Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSat, 22 Jul 2017 01:05:25 +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/Jul/22/t1500678368fxknr1fxy1wfsn1.htm/, Retrieved Tue, 14 May 2024 18:34:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=306730, Retrieved Tue, 14 May 2024 18:34:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact196
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Tijdreeks A stap 14] [2017-07-21 23:05:25] [5e513ceaaef205c0c6f269c0b513af8d] [Current]
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Dataseries X:
6195800
6172725
6149325
6100900
6579950
6554600
6195800
5957250
5980325
5980325
6006000
6052150
6123975
6123975
6077825
5957250
6579950
6674850
6531525
6195800
6339450
6123975
6221150
6267625
6316050
6195800
6221150
6052150
6579950
6746675
6603350
6339450
6626425
6316050
6603350
6579950
6651775
6387875
6674850
6651775
7082400
6985225
6603350
6410950
6674850
6316050
6579950
6626425
6723600
6508450
6626425
6698250
6962150
6746675
6459700
6149325
6436625
5646875
6029075
6244225
6459700
6149325
6149325
6149325
6316050
6077825
5765175
5503550
5693350
4952350
5406375
5670275
5718700
5454800
5477875
5406375
5646875
5477875
5144750
4903925
5311150
4426825
5001100
5262725
5262725
4952350
4665375
4642300
4903925
4665375
4211675
3899025
4234750
3445325
4162925
4544800
4665375
4401475
4068025
4306575
4401475
4329650
3611725
3278600
3516825
2799225
3540225
3804125
4019275
3660475
3324750
3516825
3611725
3421925
2704325
2391675
2678650
1889225
2750475
3278600




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306730&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]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=306730&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306730&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 time1 seconds
R ServerBig Analytics Cloud Computing Center







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean545239011252448.4552
Geometric Mean5281870
Harmonic Mean5070960
Quadratic Mean5588860
Winsorized Mean ( 1 / 40 )545577011138748.9804
Winsorized Mean ( 2 / 40 )546017011028349.5106
Winsorized Mean ( 3 / 40 )545542010957249.7885
Winsorized Mean ( 4 / 40 )545696010924949.9495
Winsorized Mean ( 5 / 40 )545803010873550.1959
Winsorized Mean ( 6 / 40 )548073010400852.6952
Winsorized Mean ( 7 / 40 )547937010387552.7496
Winsorized Mean ( 8 / 40 )548244010333153.057
Winsorized Mean ( 9 / 40 )548973010207153.7833
Winsorized Mean ( 10 / 40 )548976010155454.0575
Winsorized Mean ( 11 / 40 )549631010045754.7131
Winsorized Mean ( 12 / 40 )549378010021454.8204
Winsorized Mean ( 13 / 40 )549631099795.255.0759
Winsorized Mean ( 14 / 40 )550466098434.155.9222
Winsorized Mean ( 15 / 40 )55017709816056.049
Winsorized Mean ( 16 / 40 )550827097114.456.7194
Winsorized Mean ( 17 / 40 )552862093916.558.8674
Winsorized Mean ( 18 / 40 )553935091407.960.6003
Winsorized Mean ( 19 / 40 )555839088581.762.7487
Winsorized Mean ( 20 / 40 )556651087403.263.6878
Winsorized Mean ( 21 / 40 )558312085041.165.652
Winsorized Mean ( 22 / 40 )559206083795.366.7347
Winsorized Mean ( 23 / 40 )559162082705.967.6085
Winsorized Mean ( 24 / 40 )560137080291.769.7628
Winsorized Mean ( 25 / 40 )560137079176.170.7457
Winsorized Mean ( 26 / 40 )560637076083.673.6869
Winsorized Mean ( 27 / 40 )560637076083.673.6869
Winsorized Mean ( 28 / 40 )560690074793.274.9654
Winsorized Mean ( 29 / 40 )562921070480.279.8693
Winsorized Mean ( 30 / 40 )564781066825.284.5162
Winsorized Mean ( 31 / 40 )564126064924.286.8899
Winsorized Mean ( 32 / 40 )564126064924.286.8899
Winsorized Mean ( 33 / 40 )563483064347.287.5691
Winsorized Mean ( 34 / 40 )570242056003.7101.822
Winsorized Mean ( 35 / 40 )570242056003.7101.822
Winsorized Mean ( 36 / 40 )571694054273.3105.336
Winsorized Mean ( 37 / 40 )570201052909.9107.768
Winsorized Mean ( 38 / 40 )571004050415.8113.259
Winsorized Mean ( 39 / 40 )574923044306.5129.76
Winsorized Mean ( 40 / 40 )578855039869145.189
Trimmed Mean ( 1 / 40 )546878010946349.9602
Trimmed Mean ( 2 / 40 )548223010731751.0845
Trimmed Mean ( 3 / 40 )549384010557052.0398
Trimmed Mean ( 4 / 40 )550756010389753.0099
Trimmed Mean ( 5 / 40 )552136010212154.0669
Trimmed Mean ( 6 / 40 )553543010026155.2104
Trimmed Mean ( 7 / 40 )554575099281.555.8589
Trimmed Mean ( 8 / 40 )555670098190.856.5908
Trimmed Mean ( 9 / 40 )556762097051.857.3675
Trimmed Mean ( 10 / 40 )557800095976.858.1182
Trimmed Mean ( 11 / 40 )558881094828.258.9361
Trimmed Mean ( 12 / 40 )559932093686.759.7664
Trimmed Mean ( 13 / 40 )561054092404.560.7172
Trimmed Mean ( 14 / 40 )562201090990.561.7867
Trimmed Mean ( 15 / 40 )563318089563.262.8961
Trimmed Mean ( 16 / 40 )564513087944.164.19
Trimmed Mean ( 17 / 40 )565706086221.365.6109
Trimmed Mean ( 18 / 40 )56678608468966.9255
Trimmed Mean ( 19 / 40 )567830083252.168.2061
Trimmed Mean ( 20 / 40 )568777081968.169.39
Trimmed Mean ( 21 / 40 )569710080619.870.6663
Trimmed Mean ( 22 / 40 )570567079358.871.8971
Trimmed Mean ( 23 / 40 )571404078035.973.2233
Trimmed Mean ( 24 / 40 )572292076600.774.711
Trimmed Mean ( 25 / 40 )573160075222.776.195
Trimmed Mean ( 26 / 40 )574079073713.277.8801
Trimmed Mean ( 27 / 40 )575019072322.879.5073
Trimmed Mean ( 28 / 40 )576018070623.781.5616
Trimmed Mean ( 29 / 40 )57707706873583.9569
Trimmed Mean ( 30 / 40 )578054067123.186.1185
Trimmed Mean ( 31 / 40 )578969065722.788.0927
Trimmed Mean ( 32 / 40 )579995064233.790.2945
Trimmed Mean ( 33 / 40 )581097062341.693.2118
Trimmed Mean ( 34 / 40 )582329060001.697.0522
Trimmed Mean ( 35 / 40 )58318205874999.2668
Trimmed Mean ( 36 / 40 )584106057103.8102.289
Trimmed Mean ( 37 / 40 )585006055330.9105.729
Trimmed Mean ( 38 / 40 )586097053185.2110.199
Trimmed Mean ( 39 / 40 )587232050893.1115.385
Trimmed Mean ( 40 / 40 )588178049390.8119.087
Median6017540
Midrange4485810
Midmean - Weighted Average at Xnp5760280
Midmean - Weighted Average at X(n+1)p5780540
Midmean - Empirical Distribution Function5760280
Midmean - Empirical Distribution Function - Averaging5780540
Midmean - Empirical Distribution Function - Interpolation5780540
Midmean - Closest Observation5760280
Midmean - True Basic - Statistics Graphics Toolkit5780540
Midmean - MS Excel (old versions)5770770
Number of observations120

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 5452390 & 112524 & 48.4552 \tabularnewline
Geometric Mean & 5281870 &  &  \tabularnewline
Harmonic Mean & 5070960 &  &  \tabularnewline
Quadratic Mean & 5588860 &  &  \tabularnewline
Winsorized Mean ( 1 / 40 ) & 5455770 & 111387 & 48.9804 \tabularnewline
Winsorized Mean ( 2 / 40 ) & 5460170 & 110283 & 49.5106 \tabularnewline
Winsorized Mean ( 3 / 40 ) & 5455420 & 109572 & 49.7885 \tabularnewline
Winsorized Mean ( 4 / 40 ) & 5456960 & 109249 & 49.9495 \tabularnewline
Winsorized Mean ( 5 / 40 ) & 5458030 & 108735 & 50.1959 \tabularnewline
Winsorized Mean ( 6 / 40 ) & 5480730 & 104008 & 52.6952 \tabularnewline
Winsorized Mean ( 7 / 40 ) & 5479370 & 103875 & 52.7496 \tabularnewline
Winsorized Mean ( 8 / 40 ) & 5482440 & 103331 & 53.057 \tabularnewline
Winsorized Mean ( 9 / 40 ) & 5489730 & 102071 & 53.7833 \tabularnewline
Winsorized Mean ( 10 / 40 ) & 5489760 & 101554 & 54.0575 \tabularnewline
Winsorized Mean ( 11 / 40 ) & 5496310 & 100457 & 54.7131 \tabularnewline
Winsorized Mean ( 12 / 40 ) & 5493780 & 100214 & 54.8204 \tabularnewline
Winsorized Mean ( 13 / 40 ) & 5496310 & 99795.2 & 55.0759 \tabularnewline
Winsorized Mean ( 14 / 40 ) & 5504660 & 98434.1 & 55.9222 \tabularnewline
Winsorized Mean ( 15 / 40 ) & 5501770 & 98160 & 56.049 \tabularnewline
Winsorized Mean ( 16 / 40 ) & 5508270 & 97114.4 & 56.7194 \tabularnewline
Winsorized Mean ( 17 / 40 ) & 5528620 & 93916.5 & 58.8674 \tabularnewline
Winsorized Mean ( 18 / 40 ) & 5539350 & 91407.9 & 60.6003 \tabularnewline
Winsorized Mean ( 19 / 40 ) & 5558390 & 88581.7 & 62.7487 \tabularnewline
Winsorized Mean ( 20 / 40 ) & 5566510 & 87403.2 & 63.6878 \tabularnewline
Winsorized Mean ( 21 / 40 ) & 5583120 & 85041.1 & 65.652 \tabularnewline
Winsorized Mean ( 22 / 40 ) & 5592060 & 83795.3 & 66.7347 \tabularnewline
Winsorized Mean ( 23 / 40 ) & 5591620 & 82705.9 & 67.6085 \tabularnewline
Winsorized Mean ( 24 / 40 ) & 5601370 & 80291.7 & 69.7628 \tabularnewline
Winsorized Mean ( 25 / 40 ) & 5601370 & 79176.1 & 70.7457 \tabularnewline
Winsorized Mean ( 26 / 40 ) & 5606370 & 76083.6 & 73.6869 \tabularnewline
Winsorized Mean ( 27 / 40 ) & 5606370 & 76083.6 & 73.6869 \tabularnewline
Winsorized Mean ( 28 / 40 ) & 5606900 & 74793.2 & 74.9654 \tabularnewline
Winsorized Mean ( 29 / 40 ) & 5629210 & 70480.2 & 79.8693 \tabularnewline
Winsorized Mean ( 30 / 40 ) & 5647810 & 66825.2 & 84.5162 \tabularnewline
Winsorized Mean ( 31 / 40 ) & 5641260 & 64924.2 & 86.8899 \tabularnewline
Winsorized Mean ( 32 / 40 ) & 5641260 & 64924.2 & 86.8899 \tabularnewline
Winsorized Mean ( 33 / 40 ) & 5634830 & 64347.2 & 87.5691 \tabularnewline
Winsorized Mean ( 34 / 40 ) & 5702420 & 56003.7 & 101.822 \tabularnewline
Winsorized Mean ( 35 / 40 ) & 5702420 & 56003.7 & 101.822 \tabularnewline
Winsorized Mean ( 36 / 40 ) & 5716940 & 54273.3 & 105.336 \tabularnewline
Winsorized Mean ( 37 / 40 ) & 5702010 & 52909.9 & 107.768 \tabularnewline
Winsorized Mean ( 38 / 40 ) & 5710040 & 50415.8 & 113.259 \tabularnewline
Winsorized Mean ( 39 / 40 ) & 5749230 & 44306.5 & 129.76 \tabularnewline
Winsorized Mean ( 40 / 40 ) & 5788550 & 39869 & 145.189 \tabularnewline
Trimmed Mean ( 1 / 40 ) & 5468780 & 109463 & 49.9602 \tabularnewline
Trimmed Mean ( 2 / 40 ) & 5482230 & 107317 & 51.0845 \tabularnewline
Trimmed Mean ( 3 / 40 ) & 5493840 & 105570 & 52.0398 \tabularnewline
Trimmed Mean ( 4 / 40 ) & 5507560 & 103897 & 53.0099 \tabularnewline
Trimmed Mean ( 5 / 40 ) & 5521360 & 102121 & 54.0669 \tabularnewline
Trimmed Mean ( 6 / 40 ) & 5535430 & 100261 & 55.2104 \tabularnewline
Trimmed Mean ( 7 / 40 ) & 5545750 & 99281.5 & 55.8589 \tabularnewline
Trimmed Mean ( 8 / 40 ) & 5556700 & 98190.8 & 56.5908 \tabularnewline
Trimmed Mean ( 9 / 40 ) & 5567620 & 97051.8 & 57.3675 \tabularnewline
Trimmed Mean ( 10 / 40 ) & 5578000 & 95976.8 & 58.1182 \tabularnewline
Trimmed Mean ( 11 / 40 ) & 5588810 & 94828.2 & 58.9361 \tabularnewline
Trimmed Mean ( 12 / 40 ) & 5599320 & 93686.7 & 59.7664 \tabularnewline
Trimmed Mean ( 13 / 40 ) & 5610540 & 92404.5 & 60.7172 \tabularnewline
Trimmed Mean ( 14 / 40 ) & 5622010 & 90990.5 & 61.7867 \tabularnewline
Trimmed Mean ( 15 / 40 ) & 5633180 & 89563.2 & 62.8961 \tabularnewline
Trimmed Mean ( 16 / 40 ) & 5645130 & 87944.1 & 64.19 \tabularnewline
Trimmed Mean ( 17 / 40 ) & 5657060 & 86221.3 & 65.6109 \tabularnewline
Trimmed Mean ( 18 / 40 ) & 5667860 & 84689 & 66.9255 \tabularnewline
Trimmed Mean ( 19 / 40 ) & 5678300 & 83252.1 & 68.2061 \tabularnewline
Trimmed Mean ( 20 / 40 ) & 5687770 & 81968.1 & 69.39 \tabularnewline
Trimmed Mean ( 21 / 40 ) & 5697100 & 80619.8 & 70.6663 \tabularnewline
Trimmed Mean ( 22 / 40 ) & 5705670 & 79358.8 & 71.8971 \tabularnewline
Trimmed Mean ( 23 / 40 ) & 5714040 & 78035.9 & 73.2233 \tabularnewline
Trimmed Mean ( 24 / 40 ) & 5722920 & 76600.7 & 74.711 \tabularnewline
Trimmed Mean ( 25 / 40 ) & 5731600 & 75222.7 & 76.195 \tabularnewline
Trimmed Mean ( 26 / 40 ) & 5740790 & 73713.2 & 77.8801 \tabularnewline
Trimmed Mean ( 27 / 40 ) & 5750190 & 72322.8 & 79.5073 \tabularnewline
Trimmed Mean ( 28 / 40 ) & 5760180 & 70623.7 & 81.5616 \tabularnewline
Trimmed Mean ( 29 / 40 ) & 5770770 & 68735 & 83.9569 \tabularnewline
Trimmed Mean ( 30 / 40 ) & 5780540 & 67123.1 & 86.1185 \tabularnewline
Trimmed Mean ( 31 / 40 ) & 5789690 & 65722.7 & 88.0927 \tabularnewline
Trimmed Mean ( 32 / 40 ) & 5799950 & 64233.7 & 90.2945 \tabularnewline
Trimmed Mean ( 33 / 40 ) & 5810970 & 62341.6 & 93.2118 \tabularnewline
Trimmed Mean ( 34 / 40 ) & 5823290 & 60001.6 & 97.0522 \tabularnewline
Trimmed Mean ( 35 / 40 ) & 5831820 & 58749 & 99.2668 \tabularnewline
Trimmed Mean ( 36 / 40 ) & 5841060 & 57103.8 & 102.289 \tabularnewline
Trimmed Mean ( 37 / 40 ) & 5850060 & 55330.9 & 105.729 \tabularnewline
Trimmed Mean ( 38 / 40 ) & 5860970 & 53185.2 & 110.199 \tabularnewline
Trimmed Mean ( 39 / 40 ) & 5872320 & 50893.1 & 115.385 \tabularnewline
Trimmed Mean ( 40 / 40 ) & 5881780 & 49390.8 & 119.087 \tabularnewline
Median & 6017540 &  &  \tabularnewline
Midrange & 4485810 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 5760280 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 5780540 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 5760280 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 5780540 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 5780540 &  &  \tabularnewline
Midmean - Closest Observation & 5760280 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 5780540 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 5770770 &  &  \tabularnewline
Number of observations & 120 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306730&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]5452390[/C][C]112524[/C][C]48.4552[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]5281870[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]5070960[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]5588860[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 40 )[/C][C]5455770[/C][C]111387[/C][C]48.9804[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 40 )[/C][C]5460170[/C][C]110283[/C][C]49.5106[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 40 )[/C][C]5455420[/C][C]109572[/C][C]49.7885[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 40 )[/C][C]5456960[/C][C]109249[/C][C]49.9495[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 40 )[/C][C]5458030[/C][C]108735[/C][C]50.1959[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 40 )[/C][C]5480730[/C][C]104008[/C][C]52.6952[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 40 )[/C][C]5479370[/C][C]103875[/C][C]52.7496[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 40 )[/C][C]5482440[/C][C]103331[/C][C]53.057[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 40 )[/C][C]5489730[/C][C]102071[/C][C]53.7833[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 40 )[/C][C]5489760[/C][C]101554[/C][C]54.0575[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 40 )[/C][C]5496310[/C][C]100457[/C][C]54.7131[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 40 )[/C][C]5493780[/C][C]100214[/C][C]54.8204[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 40 )[/C][C]5496310[/C][C]99795.2[/C][C]55.0759[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 40 )[/C][C]5504660[/C][C]98434.1[/C][C]55.9222[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 40 )[/C][C]5501770[/C][C]98160[/C][C]56.049[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 40 )[/C][C]5508270[/C][C]97114.4[/C][C]56.7194[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 40 )[/C][C]5528620[/C][C]93916.5[/C][C]58.8674[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 40 )[/C][C]5539350[/C][C]91407.9[/C][C]60.6003[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 40 )[/C][C]5558390[/C][C]88581.7[/C][C]62.7487[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 40 )[/C][C]5566510[/C][C]87403.2[/C][C]63.6878[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 40 )[/C][C]5583120[/C][C]85041.1[/C][C]65.652[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 40 )[/C][C]5592060[/C][C]83795.3[/C][C]66.7347[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 40 )[/C][C]5591620[/C][C]82705.9[/C][C]67.6085[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 40 )[/C][C]5601370[/C][C]80291.7[/C][C]69.7628[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 40 )[/C][C]5601370[/C][C]79176.1[/C][C]70.7457[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 40 )[/C][C]5606370[/C][C]76083.6[/C][C]73.6869[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 40 )[/C][C]5606370[/C][C]76083.6[/C][C]73.6869[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 40 )[/C][C]5606900[/C][C]74793.2[/C][C]74.9654[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 40 )[/C][C]5629210[/C][C]70480.2[/C][C]79.8693[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 40 )[/C][C]5647810[/C][C]66825.2[/C][C]84.5162[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 40 )[/C][C]5641260[/C][C]64924.2[/C][C]86.8899[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 40 )[/C][C]5641260[/C][C]64924.2[/C][C]86.8899[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 40 )[/C][C]5634830[/C][C]64347.2[/C][C]87.5691[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 40 )[/C][C]5702420[/C][C]56003.7[/C][C]101.822[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 40 )[/C][C]5702420[/C][C]56003.7[/C][C]101.822[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 40 )[/C][C]5716940[/C][C]54273.3[/C][C]105.336[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 40 )[/C][C]5702010[/C][C]52909.9[/C][C]107.768[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 40 )[/C][C]5710040[/C][C]50415.8[/C][C]113.259[/C][/ROW]
[ROW][C]Winsorized Mean ( 39 / 40 )[/C][C]5749230[/C][C]44306.5[/C][C]129.76[/C][/ROW]
[ROW][C]Winsorized Mean ( 40 / 40 )[/C][C]5788550[/C][C]39869[/C][C]145.189[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 40 )[/C][C]5468780[/C][C]109463[/C][C]49.9602[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 40 )[/C][C]5482230[/C][C]107317[/C][C]51.0845[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 40 )[/C][C]5493840[/C][C]105570[/C][C]52.0398[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 40 )[/C][C]5507560[/C][C]103897[/C][C]53.0099[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 40 )[/C][C]5521360[/C][C]102121[/C][C]54.0669[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 40 )[/C][C]5535430[/C][C]100261[/C][C]55.2104[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 40 )[/C][C]5545750[/C][C]99281.5[/C][C]55.8589[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 40 )[/C][C]5556700[/C][C]98190.8[/C][C]56.5908[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 40 )[/C][C]5567620[/C][C]97051.8[/C][C]57.3675[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 40 )[/C][C]5578000[/C][C]95976.8[/C][C]58.1182[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 40 )[/C][C]5588810[/C][C]94828.2[/C][C]58.9361[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 40 )[/C][C]5599320[/C][C]93686.7[/C][C]59.7664[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 40 )[/C][C]5610540[/C][C]92404.5[/C][C]60.7172[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 40 )[/C][C]5622010[/C][C]90990.5[/C][C]61.7867[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 40 )[/C][C]5633180[/C][C]89563.2[/C][C]62.8961[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 40 )[/C][C]5645130[/C][C]87944.1[/C][C]64.19[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 40 )[/C][C]5657060[/C][C]86221.3[/C][C]65.6109[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 40 )[/C][C]5667860[/C][C]84689[/C][C]66.9255[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 40 )[/C][C]5678300[/C][C]83252.1[/C][C]68.2061[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 40 )[/C][C]5687770[/C][C]81968.1[/C][C]69.39[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 40 )[/C][C]5697100[/C][C]80619.8[/C][C]70.6663[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 40 )[/C][C]5705670[/C][C]79358.8[/C][C]71.8971[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 40 )[/C][C]5714040[/C][C]78035.9[/C][C]73.2233[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 40 )[/C][C]5722920[/C][C]76600.7[/C][C]74.711[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 40 )[/C][C]5731600[/C][C]75222.7[/C][C]76.195[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 40 )[/C][C]5740790[/C][C]73713.2[/C][C]77.8801[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 40 )[/C][C]5750190[/C][C]72322.8[/C][C]79.5073[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 40 )[/C][C]5760180[/C][C]70623.7[/C][C]81.5616[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 40 )[/C][C]5770770[/C][C]68735[/C][C]83.9569[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 40 )[/C][C]5780540[/C][C]67123.1[/C][C]86.1185[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 40 )[/C][C]5789690[/C][C]65722.7[/C][C]88.0927[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 40 )[/C][C]5799950[/C][C]64233.7[/C][C]90.2945[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 40 )[/C][C]5810970[/C][C]62341.6[/C][C]93.2118[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 40 )[/C][C]5823290[/C][C]60001.6[/C][C]97.0522[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 40 )[/C][C]5831820[/C][C]58749[/C][C]99.2668[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 40 )[/C][C]5841060[/C][C]57103.8[/C][C]102.289[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 40 )[/C][C]5850060[/C][C]55330.9[/C][C]105.729[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 40 )[/C][C]5860970[/C][C]53185.2[/C][C]110.199[/C][/ROW]
[ROW][C]Trimmed Mean ( 39 / 40 )[/C][C]5872320[/C][C]50893.1[/C][C]115.385[/C][/ROW]
[ROW][C]Trimmed Mean ( 40 / 40 )[/C][C]5881780[/C][C]49390.8[/C][C]119.087[/C][/ROW]
[ROW][C]Median[/C][C]6017540[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]4485810[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]5760280[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]5780540[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]5760280[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]5780540[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]5780540[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]5760280[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]5780540[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]5770770[/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=306730&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306730&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 Mean545239011252448.4552
Geometric Mean5281870
Harmonic Mean5070960
Quadratic Mean5588860
Winsorized Mean ( 1 / 40 )545577011138748.9804
Winsorized Mean ( 2 / 40 )546017011028349.5106
Winsorized Mean ( 3 / 40 )545542010957249.7885
Winsorized Mean ( 4 / 40 )545696010924949.9495
Winsorized Mean ( 5 / 40 )545803010873550.1959
Winsorized Mean ( 6 / 40 )548073010400852.6952
Winsorized Mean ( 7 / 40 )547937010387552.7496
Winsorized Mean ( 8 / 40 )548244010333153.057
Winsorized Mean ( 9 / 40 )548973010207153.7833
Winsorized Mean ( 10 / 40 )548976010155454.0575
Winsorized Mean ( 11 / 40 )549631010045754.7131
Winsorized Mean ( 12 / 40 )549378010021454.8204
Winsorized Mean ( 13 / 40 )549631099795.255.0759
Winsorized Mean ( 14 / 40 )550466098434.155.9222
Winsorized Mean ( 15 / 40 )55017709816056.049
Winsorized Mean ( 16 / 40 )550827097114.456.7194
Winsorized Mean ( 17 / 40 )552862093916.558.8674
Winsorized Mean ( 18 / 40 )553935091407.960.6003
Winsorized Mean ( 19 / 40 )555839088581.762.7487
Winsorized Mean ( 20 / 40 )556651087403.263.6878
Winsorized Mean ( 21 / 40 )558312085041.165.652
Winsorized Mean ( 22 / 40 )559206083795.366.7347
Winsorized Mean ( 23 / 40 )559162082705.967.6085
Winsorized Mean ( 24 / 40 )560137080291.769.7628
Winsorized Mean ( 25 / 40 )560137079176.170.7457
Winsorized Mean ( 26 / 40 )560637076083.673.6869
Winsorized Mean ( 27 / 40 )560637076083.673.6869
Winsorized Mean ( 28 / 40 )560690074793.274.9654
Winsorized Mean ( 29 / 40 )562921070480.279.8693
Winsorized Mean ( 30 / 40 )564781066825.284.5162
Winsorized Mean ( 31 / 40 )564126064924.286.8899
Winsorized Mean ( 32 / 40 )564126064924.286.8899
Winsorized Mean ( 33 / 40 )563483064347.287.5691
Winsorized Mean ( 34 / 40 )570242056003.7101.822
Winsorized Mean ( 35 / 40 )570242056003.7101.822
Winsorized Mean ( 36 / 40 )571694054273.3105.336
Winsorized Mean ( 37 / 40 )570201052909.9107.768
Winsorized Mean ( 38 / 40 )571004050415.8113.259
Winsorized Mean ( 39 / 40 )574923044306.5129.76
Winsorized Mean ( 40 / 40 )578855039869145.189
Trimmed Mean ( 1 / 40 )546878010946349.9602
Trimmed Mean ( 2 / 40 )548223010731751.0845
Trimmed Mean ( 3 / 40 )549384010557052.0398
Trimmed Mean ( 4 / 40 )550756010389753.0099
Trimmed Mean ( 5 / 40 )552136010212154.0669
Trimmed Mean ( 6 / 40 )553543010026155.2104
Trimmed Mean ( 7 / 40 )554575099281.555.8589
Trimmed Mean ( 8 / 40 )555670098190.856.5908
Trimmed Mean ( 9 / 40 )556762097051.857.3675
Trimmed Mean ( 10 / 40 )557800095976.858.1182
Trimmed Mean ( 11 / 40 )558881094828.258.9361
Trimmed Mean ( 12 / 40 )559932093686.759.7664
Trimmed Mean ( 13 / 40 )561054092404.560.7172
Trimmed Mean ( 14 / 40 )562201090990.561.7867
Trimmed Mean ( 15 / 40 )563318089563.262.8961
Trimmed Mean ( 16 / 40 )564513087944.164.19
Trimmed Mean ( 17 / 40 )565706086221.365.6109
Trimmed Mean ( 18 / 40 )56678608468966.9255
Trimmed Mean ( 19 / 40 )567830083252.168.2061
Trimmed Mean ( 20 / 40 )568777081968.169.39
Trimmed Mean ( 21 / 40 )569710080619.870.6663
Trimmed Mean ( 22 / 40 )570567079358.871.8971
Trimmed Mean ( 23 / 40 )571404078035.973.2233
Trimmed Mean ( 24 / 40 )572292076600.774.711
Trimmed Mean ( 25 / 40 )573160075222.776.195
Trimmed Mean ( 26 / 40 )574079073713.277.8801
Trimmed Mean ( 27 / 40 )575019072322.879.5073
Trimmed Mean ( 28 / 40 )576018070623.781.5616
Trimmed Mean ( 29 / 40 )57707706873583.9569
Trimmed Mean ( 30 / 40 )578054067123.186.1185
Trimmed Mean ( 31 / 40 )578969065722.788.0927
Trimmed Mean ( 32 / 40 )579995064233.790.2945
Trimmed Mean ( 33 / 40 )581097062341.693.2118
Trimmed Mean ( 34 / 40 )582329060001.697.0522
Trimmed Mean ( 35 / 40 )58318205874999.2668
Trimmed Mean ( 36 / 40 )584106057103.8102.289
Trimmed Mean ( 37 / 40 )585006055330.9105.729
Trimmed Mean ( 38 / 40 )586097053185.2110.199
Trimmed Mean ( 39 / 40 )587232050893.1115.385
Trimmed Mean ( 40 / 40 )588178049390.8119.087
Median6017540
Midrange4485810
Midmean - Weighted Average at Xnp5760280
Midmean - Weighted Average at X(n+1)p5780540
Midmean - Empirical Distribution Function5760280
Midmean - Empirical Distribution Function - Averaging5780540
Midmean - Empirical Distribution Function - Interpolation5780540
Midmean - Closest Observation5760280
Midmean - True Basic - Statistics Graphics Toolkit5780540
Midmean - MS Excel (old versions)5770770
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')