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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, 13 Aug 2017 12:18:13 +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/13/t1502619537duu1skx7bdgu8m4.htm/, Retrieved Fri, 10 May 2024 10:07:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307159, Retrieved Fri, 10 May 2024 10:07:13 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact98
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
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Dataseries X:
4213144
4197453
4181541
4148612
4474366
4457128
4213144
4050930
4066621
4066621
4084080
4115462
4164303
4164303
4132921
4050930
4474366
4538898
4441437
4213144
4310826
4164303
4230382
4261985
4294914
4213144
4230382
4115462
4474366
4587739
4490278
4310826
4505969
4294914
4490278
4474366
4523207
4343755
4538898
4523207
4816032
4749953
4490278
4359446
4538898
4294914
4474366
4505969
4572048
4425746
4505969
4554810
4734262
4587739
4392596
4181541
4376905
3839875
4099771
4246073
4392596
4181541
4181541
4181541
4294914
4132921
3920319
3742414
3871478
3367598
3676335
3855787
3888716
3709264
3724955
3676335
3839875
3724955
3498430
3334669
3611582
3010241
3400748
3578653
3578653
3367598
3172455
3156764
3334669
3172455
2863939
2651337
2879630
2342821
2830789
3090464
3172455
2993003
2766257
2928471
2993003
2944162
2455973
2229448
2391441
1903473
2407353
2586805
2733107
2489123
2260830
2391441
2455973
2326909
1838941
1626339
1821482
1284673
1870323
2229448




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=307159&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=307159&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307159&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 Mean370763076516.548.4552
Geometric Mean3591670
Harmonic Mean3448260
Quadratic Mean3800420
Winsorized Mean ( 1 / 40 )370992075743.148.9804
Winsorized Mean ( 2 / 40 )371291074992.349.5106
Winsorized Mean ( 3 / 40 )370969074508.949.7885
Winsorized Mean ( 4 / 40 )371073074289.749.9495
Winsorized Mean ( 5 / 40 )371146073939.650.1959
Winsorized Mean ( 6 / 40 )372690070725.552.6952
Winsorized Mean ( 7 / 40 )37259707063552.7496
Winsorized Mean ( 8 / 40 )372806070265.253.057
Winsorized Mean ( 9 / 40 )373302069408.553.7833
Winsorized Mean ( 10 / 40 )373304069056.854.0575
Winsorized Mean ( 11 / 40 )373749068310.754.7131
Winsorized Mean ( 12 / 40 )373577068145.654.8204
Winsorized Mean ( 13 / 40 )373749067860.755.0759
Winsorized Mean ( 14 / 40 )374317066935.255.9222
Winsorized Mean ( 15 / 40 )374120066748.856.049
Winsorized Mean ( 16 / 40 )374562066037.856.7194
Winsorized Mean ( 17 / 40 )375946063863.258.8674
Winsorized Mean ( 18 / 40 )376676062157.460.6003
Winsorized Mean ( 19 / 40 )377970060235.562.7487
Winsorized Mean ( 20 / 40 )378523059434.163.6878
Winsorized Mean ( 21 / 40 )379652057827.965.652
Winsorized Mean ( 22 / 40 )380260056980.866.7347
Winsorized Mean ( 23 / 40 )38023005624067.6085
Winsorized Mean ( 24 / 40 )380893054598.369.7628
Winsorized Mean ( 25 / 40 )380893053839.770.7457
Winsorized Mean ( 26 / 40 )381233051736.973.6869
Winsorized Mean ( 27 / 40 )381233051736.973.6869
Winsorized Mean ( 28 / 40 )381269050859.474.9654
Winsorized Mean ( 29 / 40 )382786047926.579.8693
Winsorized Mean ( 30 / 40 )384051045441.184.5162
Winsorized Mean ( 31 / 40 )383606044148.586.8899
Winsorized Mean ( 32 / 40 )383606044148.586.8899
Winsorized Mean ( 33 / 40 )383168043756.187.5691
Winsorized Mean ( 34 / 40 )387764038082.5101.822
Winsorized Mean ( 35 / 40 )387764038082.5101.822
Winsorized Mean ( 36 / 40 )388752036905.9105.336
Winsorized Mean ( 37 / 40 )387737035978.7107.768
Winsorized Mean ( 38 / 40 )388283034282.7113.259
Winsorized Mean ( 39 / 40 )390948030128.4129.76
Winsorized Mean ( 40 / 40 )393622027111145.189
Trimmed Mean ( 1 / 40 )371877074434.649.9602
Trimmed Mean ( 2 / 40 )372792072975.451.0845
Trimmed Mean ( 3 / 40 )373581071787.552.0398
Trimmed Mean ( 4 / 40 )374514070649.853.0099
Trimmed Mean ( 5 / 40 )375452069442.254.0669
Trimmed Mean ( 6 / 40 )376409068177.255.2104
Trimmed Mean ( 7 / 40 )377111067511.455.8589
Trimmed Mean ( 8 / 40 )377855066769.856.5908
Trimmed Mean ( 9 / 40 )378598065995.257.3675
Trimmed Mean ( 10 / 40 )379304065264.258.1182
Trimmed Mean ( 11 / 40 )380039064483.258.9361
Trimmed Mean ( 12 / 40 )380754063706.959.7664
Trimmed Mean ( 13 / 40 )381517062835.160.7172
Trimmed Mean ( 14 / 40 )382296061873.661.7867
Trimmed Mean ( 15 / 40 )38305606090362.8961
Trimmed Mean ( 16 / 40 )38386905980264.19
Trimmed Mean ( 17 / 40 )384680058630.565.6109
Trimmed Mean ( 18 / 40 )385414057588.566.9255
Trimmed Mean ( 19 / 40 )386125056611.568.2061
Trimmed Mean ( 20 / 40 )386769055738.369.39
Trimmed Mean ( 21 / 40 )387403054821.570.6663
Trimmed Mean ( 22 / 40 )38798605396471.8971
Trimmed Mean ( 23 / 40 )388555053064.473.2233
Trimmed Mean ( 24 / 40 )389158052088.574.711
Trimmed Mean ( 25 / 40 )389749051151.576.195
Trimmed Mean ( 26 / 40 )39037405012577.8801
Trimmed Mean ( 27 / 40 )391013049179.579.5073
Trimmed Mean ( 28 / 40 )391692048024.181.5616
Trimmed Mean ( 29 / 40 )392413046739.883.9569
Trimmed Mean ( 30 / 40 )393076045643.786.1185
Trimmed Mean ( 31 / 40 )393699044691.488.0927
Trimmed Mean ( 32 / 40 )394397043678.990.2945
Trimmed Mean ( 33 / 40 )395146042392.393.2118
Trimmed Mean ( 34 / 40 )395984040801.197.0522
Trimmed Mean ( 35 / 40 )396564039949.399.2668
Trimmed Mean ( 36 / 40 )397192038830.6102.289
Trimmed Mean ( 37 / 40 )397804037625105.729
Trimmed Mean ( 38 / 40 )398546036165.9110.199
Trimmed Mean ( 39 / 40 )399318034607.3115.385
Trimmed Mean ( 40 / 40 )399961033585.7119.087
Median4091930
Midrange3050350
Midmean - Weighted Average at Xnp3916990
Midmean - Weighted Average at X(n+1)p3930760
Midmean - Empirical Distribution Function3916990
Midmean - Empirical Distribution Function - Averaging3930760
Midmean - Empirical Distribution Function - Interpolation3930760
Midmean - Closest Observation3916990
Midmean - True Basic - Statistics Graphics Toolkit3930760
Midmean - MS Excel (old versions)3924130
Number of observations120

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 3707630 & 76516.5 & 48.4552 \tabularnewline
Geometric Mean & 3591670 &  &  \tabularnewline
Harmonic Mean & 3448260 &  &  \tabularnewline
Quadratic Mean & 3800420 &  &  \tabularnewline
Winsorized Mean ( 1 / 40 ) & 3709920 & 75743.1 & 48.9804 \tabularnewline
Winsorized Mean ( 2 / 40 ) & 3712910 & 74992.3 & 49.5106 \tabularnewline
Winsorized Mean ( 3 / 40 ) & 3709690 & 74508.9 & 49.7885 \tabularnewline
Winsorized Mean ( 4 / 40 ) & 3710730 & 74289.7 & 49.9495 \tabularnewline
Winsorized Mean ( 5 / 40 ) & 3711460 & 73939.6 & 50.1959 \tabularnewline
Winsorized Mean ( 6 / 40 ) & 3726900 & 70725.5 & 52.6952 \tabularnewline
Winsorized Mean ( 7 / 40 ) & 3725970 & 70635 & 52.7496 \tabularnewline
Winsorized Mean ( 8 / 40 ) & 3728060 & 70265.2 & 53.057 \tabularnewline
Winsorized Mean ( 9 / 40 ) & 3733020 & 69408.5 & 53.7833 \tabularnewline
Winsorized Mean ( 10 / 40 ) & 3733040 & 69056.8 & 54.0575 \tabularnewline
Winsorized Mean ( 11 / 40 ) & 3737490 & 68310.7 & 54.7131 \tabularnewline
Winsorized Mean ( 12 / 40 ) & 3735770 & 68145.6 & 54.8204 \tabularnewline
Winsorized Mean ( 13 / 40 ) & 3737490 & 67860.7 & 55.0759 \tabularnewline
Winsorized Mean ( 14 / 40 ) & 3743170 & 66935.2 & 55.9222 \tabularnewline
Winsorized Mean ( 15 / 40 ) & 3741200 & 66748.8 & 56.049 \tabularnewline
Winsorized Mean ( 16 / 40 ) & 3745620 & 66037.8 & 56.7194 \tabularnewline
Winsorized Mean ( 17 / 40 ) & 3759460 & 63863.2 & 58.8674 \tabularnewline
Winsorized Mean ( 18 / 40 ) & 3766760 & 62157.4 & 60.6003 \tabularnewline
Winsorized Mean ( 19 / 40 ) & 3779700 & 60235.5 & 62.7487 \tabularnewline
Winsorized Mean ( 20 / 40 ) & 3785230 & 59434.1 & 63.6878 \tabularnewline
Winsorized Mean ( 21 / 40 ) & 3796520 & 57827.9 & 65.652 \tabularnewline
Winsorized Mean ( 22 / 40 ) & 3802600 & 56980.8 & 66.7347 \tabularnewline
Winsorized Mean ( 23 / 40 ) & 3802300 & 56240 & 67.6085 \tabularnewline
Winsorized Mean ( 24 / 40 ) & 3808930 & 54598.3 & 69.7628 \tabularnewline
Winsorized Mean ( 25 / 40 ) & 3808930 & 53839.7 & 70.7457 \tabularnewline
Winsorized Mean ( 26 / 40 ) & 3812330 & 51736.9 & 73.6869 \tabularnewline
Winsorized Mean ( 27 / 40 ) & 3812330 & 51736.9 & 73.6869 \tabularnewline
Winsorized Mean ( 28 / 40 ) & 3812690 & 50859.4 & 74.9654 \tabularnewline
Winsorized Mean ( 29 / 40 ) & 3827860 & 47926.5 & 79.8693 \tabularnewline
Winsorized Mean ( 30 / 40 ) & 3840510 & 45441.1 & 84.5162 \tabularnewline
Winsorized Mean ( 31 / 40 ) & 3836060 & 44148.5 & 86.8899 \tabularnewline
Winsorized Mean ( 32 / 40 ) & 3836060 & 44148.5 & 86.8899 \tabularnewline
Winsorized Mean ( 33 / 40 ) & 3831680 & 43756.1 & 87.5691 \tabularnewline
Winsorized Mean ( 34 / 40 ) & 3877640 & 38082.5 & 101.822 \tabularnewline
Winsorized Mean ( 35 / 40 ) & 3877640 & 38082.5 & 101.822 \tabularnewline
Winsorized Mean ( 36 / 40 ) & 3887520 & 36905.9 & 105.336 \tabularnewline
Winsorized Mean ( 37 / 40 ) & 3877370 & 35978.7 & 107.768 \tabularnewline
Winsorized Mean ( 38 / 40 ) & 3882830 & 34282.7 & 113.259 \tabularnewline
Winsorized Mean ( 39 / 40 ) & 3909480 & 30128.4 & 129.76 \tabularnewline
Winsorized Mean ( 40 / 40 ) & 3936220 & 27111 & 145.189 \tabularnewline
Trimmed Mean ( 1 / 40 ) & 3718770 & 74434.6 & 49.9602 \tabularnewline
Trimmed Mean ( 2 / 40 ) & 3727920 & 72975.4 & 51.0845 \tabularnewline
Trimmed Mean ( 3 / 40 ) & 3735810 & 71787.5 & 52.0398 \tabularnewline
Trimmed Mean ( 4 / 40 ) & 3745140 & 70649.8 & 53.0099 \tabularnewline
Trimmed Mean ( 5 / 40 ) & 3754520 & 69442.2 & 54.0669 \tabularnewline
Trimmed Mean ( 6 / 40 ) & 3764090 & 68177.2 & 55.2104 \tabularnewline
Trimmed Mean ( 7 / 40 ) & 3771110 & 67511.4 & 55.8589 \tabularnewline
Trimmed Mean ( 8 / 40 ) & 3778550 & 66769.8 & 56.5908 \tabularnewline
Trimmed Mean ( 9 / 40 ) & 3785980 & 65995.2 & 57.3675 \tabularnewline
Trimmed Mean ( 10 / 40 ) & 3793040 & 65264.2 & 58.1182 \tabularnewline
Trimmed Mean ( 11 / 40 ) & 3800390 & 64483.2 & 58.9361 \tabularnewline
Trimmed Mean ( 12 / 40 ) & 3807540 & 63706.9 & 59.7664 \tabularnewline
Trimmed Mean ( 13 / 40 ) & 3815170 & 62835.1 & 60.7172 \tabularnewline
Trimmed Mean ( 14 / 40 ) & 3822960 & 61873.6 & 61.7867 \tabularnewline
Trimmed Mean ( 15 / 40 ) & 3830560 & 60903 & 62.8961 \tabularnewline
Trimmed Mean ( 16 / 40 ) & 3838690 & 59802 & 64.19 \tabularnewline
Trimmed Mean ( 17 / 40 ) & 3846800 & 58630.5 & 65.6109 \tabularnewline
Trimmed Mean ( 18 / 40 ) & 3854140 & 57588.5 & 66.9255 \tabularnewline
Trimmed Mean ( 19 / 40 ) & 3861250 & 56611.5 & 68.2061 \tabularnewline
Trimmed Mean ( 20 / 40 ) & 3867690 & 55738.3 & 69.39 \tabularnewline
Trimmed Mean ( 21 / 40 ) & 3874030 & 54821.5 & 70.6663 \tabularnewline
Trimmed Mean ( 22 / 40 ) & 3879860 & 53964 & 71.8971 \tabularnewline
Trimmed Mean ( 23 / 40 ) & 3885550 & 53064.4 & 73.2233 \tabularnewline
Trimmed Mean ( 24 / 40 ) & 3891580 & 52088.5 & 74.711 \tabularnewline
Trimmed Mean ( 25 / 40 ) & 3897490 & 51151.5 & 76.195 \tabularnewline
Trimmed Mean ( 26 / 40 ) & 3903740 & 50125 & 77.8801 \tabularnewline
Trimmed Mean ( 27 / 40 ) & 3910130 & 49179.5 & 79.5073 \tabularnewline
Trimmed Mean ( 28 / 40 ) & 3916920 & 48024.1 & 81.5616 \tabularnewline
Trimmed Mean ( 29 / 40 ) & 3924130 & 46739.8 & 83.9569 \tabularnewline
Trimmed Mean ( 30 / 40 ) & 3930760 & 45643.7 & 86.1185 \tabularnewline
Trimmed Mean ( 31 / 40 ) & 3936990 & 44691.4 & 88.0927 \tabularnewline
Trimmed Mean ( 32 / 40 ) & 3943970 & 43678.9 & 90.2945 \tabularnewline
Trimmed Mean ( 33 / 40 ) & 3951460 & 42392.3 & 93.2118 \tabularnewline
Trimmed Mean ( 34 / 40 ) & 3959840 & 40801.1 & 97.0522 \tabularnewline
Trimmed Mean ( 35 / 40 ) & 3965640 & 39949.3 & 99.2668 \tabularnewline
Trimmed Mean ( 36 / 40 ) & 3971920 & 38830.6 & 102.289 \tabularnewline
Trimmed Mean ( 37 / 40 ) & 3978040 & 37625 & 105.729 \tabularnewline
Trimmed Mean ( 38 / 40 ) & 3985460 & 36165.9 & 110.199 \tabularnewline
Trimmed Mean ( 39 / 40 ) & 3993180 & 34607.3 & 115.385 \tabularnewline
Trimmed Mean ( 40 / 40 ) & 3999610 & 33585.7 & 119.087 \tabularnewline
Median & 4091930 &  &  \tabularnewline
Midrange & 3050350 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 3916990 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 3930760 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 3916990 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 3930760 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 3930760 &  &  \tabularnewline
Midmean - Closest Observation & 3916990 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 3930760 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 3924130 &  &  \tabularnewline
Number of observations & 120 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307159&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]3707630[/C][C]76516.5[/C][C]48.4552[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]3591670[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]3448260[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]3800420[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 40 )[/C][C]3709920[/C][C]75743.1[/C][C]48.9804[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 40 )[/C][C]3712910[/C][C]74992.3[/C][C]49.5106[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 40 )[/C][C]3709690[/C][C]74508.9[/C][C]49.7885[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 40 )[/C][C]3710730[/C][C]74289.7[/C][C]49.9495[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 40 )[/C][C]3711460[/C][C]73939.6[/C][C]50.1959[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 40 )[/C][C]3726900[/C][C]70725.5[/C][C]52.6952[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 40 )[/C][C]3725970[/C][C]70635[/C][C]52.7496[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 40 )[/C][C]3728060[/C][C]70265.2[/C][C]53.057[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 40 )[/C][C]3733020[/C][C]69408.5[/C][C]53.7833[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 40 )[/C][C]3733040[/C][C]69056.8[/C][C]54.0575[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 40 )[/C][C]3737490[/C][C]68310.7[/C][C]54.7131[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 40 )[/C][C]3735770[/C][C]68145.6[/C][C]54.8204[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 40 )[/C][C]3737490[/C][C]67860.7[/C][C]55.0759[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 40 )[/C][C]3743170[/C][C]66935.2[/C][C]55.9222[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 40 )[/C][C]3741200[/C][C]66748.8[/C][C]56.049[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 40 )[/C][C]3745620[/C][C]66037.8[/C][C]56.7194[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 40 )[/C][C]3759460[/C][C]63863.2[/C][C]58.8674[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 40 )[/C][C]3766760[/C][C]62157.4[/C][C]60.6003[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 40 )[/C][C]3779700[/C][C]60235.5[/C][C]62.7487[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 40 )[/C][C]3785230[/C][C]59434.1[/C][C]63.6878[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 40 )[/C][C]3796520[/C][C]57827.9[/C][C]65.652[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 40 )[/C][C]3802600[/C][C]56980.8[/C][C]66.7347[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 40 )[/C][C]3802300[/C][C]56240[/C][C]67.6085[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 40 )[/C][C]3808930[/C][C]54598.3[/C][C]69.7628[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 40 )[/C][C]3808930[/C][C]53839.7[/C][C]70.7457[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 40 )[/C][C]3812330[/C][C]51736.9[/C][C]73.6869[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 40 )[/C][C]3812330[/C][C]51736.9[/C][C]73.6869[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 40 )[/C][C]3812690[/C][C]50859.4[/C][C]74.9654[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 40 )[/C][C]3827860[/C][C]47926.5[/C][C]79.8693[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 40 )[/C][C]3840510[/C][C]45441.1[/C][C]84.5162[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 40 )[/C][C]3836060[/C][C]44148.5[/C][C]86.8899[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 40 )[/C][C]3836060[/C][C]44148.5[/C][C]86.8899[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 40 )[/C][C]3831680[/C][C]43756.1[/C][C]87.5691[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 40 )[/C][C]3877640[/C][C]38082.5[/C][C]101.822[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 40 )[/C][C]3877640[/C][C]38082.5[/C][C]101.822[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 40 )[/C][C]3887520[/C][C]36905.9[/C][C]105.336[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 40 )[/C][C]3877370[/C][C]35978.7[/C][C]107.768[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 40 )[/C][C]3882830[/C][C]34282.7[/C][C]113.259[/C][/ROW]
[ROW][C]Winsorized Mean ( 39 / 40 )[/C][C]3909480[/C][C]30128.4[/C][C]129.76[/C][/ROW]
[ROW][C]Winsorized Mean ( 40 / 40 )[/C][C]3936220[/C][C]27111[/C][C]145.189[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 40 )[/C][C]3718770[/C][C]74434.6[/C][C]49.9602[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 40 )[/C][C]3727920[/C][C]72975.4[/C][C]51.0845[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 40 )[/C][C]3735810[/C][C]71787.5[/C][C]52.0398[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 40 )[/C][C]3745140[/C][C]70649.8[/C][C]53.0099[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 40 )[/C][C]3754520[/C][C]69442.2[/C][C]54.0669[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 40 )[/C][C]3764090[/C][C]68177.2[/C][C]55.2104[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 40 )[/C][C]3771110[/C][C]67511.4[/C][C]55.8589[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 40 )[/C][C]3778550[/C][C]66769.8[/C][C]56.5908[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 40 )[/C][C]3785980[/C][C]65995.2[/C][C]57.3675[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 40 )[/C][C]3793040[/C][C]65264.2[/C][C]58.1182[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 40 )[/C][C]3800390[/C][C]64483.2[/C][C]58.9361[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 40 )[/C][C]3807540[/C][C]63706.9[/C][C]59.7664[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 40 )[/C][C]3815170[/C][C]62835.1[/C][C]60.7172[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 40 )[/C][C]3822960[/C][C]61873.6[/C][C]61.7867[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 40 )[/C][C]3830560[/C][C]60903[/C][C]62.8961[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 40 )[/C][C]3838690[/C][C]59802[/C][C]64.19[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 40 )[/C][C]3846800[/C][C]58630.5[/C][C]65.6109[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 40 )[/C][C]3854140[/C][C]57588.5[/C][C]66.9255[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 40 )[/C][C]3861250[/C][C]56611.5[/C][C]68.2061[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 40 )[/C][C]3867690[/C][C]55738.3[/C][C]69.39[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 40 )[/C][C]3874030[/C][C]54821.5[/C][C]70.6663[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 40 )[/C][C]3879860[/C][C]53964[/C][C]71.8971[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 40 )[/C][C]3885550[/C][C]53064.4[/C][C]73.2233[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 40 )[/C][C]3891580[/C][C]52088.5[/C][C]74.711[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 40 )[/C][C]3897490[/C][C]51151.5[/C][C]76.195[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 40 )[/C][C]3903740[/C][C]50125[/C][C]77.8801[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 40 )[/C][C]3910130[/C][C]49179.5[/C][C]79.5073[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 40 )[/C][C]3916920[/C][C]48024.1[/C][C]81.5616[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 40 )[/C][C]3924130[/C][C]46739.8[/C][C]83.9569[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 40 )[/C][C]3930760[/C][C]45643.7[/C][C]86.1185[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 40 )[/C][C]3936990[/C][C]44691.4[/C][C]88.0927[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 40 )[/C][C]3943970[/C][C]43678.9[/C][C]90.2945[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 40 )[/C][C]3951460[/C][C]42392.3[/C][C]93.2118[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 40 )[/C][C]3959840[/C][C]40801.1[/C][C]97.0522[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 40 )[/C][C]3965640[/C][C]39949.3[/C][C]99.2668[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 40 )[/C][C]3971920[/C][C]38830.6[/C][C]102.289[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 40 )[/C][C]3978040[/C][C]37625[/C][C]105.729[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 40 )[/C][C]3985460[/C][C]36165.9[/C][C]110.199[/C][/ROW]
[ROW][C]Trimmed Mean ( 39 / 40 )[/C][C]3993180[/C][C]34607.3[/C][C]115.385[/C][/ROW]
[ROW][C]Trimmed Mean ( 40 / 40 )[/C][C]3999610[/C][C]33585.7[/C][C]119.087[/C][/ROW]
[ROW][C]Median[/C][C]4091930[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]3050350[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]3916990[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]3930760[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]3916990[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]3930760[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]3930760[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]3916990[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]3930760[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]3924130[/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=307159&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307159&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 Mean370763076516.548.4552
Geometric Mean3591670
Harmonic Mean3448260
Quadratic Mean3800420
Winsorized Mean ( 1 / 40 )370992075743.148.9804
Winsorized Mean ( 2 / 40 )371291074992.349.5106
Winsorized Mean ( 3 / 40 )370969074508.949.7885
Winsorized Mean ( 4 / 40 )371073074289.749.9495
Winsorized Mean ( 5 / 40 )371146073939.650.1959
Winsorized Mean ( 6 / 40 )372690070725.552.6952
Winsorized Mean ( 7 / 40 )37259707063552.7496
Winsorized Mean ( 8 / 40 )372806070265.253.057
Winsorized Mean ( 9 / 40 )373302069408.553.7833
Winsorized Mean ( 10 / 40 )373304069056.854.0575
Winsorized Mean ( 11 / 40 )373749068310.754.7131
Winsorized Mean ( 12 / 40 )373577068145.654.8204
Winsorized Mean ( 13 / 40 )373749067860.755.0759
Winsorized Mean ( 14 / 40 )374317066935.255.9222
Winsorized Mean ( 15 / 40 )374120066748.856.049
Winsorized Mean ( 16 / 40 )374562066037.856.7194
Winsorized Mean ( 17 / 40 )375946063863.258.8674
Winsorized Mean ( 18 / 40 )376676062157.460.6003
Winsorized Mean ( 19 / 40 )377970060235.562.7487
Winsorized Mean ( 20 / 40 )378523059434.163.6878
Winsorized Mean ( 21 / 40 )379652057827.965.652
Winsorized Mean ( 22 / 40 )380260056980.866.7347
Winsorized Mean ( 23 / 40 )38023005624067.6085
Winsorized Mean ( 24 / 40 )380893054598.369.7628
Winsorized Mean ( 25 / 40 )380893053839.770.7457
Winsorized Mean ( 26 / 40 )381233051736.973.6869
Winsorized Mean ( 27 / 40 )381233051736.973.6869
Winsorized Mean ( 28 / 40 )381269050859.474.9654
Winsorized Mean ( 29 / 40 )382786047926.579.8693
Winsorized Mean ( 30 / 40 )384051045441.184.5162
Winsorized Mean ( 31 / 40 )383606044148.586.8899
Winsorized Mean ( 32 / 40 )383606044148.586.8899
Winsorized Mean ( 33 / 40 )383168043756.187.5691
Winsorized Mean ( 34 / 40 )387764038082.5101.822
Winsorized Mean ( 35 / 40 )387764038082.5101.822
Winsorized Mean ( 36 / 40 )388752036905.9105.336
Winsorized Mean ( 37 / 40 )387737035978.7107.768
Winsorized Mean ( 38 / 40 )388283034282.7113.259
Winsorized Mean ( 39 / 40 )390948030128.4129.76
Winsorized Mean ( 40 / 40 )393622027111145.189
Trimmed Mean ( 1 / 40 )371877074434.649.9602
Trimmed Mean ( 2 / 40 )372792072975.451.0845
Trimmed Mean ( 3 / 40 )373581071787.552.0398
Trimmed Mean ( 4 / 40 )374514070649.853.0099
Trimmed Mean ( 5 / 40 )375452069442.254.0669
Trimmed Mean ( 6 / 40 )376409068177.255.2104
Trimmed Mean ( 7 / 40 )377111067511.455.8589
Trimmed Mean ( 8 / 40 )377855066769.856.5908
Trimmed Mean ( 9 / 40 )378598065995.257.3675
Trimmed Mean ( 10 / 40 )379304065264.258.1182
Trimmed Mean ( 11 / 40 )380039064483.258.9361
Trimmed Mean ( 12 / 40 )380754063706.959.7664
Trimmed Mean ( 13 / 40 )381517062835.160.7172
Trimmed Mean ( 14 / 40 )382296061873.661.7867
Trimmed Mean ( 15 / 40 )38305606090362.8961
Trimmed Mean ( 16 / 40 )38386905980264.19
Trimmed Mean ( 17 / 40 )384680058630.565.6109
Trimmed Mean ( 18 / 40 )385414057588.566.9255
Trimmed Mean ( 19 / 40 )386125056611.568.2061
Trimmed Mean ( 20 / 40 )386769055738.369.39
Trimmed Mean ( 21 / 40 )387403054821.570.6663
Trimmed Mean ( 22 / 40 )38798605396471.8971
Trimmed Mean ( 23 / 40 )388555053064.473.2233
Trimmed Mean ( 24 / 40 )389158052088.574.711
Trimmed Mean ( 25 / 40 )389749051151.576.195
Trimmed Mean ( 26 / 40 )39037405012577.8801
Trimmed Mean ( 27 / 40 )391013049179.579.5073
Trimmed Mean ( 28 / 40 )391692048024.181.5616
Trimmed Mean ( 29 / 40 )392413046739.883.9569
Trimmed Mean ( 30 / 40 )393076045643.786.1185
Trimmed Mean ( 31 / 40 )393699044691.488.0927
Trimmed Mean ( 32 / 40 )394397043678.990.2945
Trimmed Mean ( 33 / 40 )395146042392.393.2118
Trimmed Mean ( 34 / 40 )395984040801.197.0522
Trimmed Mean ( 35 / 40 )396564039949.399.2668
Trimmed Mean ( 36 / 40 )397192038830.6102.289
Trimmed Mean ( 37 / 40 )397804037625105.729
Trimmed Mean ( 38 / 40 )398546036165.9110.199
Trimmed Mean ( 39 / 40 )399318034607.3115.385
Trimmed Mean ( 40 / 40 )399961033585.7119.087
Median4091930
Midrange3050350
Midmean - Weighted Average at Xnp3916990
Midmean - Weighted Average at X(n+1)p3930760
Midmean - Empirical Distribution Function3916990
Midmean - Empirical Distribution Function - Averaging3930760
Midmean - Empirical Distribution Function - Interpolation3930760
Midmean - Closest Observation3916990
Midmean - True Basic - Statistics Graphics Toolkit3930760
Midmean - MS Excel (old versions)3924130
Number of observations120



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,'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')