Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSat, 05 Aug 2017 12:28:20 +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/05/t1501929829mrfjh57iqebczud.htm/, Retrieved Fri, 10 May 2024 11:52:42 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Fri, 10 May 2024 11:52:42 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
3221816
3209817
3197649
3172468
3421574
3408392
3221816
3097770
3109769
3109769
3123120
3147118
3184467
3184467
3160469
3097770
3421574
3470922
3396393
3221816
3296514
3184467
3234998
3259165
3284346
3221816
3234998
3147118
3421574
3508271
3433742
3296514
3445741
3284346
3433742
3421574
3458923
3321695
3470922
3458923
3682848
3632317
3433742
3333694
3470922
3284346
3421574
3445741
3496272
3384394
3445741
3483090
3620318
3508271
3359044
3197649
3347045
2936375
3135119
3246997
3359044
3197649
3197649
3197649
3284346
3160469
2997891
2861846
2960542
2575222
2811315
2948543
2973724
2836496
2848495
2811315
2936375
2848495
2675270
2550041
2761798
2301949
2600572
2736617
2736617
2575222
2425995
2413996
2550041
2425995
2190071
2027493
2202070
1791569
2164721
2363296
2425995
2288767
2115373
2239419
2288767
2251418
1878097
1704872
1828749
1455597
1840917
1978145
2090023
1903447
1728870
1828749
1878097
1779401
1406249
1243671
1392898
982397
1430247
1704872




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=&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=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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 Mean283524058512.648.4552
Geometric Mean2746570
Harmonic Mean2636900
Quadratic Mean2906210
Winsorized Mean ( 1 / 40 )283700057921.248.9804
Winsorized Mean ( 2 / 40 )28392905734749.5106
Winsorized Mean ( 3 / 40 )283682056977.449.7885
Winsorized Mean ( 4 / 40 )283762056809.749.9495
Winsorized Mean ( 5 / 40 )28381805654250.1959
Winsorized Mean ( 6 / 40 )284998054084.252.6952
Winsorized Mean ( 7 / 40 )28492705401552.7496
Winsorized Mean ( 8 / 40 )285087053732.253.057
Winsorized Mean ( 9 / 40 )285466053077.153.7833
Winsorized Mean ( 10 / 40 )285467052808.154.0575
Winsorized Mean ( 11 / 40 )285808052237.654.7131
Winsorized Mean ( 12 / 40 )285676052111.354.8204
Winsorized Mean ( 13 / 40 )285808051893.555.0759
Winsorized Mean ( 14 / 40 )286242051185.755.9222
Winsorized Mean ( 15 / 40 )286092051043.256.049
Winsorized Mean ( 16 / 40 )286430050499.556.7194
Winsorized Mean ( 17 / 40 )287488048836.658.8674
Winsorized Mean ( 18 / 40 )288046047532.160.6003
Winsorized Mean ( 19 / 40 )289036046062.562.7487
Winsorized Mean ( 20 / 40 )289459045449.663.6878
Winsorized Mean ( 21 / 40 )290322044221.465.652
Winsorized Mean ( 22 / 40 )290787043573.566.7347
Winsorized Mean ( 23 / 40 )290764043007.167.6085
Winsorized Mean ( 24 / 40 )291271041751.769.7628
Winsorized Mean ( 25 / 40 )291271041171.670.7457
Winsorized Mean ( 26 / 40 )291531039563.573.6869
Winsorized Mean ( 27 / 40 )291531039563.573.6869
Winsorized Mean ( 28 / 40 )291559038892.574.9654
Winsorized Mean ( 29 / 40 )292719036649.779.8693
Winsorized Mean ( 30 / 40 )293686034749.184.5162
Winsorized Mean ( 31 / 40 )293346033760.686.8899
Winsorized Mean ( 32 / 40 )293346033760.686.8899
Winsorized Mean ( 33 / 40 )293011033460.687.5691
Winsorized Mean ( 34 / 40 )296526029121.9101.822
Winsorized Mean ( 35 / 40 )296526029121.9101.822
Winsorized Mean ( 36 / 40 )297281028222.1105.336
Winsorized Mean ( 37 / 40 )296505027513.1107.768
Winsorized Mean ( 38 / 40 )296922026216.2113.259
Winsorized Mean ( 39 / 40 )298960023039.4129.76
Winsorized Mean ( 40 / 40 )301005020731.9145.189
Trimmed Mean ( 1 / 40 )284376056920.649.9602
Trimmed Mean ( 2 / 40 )285076055804.851.0845
Trimmed Mean ( 3 / 40 )285680054896.352.0398
Trimmed Mean ( 4 / 40 )286393054026.353.0099
Trimmed Mean ( 5 / 40 )287111053102.954.0669
Trimmed Mean ( 6 / 40 )287843052135.555.2104
Trimmed Mean ( 7 / 40 )288379051626.455.8589
Trimmed Mean ( 8 / 40 )288948051059.256.5908
Trimmed Mean ( 9 / 40 )289516050466.957.3675
Trimmed Mean ( 10 / 40 )290056049907.958.1182
Trimmed Mean ( 11 / 40 )290618049310.758.9361
Trimmed Mean ( 12 / 40 )291164048717.159.7664
Trimmed Mean ( 13 / 40 )291748048050.460.7172
Trimmed Mean ( 14 / 40 )292344047315.161.7867
Trimmed Mean ( 15 / 40 )292925046572.962.8961
Trimmed Mean ( 16 / 40 )293547045730.964.19
Trimmed Mean ( 17 / 40 )294167044835.165.6109
Trimmed Mean ( 18 / 40 )294729044038.366.9255
Trimmed Mean ( 19 / 40 )295272043291.168.2061
Trimmed Mean ( 20 / 40 )295764042623.469.39
Trimmed Mean ( 21 / 40 )296249041922.370.6663
Trimmed Mean ( 22 / 40 )296695041266.671.8971
Trimmed Mean ( 23 / 40 )297130040578.773.2233
Trimmed Mean ( 24 / 40 )297592039832.474.711
Trimmed Mean ( 25 / 40 )298043039115.876.195
Trimmed Mean ( 26 / 40 )298521038330.977.8801
Trimmed Mean ( 27 / 40 )299010037607.979.5073
Trimmed Mean ( 28 / 40 )299529036724.381.5616
Trimmed Mean ( 29 / 40 )300080035742.283.9569
Trimmed Mean ( 30 / 40 )30058803490486.1185
Trimmed Mean ( 31 / 40 )301064034175.888.0927
Trimmed Mean ( 32 / 40 )301597033401.590.2945
Trimmed Mean ( 33 / 40 )302170032417.693.2118
Trimmed Mean ( 34 / 40 )302811031200.897.0522
Trimmed Mean ( 35 / 40 )303255030549.599.2668
Trimmed Mean ( 36 / 40 )303735029694102.289
Trimmed Mean ( 37 / 40 )304203028772105.729
Trimmed Mean ( 38 / 40 )304770027656.3110.199
Trimmed Mean ( 39 / 40 )305360026464.4115.385
Trimmed Mean ( 40 / 40 )305853025683.2119.087
Median3129120
Midrange2332620
Midmean - Weighted Average at Xnp2995340
Midmean - Weighted Average at X(n+1)p3005880
Midmean - Empirical Distribution Function2995340
Midmean - Empirical Distribution Function - Averaging3005880
Midmean - Empirical Distribution Function - Interpolation3005880
Midmean - Closest Observation2995340
Midmean - True Basic - Statistics Graphics Toolkit3005880
Midmean - MS Excel (old versions)3000800
Number of observations120

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 2835240 & 58512.6 & 48.4552 \tabularnewline
Geometric Mean & 2746570 &  &  \tabularnewline
Harmonic Mean & 2636900 &  &  \tabularnewline
Quadratic Mean & 2906210 &  &  \tabularnewline
Winsorized Mean ( 1 / 40 ) & 2837000 & 57921.2 & 48.9804 \tabularnewline
Winsorized Mean ( 2 / 40 ) & 2839290 & 57347 & 49.5106 \tabularnewline
Winsorized Mean ( 3 / 40 ) & 2836820 & 56977.4 & 49.7885 \tabularnewline
Winsorized Mean ( 4 / 40 ) & 2837620 & 56809.7 & 49.9495 \tabularnewline
Winsorized Mean ( 5 / 40 ) & 2838180 & 56542 & 50.1959 \tabularnewline
Winsorized Mean ( 6 / 40 ) & 2849980 & 54084.2 & 52.6952 \tabularnewline
Winsorized Mean ( 7 / 40 ) & 2849270 & 54015 & 52.7496 \tabularnewline
Winsorized Mean ( 8 / 40 ) & 2850870 & 53732.2 & 53.057 \tabularnewline
Winsorized Mean ( 9 / 40 ) & 2854660 & 53077.1 & 53.7833 \tabularnewline
Winsorized Mean ( 10 / 40 ) & 2854670 & 52808.1 & 54.0575 \tabularnewline
Winsorized Mean ( 11 / 40 ) & 2858080 & 52237.6 & 54.7131 \tabularnewline
Winsorized Mean ( 12 / 40 ) & 2856760 & 52111.3 & 54.8204 \tabularnewline
Winsorized Mean ( 13 / 40 ) & 2858080 & 51893.5 & 55.0759 \tabularnewline
Winsorized Mean ( 14 / 40 ) & 2862420 & 51185.7 & 55.9222 \tabularnewline
Winsorized Mean ( 15 / 40 ) & 2860920 & 51043.2 & 56.049 \tabularnewline
Winsorized Mean ( 16 / 40 ) & 2864300 & 50499.5 & 56.7194 \tabularnewline
Winsorized Mean ( 17 / 40 ) & 2874880 & 48836.6 & 58.8674 \tabularnewline
Winsorized Mean ( 18 / 40 ) & 2880460 & 47532.1 & 60.6003 \tabularnewline
Winsorized Mean ( 19 / 40 ) & 2890360 & 46062.5 & 62.7487 \tabularnewline
Winsorized Mean ( 20 / 40 ) & 2894590 & 45449.6 & 63.6878 \tabularnewline
Winsorized Mean ( 21 / 40 ) & 2903220 & 44221.4 & 65.652 \tabularnewline
Winsorized Mean ( 22 / 40 ) & 2907870 & 43573.5 & 66.7347 \tabularnewline
Winsorized Mean ( 23 / 40 ) & 2907640 & 43007.1 & 67.6085 \tabularnewline
Winsorized Mean ( 24 / 40 ) & 2912710 & 41751.7 & 69.7628 \tabularnewline
Winsorized Mean ( 25 / 40 ) & 2912710 & 41171.6 & 70.7457 \tabularnewline
Winsorized Mean ( 26 / 40 ) & 2915310 & 39563.5 & 73.6869 \tabularnewline
Winsorized Mean ( 27 / 40 ) & 2915310 & 39563.5 & 73.6869 \tabularnewline
Winsorized Mean ( 28 / 40 ) & 2915590 & 38892.5 & 74.9654 \tabularnewline
Winsorized Mean ( 29 / 40 ) & 2927190 & 36649.7 & 79.8693 \tabularnewline
Winsorized Mean ( 30 / 40 ) & 2936860 & 34749.1 & 84.5162 \tabularnewline
Winsorized Mean ( 31 / 40 ) & 2933460 & 33760.6 & 86.8899 \tabularnewline
Winsorized Mean ( 32 / 40 ) & 2933460 & 33760.6 & 86.8899 \tabularnewline
Winsorized Mean ( 33 / 40 ) & 2930110 & 33460.6 & 87.5691 \tabularnewline
Winsorized Mean ( 34 / 40 ) & 2965260 & 29121.9 & 101.822 \tabularnewline
Winsorized Mean ( 35 / 40 ) & 2965260 & 29121.9 & 101.822 \tabularnewline
Winsorized Mean ( 36 / 40 ) & 2972810 & 28222.1 & 105.336 \tabularnewline
Winsorized Mean ( 37 / 40 ) & 2965050 & 27513.1 & 107.768 \tabularnewline
Winsorized Mean ( 38 / 40 ) & 2969220 & 26216.2 & 113.259 \tabularnewline
Winsorized Mean ( 39 / 40 ) & 2989600 & 23039.4 & 129.76 \tabularnewline
Winsorized Mean ( 40 / 40 ) & 3010050 & 20731.9 & 145.189 \tabularnewline
Trimmed Mean ( 1 / 40 ) & 2843760 & 56920.6 & 49.9602 \tabularnewline
Trimmed Mean ( 2 / 40 ) & 2850760 & 55804.8 & 51.0845 \tabularnewline
Trimmed Mean ( 3 / 40 ) & 2856800 & 54896.3 & 52.0398 \tabularnewline
Trimmed Mean ( 4 / 40 ) & 2863930 & 54026.3 & 53.0099 \tabularnewline
Trimmed Mean ( 5 / 40 ) & 2871110 & 53102.9 & 54.0669 \tabularnewline
Trimmed Mean ( 6 / 40 ) & 2878430 & 52135.5 & 55.2104 \tabularnewline
Trimmed Mean ( 7 / 40 ) & 2883790 & 51626.4 & 55.8589 \tabularnewline
Trimmed Mean ( 8 / 40 ) & 2889480 & 51059.2 & 56.5908 \tabularnewline
Trimmed Mean ( 9 / 40 ) & 2895160 & 50466.9 & 57.3675 \tabularnewline
Trimmed Mean ( 10 / 40 ) & 2900560 & 49907.9 & 58.1182 \tabularnewline
Trimmed Mean ( 11 / 40 ) & 2906180 & 49310.7 & 58.9361 \tabularnewline
Trimmed Mean ( 12 / 40 ) & 2911640 & 48717.1 & 59.7664 \tabularnewline
Trimmed Mean ( 13 / 40 ) & 2917480 & 48050.4 & 60.7172 \tabularnewline
Trimmed Mean ( 14 / 40 ) & 2923440 & 47315.1 & 61.7867 \tabularnewline
Trimmed Mean ( 15 / 40 ) & 2929250 & 46572.9 & 62.8961 \tabularnewline
Trimmed Mean ( 16 / 40 ) & 2935470 & 45730.9 & 64.19 \tabularnewline
Trimmed Mean ( 17 / 40 ) & 2941670 & 44835.1 & 65.6109 \tabularnewline
Trimmed Mean ( 18 / 40 ) & 2947290 & 44038.3 & 66.9255 \tabularnewline
Trimmed Mean ( 19 / 40 ) & 2952720 & 43291.1 & 68.2061 \tabularnewline
Trimmed Mean ( 20 / 40 ) & 2957640 & 42623.4 & 69.39 \tabularnewline
Trimmed Mean ( 21 / 40 ) & 2962490 & 41922.3 & 70.6663 \tabularnewline
Trimmed Mean ( 22 / 40 ) & 2966950 & 41266.6 & 71.8971 \tabularnewline
Trimmed Mean ( 23 / 40 ) & 2971300 & 40578.7 & 73.2233 \tabularnewline
Trimmed Mean ( 24 / 40 ) & 2975920 & 39832.4 & 74.711 \tabularnewline
Trimmed Mean ( 25 / 40 ) & 2980430 & 39115.8 & 76.195 \tabularnewline
Trimmed Mean ( 26 / 40 ) & 2985210 & 38330.9 & 77.8801 \tabularnewline
Trimmed Mean ( 27 / 40 ) & 2990100 & 37607.9 & 79.5073 \tabularnewline
Trimmed Mean ( 28 / 40 ) & 2995290 & 36724.3 & 81.5616 \tabularnewline
Trimmed Mean ( 29 / 40 ) & 3000800 & 35742.2 & 83.9569 \tabularnewline
Trimmed Mean ( 30 / 40 ) & 3005880 & 34904 & 86.1185 \tabularnewline
Trimmed Mean ( 31 / 40 ) & 3010640 & 34175.8 & 88.0927 \tabularnewline
Trimmed Mean ( 32 / 40 ) & 3015970 & 33401.5 & 90.2945 \tabularnewline
Trimmed Mean ( 33 / 40 ) & 3021700 & 32417.6 & 93.2118 \tabularnewline
Trimmed Mean ( 34 / 40 ) & 3028110 & 31200.8 & 97.0522 \tabularnewline
Trimmed Mean ( 35 / 40 ) & 3032550 & 30549.5 & 99.2668 \tabularnewline
Trimmed Mean ( 36 / 40 ) & 3037350 & 29694 & 102.289 \tabularnewline
Trimmed Mean ( 37 / 40 ) & 3042030 & 28772 & 105.729 \tabularnewline
Trimmed Mean ( 38 / 40 ) & 3047700 & 27656.3 & 110.199 \tabularnewline
Trimmed Mean ( 39 / 40 ) & 3053600 & 26464.4 & 115.385 \tabularnewline
Trimmed Mean ( 40 / 40 ) & 3058530 & 25683.2 & 119.087 \tabularnewline
Median & 3129120 &  &  \tabularnewline
Midrange & 2332620 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 2995340 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 3005880 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 2995340 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 3005880 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 3005880 &  &  \tabularnewline
Midmean - Closest Observation & 2995340 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 3005880 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 3000800 &  &  \tabularnewline
Number of observations & 120 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]2835240[/C][C]58512.6[/C][C]48.4552[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]2746570[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]2636900[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]2906210[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 40 )[/C][C]2837000[/C][C]57921.2[/C][C]48.9804[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 40 )[/C][C]2839290[/C][C]57347[/C][C]49.5106[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 40 )[/C][C]2836820[/C][C]56977.4[/C][C]49.7885[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 40 )[/C][C]2837620[/C][C]56809.7[/C][C]49.9495[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 40 )[/C][C]2838180[/C][C]56542[/C][C]50.1959[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 40 )[/C][C]2849980[/C][C]54084.2[/C][C]52.6952[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 40 )[/C][C]2849270[/C][C]54015[/C][C]52.7496[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 40 )[/C][C]2850870[/C][C]53732.2[/C][C]53.057[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 40 )[/C][C]2854660[/C][C]53077.1[/C][C]53.7833[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 40 )[/C][C]2854670[/C][C]52808.1[/C][C]54.0575[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 40 )[/C][C]2858080[/C][C]52237.6[/C][C]54.7131[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 40 )[/C][C]2856760[/C][C]52111.3[/C][C]54.8204[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 40 )[/C][C]2858080[/C][C]51893.5[/C][C]55.0759[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 40 )[/C][C]2862420[/C][C]51185.7[/C][C]55.9222[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 40 )[/C][C]2860920[/C][C]51043.2[/C][C]56.049[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 40 )[/C][C]2864300[/C][C]50499.5[/C][C]56.7194[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 40 )[/C][C]2874880[/C][C]48836.6[/C][C]58.8674[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 40 )[/C][C]2880460[/C][C]47532.1[/C][C]60.6003[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 40 )[/C][C]2890360[/C][C]46062.5[/C][C]62.7487[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 40 )[/C][C]2894590[/C][C]45449.6[/C][C]63.6878[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 40 )[/C][C]2903220[/C][C]44221.4[/C][C]65.652[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 40 )[/C][C]2907870[/C][C]43573.5[/C][C]66.7347[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 40 )[/C][C]2907640[/C][C]43007.1[/C][C]67.6085[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 40 )[/C][C]2912710[/C][C]41751.7[/C][C]69.7628[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 40 )[/C][C]2912710[/C][C]41171.6[/C][C]70.7457[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 40 )[/C][C]2915310[/C][C]39563.5[/C][C]73.6869[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 40 )[/C][C]2915310[/C][C]39563.5[/C][C]73.6869[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 40 )[/C][C]2915590[/C][C]38892.5[/C][C]74.9654[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 40 )[/C][C]2927190[/C][C]36649.7[/C][C]79.8693[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 40 )[/C][C]2936860[/C][C]34749.1[/C][C]84.5162[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 40 )[/C][C]2933460[/C][C]33760.6[/C][C]86.8899[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 40 )[/C][C]2933460[/C][C]33760.6[/C][C]86.8899[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 40 )[/C][C]2930110[/C][C]33460.6[/C][C]87.5691[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 40 )[/C][C]2965260[/C][C]29121.9[/C][C]101.822[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 40 )[/C][C]2965260[/C][C]29121.9[/C][C]101.822[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 40 )[/C][C]2972810[/C][C]28222.1[/C][C]105.336[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 40 )[/C][C]2965050[/C][C]27513.1[/C][C]107.768[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 40 )[/C][C]2969220[/C][C]26216.2[/C][C]113.259[/C][/ROW]
[ROW][C]Winsorized Mean ( 39 / 40 )[/C][C]2989600[/C][C]23039.4[/C][C]129.76[/C][/ROW]
[ROW][C]Winsorized Mean ( 40 / 40 )[/C][C]3010050[/C][C]20731.9[/C][C]145.189[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 40 )[/C][C]2843760[/C][C]56920.6[/C][C]49.9602[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 40 )[/C][C]2850760[/C][C]55804.8[/C][C]51.0845[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 40 )[/C][C]2856800[/C][C]54896.3[/C][C]52.0398[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 40 )[/C][C]2863930[/C][C]54026.3[/C][C]53.0099[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 40 )[/C][C]2871110[/C][C]53102.9[/C][C]54.0669[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 40 )[/C][C]2878430[/C][C]52135.5[/C][C]55.2104[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 40 )[/C][C]2883790[/C][C]51626.4[/C][C]55.8589[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 40 )[/C][C]2889480[/C][C]51059.2[/C][C]56.5908[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 40 )[/C][C]2895160[/C][C]50466.9[/C][C]57.3675[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 40 )[/C][C]2900560[/C][C]49907.9[/C][C]58.1182[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 40 )[/C][C]2906180[/C][C]49310.7[/C][C]58.9361[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 40 )[/C][C]2911640[/C][C]48717.1[/C][C]59.7664[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 40 )[/C][C]2917480[/C][C]48050.4[/C][C]60.7172[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 40 )[/C][C]2923440[/C][C]47315.1[/C][C]61.7867[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 40 )[/C][C]2929250[/C][C]46572.9[/C][C]62.8961[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 40 )[/C][C]2935470[/C][C]45730.9[/C][C]64.19[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 40 )[/C][C]2941670[/C][C]44835.1[/C][C]65.6109[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 40 )[/C][C]2947290[/C][C]44038.3[/C][C]66.9255[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 40 )[/C][C]2952720[/C][C]43291.1[/C][C]68.2061[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 40 )[/C][C]2957640[/C][C]42623.4[/C][C]69.39[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 40 )[/C][C]2962490[/C][C]41922.3[/C][C]70.6663[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 40 )[/C][C]2966950[/C][C]41266.6[/C][C]71.8971[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 40 )[/C][C]2971300[/C][C]40578.7[/C][C]73.2233[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 40 )[/C][C]2975920[/C][C]39832.4[/C][C]74.711[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 40 )[/C][C]2980430[/C][C]39115.8[/C][C]76.195[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 40 )[/C][C]2985210[/C][C]38330.9[/C][C]77.8801[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 40 )[/C][C]2990100[/C][C]37607.9[/C][C]79.5073[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 40 )[/C][C]2995290[/C][C]36724.3[/C][C]81.5616[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 40 )[/C][C]3000800[/C][C]35742.2[/C][C]83.9569[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 40 )[/C][C]3005880[/C][C]34904[/C][C]86.1185[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 40 )[/C][C]3010640[/C][C]34175.8[/C][C]88.0927[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 40 )[/C][C]3015970[/C][C]33401.5[/C][C]90.2945[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 40 )[/C][C]3021700[/C][C]32417.6[/C][C]93.2118[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 40 )[/C][C]3028110[/C][C]31200.8[/C][C]97.0522[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 40 )[/C][C]3032550[/C][C]30549.5[/C][C]99.2668[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 40 )[/C][C]3037350[/C][C]29694[/C][C]102.289[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 40 )[/C][C]3042030[/C][C]28772[/C][C]105.729[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 40 )[/C][C]3047700[/C][C]27656.3[/C][C]110.199[/C][/ROW]
[ROW][C]Trimmed Mean ( 39 / 40 )[/C][C]3053600[/C][C]26464.4[/C][C]115.385[/C][/ROW]
[ROW][C]Trimmed Mean ( 40 / 40 )[/C][C]3058530[/C][C]25683.2[/C][C]119.087[/C][/ROW]
[ROW][C]Median[/C][C]3129120[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]2332620[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]2995340[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]3005880[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]2995340[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]3005880[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]3005880[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]2995340[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]3005880[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]3000800[/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=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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 Mean283524058512.648.4552
Geometric Mean2746570
Harmonic Mean2636900
Quadratic Mean2906210
Winsorized Mean ( 1 / 40 )283700057921.248.9804
Winsorized Mean ( 2 / 40 )28392905734749.5106
Winsorized Mean ( 3 / 40 )283682056977.449.7885
Winsorized Mean ( 4 / 40 )283762056809.749.9495
Winsorized Mean ( 5 / 40 )28381805654250.1959
Winsorized Mean ( 6 / 40 )284998054084.252.6952
Winsorized Mean ( 7 / 40 )28492705401552.7496
Winsorized Mean ( 8 / 40 )285087053732.253.057
Winsorized Mean ( 9 / 40 )285466053077.153.7833
Winsorized Mean ( 10 / 40 )285467052808.154.0575
Winsorized Mean ( 11 / 40 )285808052237.654.7131
Winsorized Mean ( 12 / 40 )285676052111.354.8204
Winsorized Mean ( 13 / 40 )285808051893.555.0759
Winsorized Mean ( 14 / 40 )286242051185.755.9222
Winsorized Mean ( 15 / 40 )286092051043.256.049
Winsorized Mean ( 16 / 40 )286430050499.556.7194
Winsorized Mean ( 17 / 40 )287488048836.658.8674
Winsorized Mean ( 18 / 40 )288046047532.160.6003
Winsorized Mean ( 19 / 40 )289036046062.562.7487
Winsorized Mean ( 20 / 40 )289459045449.663.6878
Winsorized Mean ( 21 / 40 )290322044221.465.652
Winsorized Mean ( 22 / 40 )290787043573.566.7347
Winsorized Mean ( 23 / 40 )290764043007.167.6085
Winsorized Mean ( 24 / 40 )291271041751.769.7628
Winsorized Mean ( 25 / 40 )291271041171.670.7457
Winsorized Mean ( 26 / 40 )291531039563.573.6869
Winsorized Mean ( 27 / 40 )291531039563.573.6869
Winsorized Mean ( 28 / 40 )291559038892.574.9654
Winsorized Mean ( 29 / 40 )292719036649.779.8693
Winsorized Mean ( 30 / 40 )293686034749.184.5162
Winsorized Mean ( 31 / 40 )293346033760.686.8899
Winsorized Mean ( 32 / 40 )293346033760.686.8899
Winsorized Mean ( 33 / 40 )293011033460.687.5691
Winsorized Mean ( 34 / 40 )296526029121.9101.822
Winsorized Mean ( 35 / 40 )296526029121.9101.822
Winsorized Mean ( 36 / 40 )297281028222.1105.336
Winsorized Mean ( 37 / 40 )296505027513.1107.768
Winsorized Mean ( 38 / 40 )296922026216.2113.259
Winsorized Mean ( 39 / 40 )298960023039.4129.76
Winsorized Mean ( 40 / 40 )301005020731.9145.189
Trimmed Mean ( 1 / 40 )284376056920.649.9602
Trimmed Mean ( 2 / 40 )285076055804.851.0845
Trimmed Mean ( 3 / 40 )285680054896.352.0398
Trimmed Mean ( 4 / 40 )286393054026.353.0099
Trimmed Mean ( 5 / 40 )287111053102.954.0669
Trimmed Mean ( 6 / 40 )287843052135.555.2104
Trimmed Mean ( 7 / 40 )288379051626.455.8589
Trimmed Mean ( 8 / 40 )288948051059.256.5908
Trimmed Mean ( 9 / 40 )289516050466.957.3675
Trimmed Mean ( 10 / 40 )290056049907.958.1182
Trimmed Mean ( 11 / 40 )290618049310.758.9361
Trimmed Mean ( 12 / 40 )291164048717.159.7664
Trimmed Mean ( 13 / 40 )291748048050.460.7172
Trimmed Mean ( 14 / 40 )292344047315.161.7867
Trimmed Mean ( 15 / 40 )292925046572.962.8961
Trimmed Mean ( 16 / 40 )293547045730.964.19
Trimmed Mean ( 17 / 40 )294167044835.165.6109
Trimmed Mean ( 18 / 40 )294729044038.366.9255
Trimmed Mean ( 19 / 40 )295272043291.168.2061
Trimmed Mean ( 20 / 40 )295764042623.469.39
Trimmed Mean ( 21 / 40 )296249041922.370.6663
Trimmed Mean ( 22 / 40 )296695041266.671.8971
Trimmed Mean ( 23 / 40 )297130040578.773.2233
Trimmed Mean ( 24 / 40 )297592039832.474.711
Trimmed Mean ( 25 / 40 )298043039115.876.195
Trimmed Mean ( 26 / 40 )298521038330.977.8801
Trimmed Mean ( 27 / 40 )299010037607.979.5073
Trimmed Mean ( 28 / 40 )299529036724.381.5616
Trimmed Mean ( 29 / 40 )300080035742.283.9569
Trimmed Mean ( 30 / 40 )30058803490486.1185
Trimmed Mean ( 31 / 40 )301064034175.888.0927
Trimmed Mean ( 32 / 40 )301597033401.590.2945
Trimmed Mean ( 33 / 40 )302170032417.693.2118
Trimmed Mean ( 34 / 40 )302811031200.897.0522
Trimmed Mean ( 35 / 40 )303255030549.599.2668
Trimmed Mean ( 36 / 40 )303735029694102.289
Trimmed Mean ( 37 / 40 )304203028772105.729
Trimmed Mean ( 38 / 40 )304770027656.3110.199
Trimmed Mean ( 39 / 40 )305360026464.4115.385
Trimmed Mean ( 40 / 40 )305853025683.2119.087
Median3129120
Midrange2332620
Midmean - Weighted Average at Xnp2995340
Midmean - Weighted Average at X(n+1)p3005880
Midmean - Empirical Distribution Function2995340
Midmean - Empirical Distribution Function - Averaging3005880
Midmean - Empirical Distribution Function - Interpolation3005880
Midmean - Closest Observation2995340
Midmean - True Basic - Statistics Graphics Toolkit3005880
Midmean - MS Excel (old versions)3000800
Number of observations120



Parameters (Session):
par1 = 12greygrey0.010.10,010,010,010,10,10,10,010,010,010,010,1 ; par2 = nono0.990.90,990,990,990,990,990,990,990,990,990,990,99 ; par3 = 0.010.10,010,010,010,10,10,10,010,10,10,10,1 ;
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')