a<-table.element(a,win[j,1])
a<-table.element(a,win[j,2])
a<-table.element(a,win[j,1]/win[j,2])
a<-table.row.end(a)
}
for (j in 1:length(tri[,1])) {
a<-table.row.start(a)
mylabel <- paste('Trimmed Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(tri[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE)
a<-table.element(a,tri[j,1])
a<-table.element(a,tri[j,2])
a<-table.element(a,tri[j,1]/tri[j,2])
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,hyperlink('median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE)
a<-table.element(a,median(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE)
a<-table.element(a,midr)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_1.htm','Weighted Average at Xnp',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[2])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_3.htm','Empirical Distribution Function',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[3])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[4])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[5])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_6.htm','Closest Observation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[6])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[7])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_8.htm','MS Excel (old versions)',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[8])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')