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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 computationSat, 29 Jul 2017 18:19:26 +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/29/t150134521634e4q7plejyeywu.htm/, Retrieved Tue, 14 May 2024 14:09:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=306795, Retrieved Tue, 14 May 2024 14:09:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2017-07-29 16:19:26] [bb1ebaef39f3ee233240b5c77a617fca] [Current]
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Dataseries X:
6195800.00
6172725.00
6149325.00
6100900.00
6579950.00
6554600.00
6195800.00
5957250.00
5980325.00
5980325.00
6006000.00
6052150.00
6123975.00
6123975.00
6077825.00
5957250.00
6579950.00
6674850.00
6531525.00
6195800.00
6339450.00
6123975.00
6221150.00
6267625.00
6316050.00
6195800.00
6221150.00
6052150.00
6579950.00
6746675.00
6603350.00
6339450.00
6626425.00
6316050.00
6603350.00
6579950.00
6651775.00
6387875.00
6674850.00
6651775.00
7082400.00
6985225.00
6603350.00
6410950.00
6674850.00
6316050.00
6579950.00
6626425.00
6723600.00
6508450.00
6626425.00
6698250.00
6962150.00
6746675.00
6459700.00
6149325.00
6436625.00
5646875.00
6029075.00
6244225.00
6459700.00
6149325.00
6149325.00
6149325.00
6316050.00
6077825.00
5765175.00
5503550.00
5693350.00
4952350.00
5406375.00
5670275.00
5718700.00
5454800.00
5477875.00
5406375.00
5646875.00
5477875.00
5144750.00
4903925.00
5311150.00
4426825.00
5001100.00
5262725.00
5262725.00
4952350.00
4665375.00
4642300.00
4903925.00
4665375.00
4211675.00
3899025.00
4234750.00
3445325.00
4162925.00
4544800.00
4665375.00
4401475.00
4068025.00
4306575.00
4401475.00
4329650.00
3611725.00
3278600.00
3516825.00
2799225.00
3540225.00
3804125.00
4019275.00
3660475.00
3324750.00
3516825.00
3611725.00
3421925.00
2704325.00
2391675.00
2678650.00
1889225.00
2750475.00
3278600.00




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=306795&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=306795&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306795&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 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=306795&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=306795&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306795&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')