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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSun, 06 Aug 2017 19:42:51 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Aug/06/t15020415968biwy0yh6xv96xe.htm/, Retrieved Mon, 20 May 2024 06:25:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=306977, Retrieved Mon, 20 May 2024 06:25:06 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact115
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2017-08-06 17:42:51] [eec775fda337aa2da775a098928b5865] [Current]
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Dataseries X:
3469648
3456726
3443622
3416504
3684772
3670576
3469648
3336060
3348982
3348982
3363360
3389204
3429426
3429426
3403582
3336060
3684772
3737916
3657654
3469648
3550092
3429426
3483844
3509870
3536988
3469648
3483844
3389204
3684772
3778138
3697876
3550092
3710798
3536988
3697876
3684772
3724994
3577210
3737916
3724994
3966144
3911726
3697876
3590132
3737916
3536988
3684772
3710798
3765216
3644732
3710798
3751020
3898804
3778138
3617432
3443622
3604510
3162250
3376282
3496766
3617432
3443622
3443622
3443622
3536988
3403582
3228498
3081988
3188276
2773316
3027570
3175354
3202472
3054688
3067610
3027570
3162250
3067610
2881060
2746198
2974244
2479022
2800616
2947126
2947126
2773316
2612610
2599688
2746198
2612610
2358538
2183454
2371460
1929382
2331238
2545088
2612610
2464826
2278094
2411682
2464826
2424604
2022566
1836016
1969422
1567566
1982526
2130310
2250794
2049866
1861860
1969422
2022566
1916278
1514422
1339338
1500044
1057966
1540266
1836016




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306977&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=306977&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306977&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean305334063013.648.4552
Geometric Mean2957850
Harmonic Mean2839740
Quadratic Mean3129760
Winsorized Mean ( 1 / 40 )305523062376.748.9804
Winsorized Mean ( 2 / 40 )305769061758.449.5106
Winsorized Mean ( 3 / 40 )305504061360.349.7885
Winsorized Mean ( 4 / 40 )305590061179.749.9495
Winsorized Mean ( 5 / 40 )305650060891.450.1959
Winsorized Mean ( 6 / 40 )306921058244.652.6952
Winsorized Mean ( 7 / 40 )30684505817052.7496
Winsorized Mean ( 8 / 40 )307017057865.553.057
Winsorized Mean ( 9 / 40 )307425057159.953.7833
Winsorized Mean ( 10 / 40 )307427056870.354.0575
Winsorized Mean ( 11 / 40 )307794056255.954.7131
Winsorized Mean ( 12 / 40 )307652056119.954.8204
Winsorized Mean ( 13 / 40 )307794055885.355.0759
Winsorized Mean ( 14 / 40 )308261055123.155.9222
Winsorized Mean ( 15 / 40 )308099054969.656.049
Winsorized Mean ( 16 / 40 )308463054384.156.7194
Winsorized Mean ( 17 / 40 )309603052593.258.8674
Winsorized Mean ( 18 / 40 )310203051188.460.6003
Winsorized Mean ( 19 / 40 )311270049605.762.7487
Winsorized Mean ( 20 / 40 )311725048945.863.6878
Winsorized Mean ( 21 / 40 )31265504762365.652
Winsorized Mean ( 22 / 40 )313155046925.466.7347
Winsorized Mean ( 23 / 40 )313131046315.367.6085
Winsorized Mean ( 24 / 40 )313677044963.369.7628
Winsorized Mean ( 25 / 40 )313677044338.670.7457
Winsorized Mean ( 26 / 40 )313957042606.873.6869
Winsorized Mean ( 27 / 40 )313957042606.873.6869
Winsorized Mean ( 28 / 40 )313986041884.274.9654
Winsorized Mean ( 29 / 40 )315236039468.979.8693
Winsorized Mean ( 30 / 40 )316277037422.184.5162
Winsorized Mean ( 31 / 40 )315911036357.686.8899
Winsorized Mean ( 32 / 40 )315911036357.686.8899
Winsorized Mean ( 33 / 40 )315550036034.487.5691
Winsorized Mean ( 34 / 40 )319335031362.1101.822
Winsorized Mean ( 35 / 40 )319335031362.1101.822
Winsorized Mean ( 36 / 40 )320149030393.1105.336
Winsorized Mean ( 37 / 40 )319313029629.5107.768
Winsorized Mean ( 38 / 40 )319762028232.8113.259
Winsorized Mean ( 39 / 40 )321957024811.6129.76
Winsorized Mean ( 40 / 40 )324159022326.7145.189
Trimmed Mean ( 1 / 40 )306251061299.149.9602
Trimmed Mean ( 2 / 40 )307005060097.451.0845
Trimmed Mean ( 3 / 40 )307655059119.152.0398
Trimmed Mean ( 4 / 40 )308423058182.253.0099
Trimmed Mean ( 5 / 40 )309196057187.754.0669
Trimmed Mean ( 6 / 40 )30998405614655.2104
Trimmed Mean ( 7 / 40 )310562055597.755.8589
Trimmed Mean ( 8 / 40 )311175054986.956.5908
Trimmed Mean ( 9 / 40 )31178705434957.3675
Trimmed Mean ( 10 / 40 )31236805374758.1182
Trimmed Mean ( 11 / 40 )312973053103.858.9361
Trimmed Mean ( 12 / 40 )313562052464.559.7664
Trimmed Mean ( 13 / 40 )314190051746.560.7172
Trimmed Mean ( 14 / 40 )314832050954.761.7867
Trimmed Mean ( 15 / 40 )315458050155.462.8961
Trimmed Mean ( 16 / 40 )316127049248.764.19
Trimmed Mean ( 17 / 40 )31679604828465.6109
Trimmed Mean ( 18 / 40 )317400047425.966.9255
Trimmed Mean ( 19 / 40 )317985046621.268.2061
Trimmed Mean ( 20 / 40 )318515045902.269.39
Trimmed Mean ( 21 / 40 )319038045147.170.6663
Trimmed Mean ( 22 / 40 )319518044440.971.8971
Trimmed Mean ( 23 / 40 )319986043700.173.2233
Trimmed Mean ( 24 / 40 )320483042896.474.711
Trimmed Mean ( 25 / 40 )320969042124.776.195
Trimmed Mean ( 26 / 40 )321484041279.477.8801
Trimmed Mean ( 27 / 40 )322011040500.879.5073
Trimmed Mean ( 28 / 40 )322570039549.381.5616
Trimmed Mean ( 29 / 40 )323163038491.683.9569
Trimmed Mean ( 30 / 40 )323710037588.986.1185
Trimmed Mean ( 31 / 40 )324223036804.788.0927
Trimmed Mean ( 32 / 40 )324797035970.990.2945
Trimmed Mean ( 33 / 40 )325414034911.393.2118
Trimmed Mean ( 34 / 40 )326104033600.997.0522
Trimmed Mean ( 35 / 40 )326582032899.499.2668
Trimmed Mean ( 36 / 40 )327100031978.1102.289
Trimmed Mean ( 37 / 40 )327603030985.3105.729
Trimmed Mean ( 38 / 40 )328214029783.7110.199
Trimmed Mean ( 39 / 40 )328850028500.1115.385
Trimmed Mean ( 40 / 40 )329380027658.8119.087
Median3369820
Midrange2512060
Midmean - Weighted Average at Xnp3225760
Midmean - Weighted Average at X(n+1)p3237100
Midmean - Empirical Distribution Function3225760
Midmean - Empirical Distribution Function - Averaging3237100
Midmean - Empirical Distribution Function - Interpolation3237100
Midmean - Closest Observation3225760
Midmean - True Basic - Statistics Graphics Toolkit3237100
Midmean - MS Excel (old versions)3231630
Number of observations120

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 3053340 & 63013.6 & 48.4552 \tabularnewline
Geometric Mean & 2957850 &  &  \tabularnewline
Harmonic Mean & 2839740 &  &  \tabularnewline
Quadratic Mean & 3129760 &  &  \tabularnewline
Winsorized Mean ( 1 / 40 ) & 3055230 & 62376.7 & 48.9804 \tabularnewline
Winsorized Mean ( 2 / 40 ) & 3057690 & 61758.4 & 49.5106 \tabularnewline
Winsorized Mean ( 3 / 40 ) & 3055040 & 61360.3 & 49.7885 \tabularnewline
Winsorized Mean ( 4 / 40 ) & 3055900 & 61179.7 & 49.9495 \tabularnewline
Winsorized Mean ( 5 / 40 ) & 3056500 & 60891.4 & 50.1959 \tabularnewline
Winsorized Mean ( 6 / 40 ) & 3069210 & 58244.6 & 52.6952 \tabularnewline
Winsorized Mean ( 7 / 40 ) & 3068450 & 58170 & 52.7496 \tabularnewline
Winsorized Mean ( 8 / 40 ) & 3070170 & 57865.5 & 53.057 \tabularnewline
Winsorized Mean ( 9 / 40 ) & 3074250 & 57159.9 & 53.7833 \tabularnewline
Winsorized Mean ( 10 / 40 ) & 3074270 & 56870.3 & 54.0575 \tabularnewline
Winsorized Mean ( 11 / 40 ) & 3077940 & 56255.9 & 54.7131 \tabularnewline
Winsorized Mean ( 12 / 40 ) & 3076520 & 56119.9 & 54.8204 \tabularnewline
Winsorized Mean ( 13 / 40 ) & 3077940 & 55885.3 & 55.0759 \tabularnewline
Winsorized Mean ( 14 / 40 ) & 3082610 & 55123.1 & 55.9222 \tabularnewline
Winsorized Mean ( 15 / 40 ) & 3080990 & 54969.6 & 56.049 \tabularnewline
Winsorized Mean ( 16 / 40 ) & 3084630 & 54384.1 & 56.7194 \tabularnewline
Winsorized Mean ( 17 / 40 ) & 3096030 & 52593.2 & 58.8674 \tabularnewline
Winsorized Mean ( 18 / 40 ) & 3102030 & 51188.4 & 60.6003 \tabularnewline
Winsorized Mean ( 19 / 40 ) & 3112700 & 49605.7 & 62.7487 \tabularnewline
Winsorized Mean ( 20 / 40 ) & 3117250 & 48945.8 & 63.6878 \tabularnewline
Winsorized Mean ( 21 / 40 ) & 3126550 & 47623 & 65.652 \tabularnewline
Winsorized Mean ( 22 / 40 ) & 3131550 & 46925.4 & 66.7347 \tabularnewline
Winsorized Mean ( 23 / 40 ) & 3131310 & 46315.3 & 67.6085 \tabularnewline
Winsorized Mean ( 24 / 40 ) & 3136770 & 44963.3 & 69.7628 \tabularnewline
Winsorized Mean ( 25 / 40 ) & 3136770 & 44338.6 & 70.7457 \tabularnewline
Winsorized Mean ( 26 / 40 ) & 3139570 & 42606.8 & 73.6869 \tabularnewline
Winsorized Mean ( 27 / 40 ) & 3139570 & 42606.8 & 73.6869 \tabularnewline
Winsorized Mean ( 28 / 40 ) & 3139860 & 41884.2 & 74.9654 \tabularnewline
Winsorized Mean ( 29 / 40 ) & 3152360 & 39468.9 & 79.8693 \tabularnewline
Winsorized Mean ( 30 / 40 ) & 3162770 & 37422.1 & 84.5162 \tabularnewline
Winsorized Mean ( 31 / 40 ) & 3159110 & 36357.6 & 86.8899 \tabularnewline
Winsorized Mean ( 32 / 40 ) & 3159110 & 36357.6 & 86.8899 \tabularnewline
Winsorized Mean ( 33 / 40 ) & 3155500 & 36034.4 & 87.5691 \tabularnewline
Winsorized Mean ( 34 / 40 ) & 3193350 & 31362.1 & 101.822 \tabularnewline
Winsorized Mean ( 35 / 40 ) & 3193350 & 31362.1 & 101.822 \tabularnewline
Winsorized Mean ( 36 / 40 ) & 3201490 & 30393.1 & 105.336 \tabularnewline
Winsorized Mean ( 37 / 40 ) & 3193130 & 29629.5 & 107.768 \tabularnewline
Winsorized Mean ( 38 / 40 ) & 3197620 & 28232.8 & 113.259 \tabularnewline
Winsorized Mean ( 39 / 40 ) & 3219570 & 24811.6 & 129.76 \tabularnewline
Winsorized Mean ( 40 / 40 ) & 3241590 & 22326.7 & 145.189 \tabularnewline
Trimmed Mean ( 1 / 40 ) & 3062510 & 61299.1 & 49.9602 \tabularnewline
Trimmed Mean ( 2 / 40 ) & 3070050 & 60097.4 & 51.0845 \tabularnewline
Trimmed Mean ( 3 / 40 ) & 3076550 & 59119.1 & 52.0398 \tabularnewline
Trimmed Mean ( 4 / 40 ) & 3084230 & 58182.2 & 53.0099 \tabularnewline
Trimmed Mean ( 5 / 40 ) & 3091960 & 57187.7 & 54.0669 \tabularnewline
Trimmed Mean ( 6 / 40 ) & 3099840 & 56146 & 55.2104 \tabularnewline
Trimmed Mean ( 7 / 40 ) & 3105620 & 55597.7 & 55.8589 \tabularnewline
Trimmed Mean ( 8 / 40 ) & 3111750 & 54986.9 & 56.5908 \tabularnewline
Trimmed Mean ( 9 / 40 ) & 3117870 & 54349 & 57.3675 \tabularnewline
Trimmed Mean ( 10 / 40 ) & 3123680 & 53747 & 58.1182 \tabularnewline
Trimmed Mean ( 11 / 40 ) & 3129730 & 53103.8 & 58.9361 \tabularnewline
Trimmed Mean ( 12 / 40 ) & 3135620 & 52464.5 & 59.7664 \tabularnewline
Trimmed Mean ( 13 / 40 ) & 3141900 & 51746.5 & 60.7172 \tabularnewline
Trimmed Mean ( 14 / 40 ) & 3148320 & 50954.7 & 61.7867 \tabularnewline
Trimmed Mean ( 15 / 40 ) & 3154580 & 50155.4 & 62.8961 \tabularnewline
Trimmed Mean ( 16 / 40 ) & 3161270 & 49248.7 & 64.19 \tabularnewline
Trimmed Mean ( 17 / 40 ) & 3167960 & 48284 & 65.6109 \tabularnewline
Trimmed Mean ( 18 / 40 ) & 3174000 & 47425.9 & 66.9255 \tabularnewline
Trimmed Mean ( 19 / 40 ) & 3179850 & 46621.2 & 68.2061 \tabularnewline
Trimmed Mean ( 20 / 40 ) & 3185150 & 45902.2 & 69.39 \tabularnewline
Trimmed Mean ( 21 / 40 ) & 3190380 & 45147.1 & 70.6663 \tabularnewline
Trimmed Mean ( 22 / 40 ) & 3195180 & 44440.9 & 71.8971 \tabularnewline
Trimmed Mean ( 23 / 40 ) & 3199860 & 43700.1 & 73.2233 \tabularnewline
Trimmed Mean ( 24 / 40 ) & 3204830 & 42896.4 & 74.711 \tabularnewline
Trimmed Mean ( 25 / 40 ) & 3209690 & 42124.7 & 76.195 \tabularnewline
Trimmed Mean ( 26 / 40 ) & 3214840 & 41279.4 & 77.8801 \tabularnewline
Trimmed Mean ( 27 / 40 ) & 3220110 & 40500.8 & 79.5073 \tabularnewline
Trimmed Mean ( 28 / 40 ) & 3225700 & 39549.3 & 81.5616 \tabularnewline
Trimmed Mean ( 29 / 40 ) & 3231630 & 38491.6 & 83.9569 \tabularnewline
Trimmed Mean ( 30 / 40 ) & 3237100 & 37588.9 & 86.1185 \tabularnewline
Trimmed Mean ( 31 / 40 ) & 3242230 & 36804.7 & 88.0927 \tabularnewline
Trimmed Mean ( 32 / 40 ) & 3247970 & 35970.9 & 90.2945 \tabularnewline
Trimmed Mean ( 33 / 40 ) & 3254140 & 34911.3 & 93.2118 \tabularnewline
Trimmed Mean ( 34 / 40 ) & 3261040 & 33600.9 & 97.0522 \tabularnewline
Trimmed Mean ( 35 / 40 ) & 3265820 & 32899.4 & 99.2668 \tabularnewline
Trimmed Mean ( 36 / 40 ) & 3271000 & 31978.1 & 102.289 \tabularnewline
Trimmed Mean ( 37 / 40 ) & 3276030 & 30985.3 & 105.729 \tabularnewline
Trimmed Mean ( 38 / 40 ) & 3282140 & 29783.7 & 110.199 \tabularnewline
Trimmed Mean ( 39 / 40 ) & 3288500 & 28500.1 & 115.385 \tabularnewline
Trimmed Mean ( 40 / 40 ) & 3293800 & 27658.8 & 119.087 \tabularnewline
Median & 3369820 &  &  \tabularnewline
Midrange & 2512060 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 3225760 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 3237100 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 3225760 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 3237100 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 3237100 &  &  \tabularnewline
Midmean - Closest Observation & 3225760 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 3237100 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 3231630 &  &  \tabularnewline
Number of observations & 120 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306977&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]3053340[/C][C]63013.6[/C][C]48.4552[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]2957850[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]2839740[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]3129760[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 40 )[/C][C]3055230[/C][C]62376.7[/C][C]48.9804[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 40 )[/C][C]3057690[/C][C]61758.4[/C][C]49.5106[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 40 )[/C][C]3055040[/C][C]61360.3[/C][C]49.7885[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 40 )[/C][C]3055900[/C][C]61179.7[/C][C]49.9495[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 40 )[/C][C]3056500[/C][C]60891.4[/C][C]50.1959[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 40 )[/C][C]3069210[/C][C]58244.6[/C][C]52.6952[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 40 )[/C][C]3068450[/C][C]58170[/C][C]52.7496[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 40 )[/C][C]3070170[/C][C]57865.5[/C][C]53.057[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 40 )[/C][C]3074250[/C][C]57159.9[/C][C]53.7833[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 40 )[/C][C]3074270[/C][C]56870.3[/C][C]54.0575[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 40 )[/C][C]3077940[/C][C]56255.9[/C][C]54.7131[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 40 )[/C][C]3076520[/C][C]56119.9[/C][C]54.8204[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 40 )[/C][C]3077940[/C][C]55885.3[/C][C]55.0759[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 40 )[/C][C]3082610[/C][C]55123.1[/C][C]55.9222[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 40 )[/C][C]3080990[/C][C]54969.6[/C][C]56.049[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 40 )[/C][C]3084630[/C][C]54384.1[/C][C]56.7194[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 40 )[/C][C]3096030[/C][C]52593.2[/C][C]58.8674[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 40 )[/C][C]3102030[/C][C]51188.4[/C][C]60.6003[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 40 )[/C][C]3112700[/C][C]49605.7[/C][C]62.7487[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 40 )[/C][C]3117250[/C][C]48945.8[/C][C]63.6878[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 40 )[/C][C]3126550[/C][C]47623[/C][C]65.652[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 40 )[/C][C]3131550[/C][C]46925.4[/C][C]66.7347[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 40 )[/C][C]3131310[/C][C]46315.3[/C][C]67.6085[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 40 )[/C][C]3136770[/C][C]44963.3[/C][C]69.7628[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 40 )[/C][C]3136770[/C][C]44338.6[/C][C]70.7457[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 40 )[/C][C]3139570[/C][C]42606.8[/C][C]73.6869[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 40 )[/C][C]3139570[/C][C]42606.8[/C][C]73.6869[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 40 )[/C][C]3139860[/C][C]41884.2[/C][C]74.9654[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 40 )[/C][C]3152360[/C][C]39468.9[/C][C]79.8693[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 40 )[/C][C]3162770[/C][C]37422.1[/C][C]84.5162[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 40 )[/C][C]3159110[/C][C]36357.6[/C][C]86.8899[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 40 )[/C][C]3159110[/C][C]36357.6[/C][C]86.8899[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 40 )[/C][C]3155500[/C][C]36034.4[/C][C]87.5691[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 40 )[/C][C]3193350[/C][C]31362.1[/C][C]101.822[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 40 )[/C][C]3193350[/C][C]31362.1[/C][C]101.822[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 40 )[/C][C]3201490[/C][C]30393.1[/C][C]105.336[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 40 )[/C][C]3193130[/C][C]29629.5[/C][C]107.768[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 40 )[/C][C]3197620[/C][C]28232.8[/C][C]113.259[/C][/ROW]
[ROW][C]Winsorized Mean ( 39 / 40 )[/C][C]3219570[/C][C]24811.6[/C][C]129.76[/C][/ROW]
[ROW][C]Winsorized Mean ( 40 / 40 )[/C][C]3241590[/C][C]22326.7[/C][C]145.189[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 40 )[/C][C]3062510[/C][C]61299.1[/C][C]49.9602[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 40 )[/C][C]3070050[/C][C]60097.4[/C][C]51.0845[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 40 )[/C][C]3076550[/C][C]59119.1[/C][C]52.0398[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 40 )[/C][C]3084230[/C][C]58182.2[/C][C]53.0099[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 40 )[/C][C]3091960[/C][C]57187.7[/C][C]54.0669[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 40 )[/C][C]3099840[/C][C]56146[/C][C]55.2104[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 40 )[/C][C]3105620[/C][C]55597.7[/C][C]55.8589[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 40 )[/C][C]3111750[/C][C]54986.9[/C][C]56.5908[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 40 )[/C][C]3117870[/C][C]54349[/C][C]57.3675[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 40 )[/C][C]3123680[/C][C]53747[/C][C]58.1182[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 40 )[/C][C]3129730[/C][C]53103.8[/C][C]58.9361[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 40 )[/C][C]3135620[/C][C]52464.5[/C][C]59.7664[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 40 )[/C][C]3141900[/C][C]51746.5[/C][C]60.7172[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 40 )[/C][C]3148320[/C][C]50954.7[/C][C]61.7867[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 40 )[/C][C]3154580[/C][C]50155.4[/C][C]62.8961[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 40 )[/C][C]3161270[/C][C]49248.7[/C][C]64.19[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 40 )[/C][C]3167960[/C][C]48284[/C][C]65.6109[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 40 )[/C][C]3174000[/C][C]47425.9[/C][C]66.9255[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 40 )[/C][C]3179850[/C][C]46621.2[/C][C]68.2061[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 40 )[/C][C]3185150[/C][C]45902.2[/C][C]69.39[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 40 )[/C][C]3190380[/C][C]45147.1[/C][C]70.6663[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 40 )[/C][C]3195180[/C][C]44440.9[/C][C]71.8971[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 40 )[/C][C]3199860[/C][C]43700.1[/C][C]73.2233[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 40 )[/C][C]3204830[/C][C]42896.4[/C][C]74.711[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 40 )[/C][C]3209690[/C][C]42124.7[/C][C]76.195[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 40 )[/C][C]3214840[/C][C]41279.4[/C][C]77.8801[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 40 )[/C][C]3220110[/C][C]40500.8[/C][C]79.5073[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 40 )[/C][C]3225700[/C][C]39549.3[/C][C]81.5616[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 40 )[/C][C]3231630[/C][C]38491.6[/C][C]83.9569[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 40 )[/C][C]3237100[/C][C]37588.9[/C][C]86.1185[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 40 )[/C][C]3242230[/C][C]36804.7[/C][C]88.0927[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 40 )[/C][C]3247970[/C][C]35970.9[/C][C]90.2945[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 40 )[/C][C]3254140[/C][C]34911.3[/C][C]93.2118[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 40 )[/C][C]3261040[/C][C]33600.9[/C][C]97.0522[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 40 )[/C][C]3265820[/C][C]32899.4[/C][C]99.2668[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 40 )[/C][C]3271000[/C][C]31978.1[/C][C]102.289[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 40 )[/C][C]3276030[/C][C]30985.3[/C][C]105.729[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 40 )[/C][C]3282140[/C][C]29783.7[/C][C]110.199[/C][/ROW]
[ROW][C]Trimmed Mean ( 39 / 40 )[/C][C]3288500[/C][C]28500.1[/C][C]115.385[/C][/ROW]
[ROW][C]Trimmed Mean ( 40 / 40 )[/C][C]3293800[/C][C]27658.8[/C][C]119.087[/C][/ROW]
[ROW][C]Median[/C][C]3369820[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]2512060[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]3225760[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]3237100[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]3225760[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]3237100[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]3237100[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]3225760[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]3237100[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]3231630[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]120[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306977&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306977&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 Mean305334063013.648.4552
Geometric Mean2957850
Harmonic Mean2839740
Quadratic Mean3129760
Winsorized Mean ( 1 / 40 )305523062376.748.9804
Winsorized Mean ( 2 / 40 )305769061758.449.5106
Winsorized Mean ( 3 / 40 )305504061360.349.7885
Winsorized Mean ( 4 / 40 )305590061179.749.9495
Winsorized Mean ( 5 / 40 )305650060891.450.1959
Winsorized Mean ( 6 / 40 )306921058244.652.6952
Winsorized Mean ( 7 / 40 )30684505817052.7496
Winsorized Mean ( 8 / 40 )307017057865.553.057
Winsorized Mean ( 9 / 40 )307425057159.953.7833
Winsorized Mean ( 10 / 40 )307427056870.354.0575
Winsorized Mean ( 11 / 40 )307794056255.954.7131
Winsorized Mean ( 12 / 40 )307652056119.954.8204
Winsorized Mean ( 13 / 40 )307794055885.355.0759
Winsorized Mean ( 14 / 40 )308261055123.155.9222
Winsorized Mean ( 15 / 40 )308099054969.656.049
Winsorized Mean ( 16 / 40 )308463054384.156.7194
Winsorized Mean ( 17 / 40 )309603052593.258.8674
Winsorized Mean ( 18 / 40 )310203051188.460.6003
Winsorized Mean ( 19 / 40 )311270049605.762.7487
Winsorized Mean ( 20 / 40 )311725048945.863.6878
Winsorized Mean ( 21 / 40 )31265504762365.652
Winsorized Mean ( 22 / 40 )313155046925.466.7347
Winsorized Mean ( 23 / 40 )313131046315.367.6085
Winsorized Mean ( 24 / 40 )313677044963.369.7628
Winsorized Mean ( 25 / 40 )313677044338.670.7457
Winsorized Mean ( 26 / 40 )313957042606.873.6869
Winsorized Mean ( 27 / 40 )313957042606.873.6869
Winsorized Mean ( 28 / 40 )313986041884.274.9654
Winsorized Mean ( 29 / 40 )315236039468.979.8693
Winsorized Mean ( 30 / 40 )316277037422.184.5162
Winsorized Mean ( 31 / 40 )315911036357.686.8899
Winsorized Mean ( 32 / 40 )315911036357.686.8899
Winsorized Mean ( 33 / 40 )315550036034.487.5691
Winsorized Mean ( 34 / 40 )319335031362.1101.822
Winsorized Mean ( 35 / 40 )319335031362.1101.822
Winsorized Mean ( 36 / 40 )320149030393.1105.336
Winsorized Mean ( 37 / 40 )319313029629.5107.768
Winsorized Mean ( 38 / 40 )319762028232.8113.259
Winsorized Mean ( 39 / 40 )321957024811.6129.76
Winsorized Mean ( 40 / 40 )324159022326.7145.189
Trimmed Mean ( 1 / 40 )306251061299.149.9602
Trimmed Mean ( 2 / 40 )307005060097.451.0845
Trimmed Mean ( 3 / 40 )307655059119.152.0398
Trimmed Mean ( 4 / 40 )308423058182.253.0099
Trimmed Mean ( 5 / 40 )309196057187.754.0669
Trimmed Mean ( 6 / 40 )30998405614655.2104
Trimmed Mean ( 7 / 40 )310562055597.755.8589
Trimmed Mean ( 8 / 40 )311175054986.956.5908
Trimmed Mean ( 9 / 40 )31178705434957.3675
Trimmed Mean ( 10 / 40 )31236805374758.1182
Trimmed Mean ( 11 / 40 )312973053103.858.9361
Trimmed Mean ( 12 / 40 )313562052464.559.7664
Trimmed Mean ( 13 / 40 )314190051746.560.7172
Trimmed Mean ( 14 / 40 )314832050954.761.7867
Trimmed Mean ( 15 / 40 )315458050155.462.8961
Trimmed Mean ( 16 / 40 )316127049248.764.19
Trimmed Mean ( 17 / 40 )31679604828465.6109
Trimmed Mean ( 18 / 40 )317400047425.966.9255
Trimmed Mean ( 19 / 40 )317985046621.268.2061
Trimmed Mean ( 20 / 40 )318515045902.269.39
Trimmed Mean ( 21 / 40 )319038045147.170.6663
Trimmed Mean ( 22 / 40 )319518044440.971.8971
Trimmed Mean ( 23 / 40 )319986043700.173.2233
Trimmed Mean ( 24 / 40 )320483042896.474.711
Trimmed Mean ( 25 / 40 )320969042124.776.195
Trimmed Mean ( 26 / 40 )321484041279.477.8801
Trimmed Mean ( 27 / 40 )322011040500.879.5073
Trimmed Mean ( 28 / 40 )322570039549.381.5616
Trimmed Mean ( 29 / 40 )323163038491.683.9569
Trimmed Mean ( 30 / 40 )323710037588.986.1185
Trimmed Mean ( 31 / 40 )324223036804.788.0927
Trimmed Mean ( 32 / 40 )324797035970.990.2945
Trimmed Mean ( 33 / 40 )325414034911.393.2118
Trimmed Mean ( 34 / 40 )326104033600.997.0522
Trimmed Mean ( 35 / 40 )326582032899.499.2668
Trimmed Mean ( 36 / 40 )327100031978.1102.289
Trimmed Mean ( 37 / 40 )327603030985.3105.729
Trimmed Mean ( 38 / 40 )328214029783.7110.199
Trimmed Mean ( 39 / 40 )328850028500.1115.385
Trimmed Mean ( 40 / 40 )329380027658.8119.087
Median3369820
Midrange2512060
Midmean - Weighted Average at Xnp3225760
Midmean - Weighted Average at X(n+1)p3237100
Midmean - Empirical Distribution Function3225760
Midmean - Empirical Distribution Function - Averaging3237100
Midmean - Empirical Distribution Function - Interpolation3237100
Midmean - Closest Observation3225760
Midmean - True Basic - Statistics Graphics Toolkit3237100
Midmean - MS Excel (old versions)3231630
Number of observations120



Parameters (Session):
par1 = 121260additive12grey0.10.01 ; par2 = 112Tripleno0.990.99 ; par3 = 0multiplicative0.10.01 ; par4 = 012 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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,'Arithmetic Mean',header=TRUE)
a<-table.element(a,signif(arm,6))
a<-table.element(a, signif(armse,6))
a<-table.element(a,signif(armose,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Geometric Mean',header=TRUE)
a<-table.element(a,signif(geo,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Harmonic Mean',header=TRUE)
a<-table.element(a,signif(har,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Quadratic Mean',header=TRUE)
a<-table.element(a,signif(qua,6))
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, mylabel,header=TRUE)
a<-table.element(a,signif(win[j,1],6))
a<-table.element(a,signif(win[j,2],6))
a<-table.element(a,signif(win[j,1]/win[j,2],6))
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, mylabel,header=TRUE)
a<-table.element(a,signif(tri[j,1],6))
a<-table.element(a,signif(tri[j,2],6))
a<-table.element(a,signif(tri[j,1]/tri[j,2],6))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'Median',header=TRUE)
a<-table.element(a,signif(median(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Midrange',header=TRUE)
a<-table.element(a,signif(midr,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Weighted Average at Xnp',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[1],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Weighted Average at X(n+1)p',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[2],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[3],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Averaging',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[4],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Interpolation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[5],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Closest Observation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[6],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'True Basic - Statistics Graphics Toolkit',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[7],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'MS Excel (old versions)',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[8],6))
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,signif(length(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')