Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationFri, 11 Aug 2017 16:33:15 +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/11/t1502462386f6phqo2on7ey4nh.htm/, Retrieved Sat, 11 May 2024 17:49:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307119, Retrieved Sat, 11 May 2024 17:49:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact157
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2017-08-11 14:33:15] [b4406e95441bfa154caa3f19e1e15192] [Current]
Feedback Forum

Post a new message
Dataseries X:
5947968
5925816
5903352
5856864
6316752
6292416
5947968
5718960
5741112
5741112
5765760
5810064
5879016
5879016
5834712
5718960
6316752
6407856
6270264
5947968
6085872
5879016
5972304
6016920
6063408
5947968
5972304
5810064
6316752
6476808
6339216
6085872
6361368
6063408
6339216
6316752
6385704
6132360
6407856
6385704
6799104
6705816
6339216
6154512
6407856
6063408
6316752
6361368
6454656
6248112
6361368
6430320
6683664
6476808
6201312
5903352
6179160
5421000
5787912
5994456
6201312
5903352
5903352
5903352
6063408
5834712
5534568
5283408
5465616
4754256
5190120
5443464
5489952
5236608
5258760
5190120
5421000
5258760
4938960
4707768
5098704
4249752
4801056
5052216
5052216
4754256
4478760
4456608
4707768
4478760
4043208
3743064
4065360
3307512
3996408
4363008
4478760
4225416
3905304
4134312
4225416
4156464
3467256
3147456
3376152
2687256
3398616
3651960
3858504
3514056
3191760
3376152
3467256
3285048
2596152
2296008
2571504
1813656
2640456
3147456




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=307119&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=307119&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307119&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 Mean523430010802348.4552
Geometric Mean5070600
Harmonic Mean4868130
Quadratic Mean5365300
Winsorized Mean ( 1 / 40 )523754010693148.9804
Winsorized Mean ( 2 / 40 )524176010587149.5106
Winsorized Mean ( 3 / 40 )523721010518949.7885
Winsorized Mean ( 4 / 40 )523868010488049.9495
Winsorized Mean ( 5 / 40 )523971010438550.1959
Winsorized Mean ( 6 / 40 )526150099847.852.6952
Winsorized Mean ( 7 / 40 )52601909972052.7496
Winsorized Mean ( 8 / 40 )526315099197.953.057
Winsorized Mean ( 9 / 40 )527014097988.453.7833
Winsorized Mean ( 10 / 40 )527017097491.954.0575
Winsorized Mean ( 11 / 40 )527646096438.754.7131
Winsorized Mean ( 12 / 40 )527403096205.554.8204
Winsorized Mean ( 13 / 40 )527646095803.455.0759
Winsorized Mean ( 14 / 40 )528447094496.755.9222
Winsorized Mean ( 15 / 40 )528170094233.656.049
Winsorized Mean ( 16 / 40 )528794093229.956.7194
Winsorized Mean ( 17 / 40 )530748090159.858.8674
Winsorized Mean ( 18 / 40 )531777087751.660.6003
Winsorized Mean ( 19 / 40 )533605085038.462.7487
Winsorized Mean ( 20 / 40 )53438508390763.6878
Winsorized Mean ( 21 / 40 )535979081639.465.652
Winsorized Mean ( 22 / 40 )536837080443.566.7347
Winsorized Mean ( 23 / 40 )536795079397.667.6085
Winsorized Mean ( 24 / 40 )53773107708069.7628
Winsorized Mean ( 25 / 40 )53773107600970.7457
Winsorized Mean ( 26 / 40 )538211073040.373.6869
Winsorized Mean ( 27 / 40 )538211073040.373.6869
Winsorized Mean ( 28 / 40 )538262071801.574.9654
Winsorized Mean ( 29 / 40 )54040406766179.8693
Winsorized Mean ( 30 / 40 )542190064152.284.5162
Winsorized Mean ( 31 / 40 )541561062327.386.8899
Winsorized Mean ( 32 / 40 )541561062327.386.8899
Winsorized Mean ( 33 / 40 )540944061773.387.5691
Winsorized Mean ( 34 / 40 )547432053763.6101.822
Winsorized Mean ( 35 / 40 )547432053763.6101.822
Winsorized Mean ( 36 / 40 )548827052102.4105.336
Winsorized Mean ( 37 / 40 )547393050793.5107.768
Winsorized Mean ( 38 / 40 )548164048399.2113.259
Winsorized Mean ( 39 / 40 )551926042534.2129.76
Winsorized Mean ( 40 / 40 )555701038274.3145.189
Trimmed Mean ( 1 / 40 )525002010508449.9602
Trimmed Mean ( 2 / 40 )526294010302451.0845
Trimmed Mean ( 3 / 40 )527409010134752.0398
Trimmed Mean ( 4 / 40 )528726099740.953.0099
Trimmed Mean ( 5 / 40 )530051098036.154.0669
Trimmed Mean ( 6 / 40 )531402096250.255.2104
Trimmed Mean ( 7 / 40 )532392095310.355.8589
Trimmed Mean ( 8 / 40 )533443094263.256.5908
Trimmed Mean ( 9 / 40 )534491093169.757.3675
Trimmed Mean ( 10 / 40 )535488092137.858.1182
Trimmed Mean ( 11 / 40 )536525091035.158.9361
Trimmed Mean ( 12 / 40 )537534089939.259.7664
Trimmed Mean ( 13 / 40 )538612088708.460.7172
Trimmed Mean ( 14 / 40 )539713087350.961.7867
Trimmed Mean ( 15 / 40 )540785085980.762.8961
Trimmed Mean ( 16 / 40 )541932084426.364.19
Trimmed Mean ( 17 / 40 )543078082772.565.6109
Trimmed Mean ( 18 / 40 )544114081301.566.9255
Trimmed Mean ( 19 / 40 )545117079922.168.2061
Trimmed Mean ( 20 / 40 )546026078689.469.39
Trimmed Mean ( 21 / 40 )54692207739570.6663
Trimmed Mean ( 22 / 40 )547744076184.571.8971
Trimmed Mean ( 23 / 40 )548548074914.573.2233
Trimmed Mean ( 24 / 40 )549400073536.774.711
Trimmed Mean ( 25 / 40 )550233072213.876.195
Trimmed Mean ( 26 / 40 )551116070764.777.8801
Trimmed Mean ( 27 / 40 )552018069429.979.5073
Trimmed Mean ( 28 / 40 )552977067798.781.5616
Trimmed Mean ( 29 / 40 )553994065985.683.9569
Trimmed Mean ( 30 / 40 )554932064438.186.1185
Trimmed Mean ( 31 / 40 )555810063093.888.0927
Trimmed Mean ( 32 / 40 )556795061664.390.2945
Trimmed Mean ( 33 / 40 )557853059847.993.2118
Trimmed Mean ( 34 / 40 )559036057601.597.0522
Trimmed Mean ( 35 / 40 )55985505639999.2668
Trimmed Mean ( 36 / 40 )560742054819.6102.289
Trimmed Mean ( 37 / 40 )561605053117.6105.729
Trimmed Mean ( 38 / 40 )562653051057.8110.199
Trimmed Mean ( 39 / 40 )563742048857.4115.385
Trimmed Mean ( 40 / 40 )564651047415.2119.087
Median5776840
Midrange4306380
Midmean - Weighted Average at Xnp5529870
Midmean - Weighted Average at X(n+1)p5549320
Midmean - Empirical Distribution Function5529870
Midmean - Empirical Distribution Function - Averaging5549320
Midmean - Empirical Distribution Function - Interpolation5549320
Midmean - Closest Observation5529870
Midmean - True Basic - Statistics Graphics Toolkit5549320
Midmean - MS Excel (old versions)5539940
Number of observations120

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 5234300 & 108023 & 48.4552 \tabularnewline
Geometric Mean & 5070600 &  &  \tabularnewline
Harmonic Mean & 4868130 &  &  \tabularnewline
Quadratic Mean & 5365300 &  &  \tabularnewline
Winsorized Mean ( 1 / 40 ) & 5237540 & 106931 & 48.9804 \tabularnewline
Winsorized Mean ( 2 / 40 ) & 5241760 & 105871 & 49.5106 \tabularnewline
Winsorized Mean ( 3 / 40 ) & 5237210 & 105189 & 49.7885 \tabularnewline
Winsorized Mean ( 4 / 40 ) & 5238680 & 104880 & 49.9495 \tabularnewline
Winsorized Mean ( 5 / 40 ) & 5239710 & 104385 & 50.1959 \tabularnewline
Winsorized Mean ( 6 / 40 ) & 5261500 & 99847.8 & 52.6952 \tabularnewline
Winsorized Mean ( 7 / 40 ) & 5260190 & 99720 & 52.7496 \tabularnewline
Winsorized Mean ( 8 / 40 ) & 5263150 & 99197.9 & 53.057 \tabularnewline
Winsorized Mean ( 9 / 40 ) & 5270140 & 97988.4 & 53.7833 \tabularnewline
Winsorized Mean ( 10 / 40 ) & 5270170 & 97491.9 & 54.0575 \tabularnewline
Winsorized Mean ( 11 / 40 ) & 5276460 & 96438.7 & 54.7131 \tabularnewline
Winsorized Mean ( 12 / 40 ) & 5274030 & 96205.5 & 54.8204 \tabularnewline
Winsorized Mean ( 13 / 40 ) & 5276460 & 95803.4 & 55.0759 \tabularnewline
Winsorized Mean ( 14 / 40 ) & 5284470 & 94496.7 & 55.9222 \tabularnewline
Winsorized Mean ( 15 / 40 ) & 5281700 & 94233.6 & 56.049 \tabularnewline
Winsorized Mean ( 16 / 40 ) & 5287940 & 93229.9 & 56.7194 \tabularnewline
Winsorized Mean ( 17 / 40 ) & 5307480 & 90159.8 & 58.8674 \tabularnewline
Winsorized Mean ( 18 / 40 ) & 5317770 & 87751.6 & 60.6003 \tabularnewline
Winsorized Mean ( 19 / 40 ) & 5336050 & 85038.4 & 62.7487 \tabularnewline
Winsorized Mean ( 20 / 40 ) & 5343850 & 83907 & 63.6878 \tabularnewline
Winsorized Mean ( 21 / 40 ) & 5359790 & 81639.4 & 65.652 \tabularnewline
Winsorized Mean ( 22 / 40 ) & 5368370 & 80443.5 & 66.7347 \tabularnewline
Winsorized Mean ( 23 / 40 ) & 5367950 & 79397.6 & 67.6085 \tabularnewline
Winsorized Mean ( 24 / 40 ) & 5377310 & 77080 & 69.7628 \tabularnewline
Winsorized Mean ( 25 / 40 ) & 5377310 & 76009 & 70.7457 \tabularnewline
Winsorized Mean ( 26 / 40 ) & 5382110 & 73040.3 & 73.6869 \tabularnewline
Winsorized Mean ( 27 / 40 ) & 5382110 & 73040.3 & 73.6869 \tabularnewline
Winsorized Mean ( 28 / 40 ) & 5382620 & 71801.5 & 74.9654 \tabularnewline
Winsorized Mean ( 29 / 40 ) & 5404040 & 67661 & 79.8693 \tabularnewline
Winsorized Mean ( 30 / 40 ) & 5421900 & 64152.2 & 84.5162 \tabularnewline
Winsorized Mean ( 31 / 40 ) & 5415610 & 62327.3 & 86.8899 \tabularnewline
Winsorized Mean ( 32 / 40 ) & 5415610 & 62327.3 & 86.8899 \tabularnewline
Winsorized Mean ( 33 / 40 ) & 5409440 & 61773.3 & 87.5691 \tabularnewline
Winsorized Mean ( 34 / 40 ) & 5474320 & 53763.6 & 101.822 \tabularnewline
Winsorized Mean ( 35 / 40 ) & 5474320 & 53763.6 & 101.822 \tabularnewline
Winsorized Mean ( 36 / 40 ) & 5488270 & 52102.4 & 105.336 \tabularnewline
Winsorized Mean ( 37 / 40 ) & 5473930 & 50793.5 & 107.768 \tabularnewline
Winsorized Mean ( 38 / 40 ) & 5481640 & 48399.2 & 113.259 \tabularnewline
Winsorized Mean ( 39 / 40 ) & 5519260 & 42534.2 & 129.76 \tabularnewline
Winsorized Mean ( 40 / 40 ) & 5557010 & 38274.3 & 145.189 \tabularnewline
Trimmed Mean ( 1 / 40 ) & 5250020 & 105084 & 49.9602 \tabularnewline
Trimmed Mean ( 2 / 40 ) & 5262940 & 103024 & 51.0845 \tabularnewline
Trimmed Mean ( 3 / 40 ) & 5274090 & 101347 & 52.0398 \tabularnewline
Trimmed Mean ( 4 / 40 ) & 5287260 & 99740.9 & 53.0099 \tabularnewline
Trimmed Mean ( 5 / 40 ) & 5300510 & 98036.1 & 54.0669 \tabularnewline
Trimmed Mean ( 6 / 40 ) & 5314020 & 96250.2 & 55.2104 \tabularnewline
Trimmed Mean ( 7 / 40 ) & 5323920 & 95310.3 & 55.8589 \tabularnewline
Trimmed Mean ( 8 / 40 ) & 5334430 & 94263.2 & 56.5908 \tabularnewline
Trimmed Mean ( 9 / 40 ) & 5344910 & 93169.7 & 57.3675 \tabularnewline
Trimmed Mean ( 10 / 40 ) & 5354880 & 92137.8 & 58.1182 \tabularnewline
Trimmed Mean ( 11 / 40 ) & 5365250 & 91035.1 & 58.9361 \tabularnewline
Trimmed Mean ( 12 / 40 ) & 5375340 & 89939.2 & 59.7664 \tabularnewline
Trimmed Mean ( 13 / 40 ) & 5386120 & 88708.4 & 60.7172 \tabularnewline
Trimmed Mean ( 14 / 40 ) & 5397130 & 87350.9 & 61.7867 \tabularnewline
Trimmed Mean ( 15 / 40 ) & 5407850 & 85980.7 & 62.8961 \tabularnewline
Trimmed Mean ( 16 / 40 ) & 5419320 & 84426.3 & 64.19 \tabularnewline
Trimmed Mean ( 17 / 40 ) & 5430780 & 82772.5 & 65.6109 \tabularnewline
Trimmed Mean ( 18 / 40 ) & 5441140 & 81301.5 & 66.9255 \tabularnewline
Trimmed Mean ( 19 / 40 ) & 5451170 & 79922.1 & 68.2061 \tabularnewline
Trimmed Mean ( 20 / 40 ) & 5460260 & 78689.4 & 69.39 \tabularnewline
Trimmed Mean ( 21 / 40 ) & 5469220 & 77395 & 70.6663 \tabularnewline
Trimmed Mean ( 22 / 40 ) & 5477440 & 76184.5 & 71.8971 \tabularnewline
Trimmed Mean ( 23 / 40 ) & 5485480 & 74914.5 & 73.2233 \tabularnewline
Trimmed Mean ( 24 / 40 ) & 5494000 & 73536.7 & 74.711 \tabularnewline
Trimmed Mean ( 25 / 40 ) & 5502330 & 72213.8 & 76.195 \tabularnewline
Trimmed Mean ( 26 / 40 ) & 5511160 & 70764.7 & 77.8801 \tabularnewline
Trimmed Mean ( 27 / 40 ) & 5520180 & 69429.9 & 79.5073 \tabularnewline
Trimmed Mean ( 28 / 40 ) & 5529770 & 67798.7 & 81.5616 \tabularnewline
Trimmed Mean ( 29 / 40 ) & 5539940 & 65985.6 & 83.9569 \tabularnewline
Trimmed Mean ( 30 / 40 ) & 5549320 & 64438.1 & 86.1185 \tabularnewline
Trimmed Mean ( 31 / 40 ) & 5558100 & 63093.8 & 88.0927 \tabularnewline
Trimmed Mean ( 32 / 40 ) & 5567950 & 61664.3 & 90.2945 \tabularnewline
Trimmed Mean ( 33 / 40 ) & 5578530 & 59847.9 & 93.2118 \tabularnewline
Trimmed Mean ( 34 / 40 ) & 5590360 & 57601.5 & 97.0522 \tabularnewline
Trimmed Mean ( 35 / 40 ) & 5598550 & 56399 & 99.2668 \tabularnewline
Trimmed Mean ( 36 / 40 ) & 5607420 & 54819.6 & 102.289 \tabularnewline
Trimmed Mean ( 37 / 40 ) & 5616050 & 53117.6 & 105.729 \tabularnewline
Trimmed Mean ( 38 / 40 ) & 5626530 & 51057.8 & 110.199 \tabularnewline
Trimmed Mean ( 39 / 40 ) & 5637420 & 48857.4 & 115.385 \tabularnewline
Trimmed Mean ( 40 / 40 ) & 5646510 & 47415.2 & 119.087 \tabularnewline
Median & 5776840 &  &  \tabularnewline
Midrange & 4306380 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 5529870 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 5549320 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 5529870 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 5549320 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 5549320 &  &  \tabularnewline
Midmean - Closest Observation & 5529870 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 5549320 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 5539940 &  &  \tabularnewline
Number of observations & 120 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307119&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]5234300[/C][C]108023[/C][C]48.4552[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]5070600[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]4868130[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]5365300[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 40 )[/C][C]5237540[/C][C]106931[/C][C]48.9804[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 40 )[/C][C]5241760[/C][C]105871[/C][C]49.5106[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 40 )[/C][C]5237210[/C][C]105189[/C][C]49.7885[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 40 )[/C][C]5238680[/C][C]104880[/C][C]49.9495[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 40 )[/C][C]5239710[/C][C]104385[/C][C]50.1959[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 40 )[/C][C]5261500[/C][C]99847.8[/C][C]52.6952[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 40 )[/C][C]5260190[/C][C]99720[/C][C]52.7496[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 40 )[/C][C]5263150[/C][C]99197.9[/C][C]53.057[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 40 )[/C][C]5270140[/C][C]97988.4[/C][C]53.7833[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 40 )[/C][C]5270170[/C][C]97491.9[/C][C]54.0575[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 40 )[/C][C]5276460[/C][C]96438.7[/C][C]54.7131[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 40 )[/C][C]5274030[/C][C]96205.5[/C][C]54.8204[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 40 )[/C][C]5276460[/C][C]95803.4[/C][C]55.0759[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 40 )[/C][C]5284470[/C][C]94496.7[/C][C]55.9222[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 40 )[/C][C]5281700[/C][C]94233.6[/C][C]56.049[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 40 )[/C][C]5287940[/C][C]93229.9[/C][C]56.7194[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 40 )[/C][C]5307480[/C][C]90159.8[/C][C]58.8674[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 40 )[/C][C]5317770[/C][C]87751.6[/C][C]60.6003[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 40 )[/C][C]5336050[/C][C]85038.4[/C][C]62.7487[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 40 )[/C][C]5343850[/C][C]83907[/C][C]63.6878[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 40 )[/C][C]5359790[/C][C]81639.4[/C][C]65.652[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 40 )[/C][C]5368370[/C][C]80443.5[/C][C]66.7347[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 40 )[/C][C]5367950[/C][C]79397.6[/C][C]67.6085[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 40 )[/C][C]5377310[/C][C]77080[/C][C]69.7628[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 40 )[/C][C]5377310[/C][C]76009[/C][C]70.7457[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 40 )[/C][C]5382110[/C][C]73040.3[/C][C]73.6869[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 40 )[/C][C]5382110[/C][C]73040.3[/C][C]73.6869[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 40 )[/C][C]5382620[/C][C]71801.5[/C][C]74.9654[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 40 )[/C][C]5404040[/C][C]67661[/C][C]79.8693[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 40 )[/C][C]5421900[/C][C]64152.2[/C][C]84.5162[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 40 )[/C][C]5415610[/C][C]62327.3[/C][C]86.8899[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 40 )[/C][C]5415610[/C][C]62327.3[/C][C]86.8899[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 40 )[/C][C]5409440[/C][C]61773.3[/C][C]87.5691[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 40 )[/C][C]5474320[/C][C]53763.6[/C][C]101.822[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 40 )[/C][C]5474320[/C][C]53763.6[/C][C]101.822[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 40 )[/C][C]5488270[/C][C]52102.4[/C][C]105.336[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 40 )[/C][C]5473930[/C][C]50793.5[/C][C]107.768[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 40 )[/C][C]5481640[/C][C]48399.2[/C][C]113.259[/C][/ROW]
[ROW][C]Winsorized Mean ( 39 / 40 )[/C][C]5519260[/C][C]42534.2[/C][C]129.76[/C][/ROW]
[ROW][C]Winsorized Mean ( 40 / 40 )[/C][C]5557010[/C][C]38274.3[/C][C]145.189[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 40 )[/C][C]5250020[/C][C]105084[/C][C]49.9602[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 40 )[/C][C]5262940[/C][C]103024[/C][C]51.0845[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 40 )[/C][C]5274090[/C][C]101347[/C][C]52.0398[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 40 )[/C][C]5287260[/C][C]99740.9[/C][C]53.0099[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 40 )[/C][C]5300510[/C][C]98036.1[/C][C]54.0669[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 40 )[/C][C]5314020[/C][C]96250.2[/C][C]55.2104[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 40 )[/C][C]5323920[/C][C]95310.3[/C][C]55.8589[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 40 )[/C][C]5334430[/C][C]94263.2[/C][C]56.5908[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 40 )[/C][C]5344910[/C][C]93169.7[/C][C]57.3675[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 40 )[/C][C]5354880[/C][C]92137.8[/C][C]58.1182[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 40 )[/C][C]5365250[/C][C]91035.1[/C][C]58.9361[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 40 )[/C][C]5375340[/C][C]89939.2[/C][C]59.7664[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 40 )[/C][C]5386120[/C][C]88708.4[/C][C]60.7172[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 40 )[/C][C]5397130[/C][C]87350.9[/C][C]61.7867[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 40 )[/C][C]5407850[/C][C]85980.7[/C][C]62.8961[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 40 )[/C][C]5419320[/C][C]84426.3[/C][C]64.19[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 40 )[/C][C]5430780[/C][C]82772.5[/C][C]65.6109[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 40 )[/C][C]5441140[/C][C]81301.5[/C][C]66.9255[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 40 )[/C][C]5451170[/C][C]79922.1[/C][C]68.2061[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 40 )[/C][C]5460260[/C][C]78689.4[/C][C]69.39[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 40 )[/C][C]5469220[/C][C]77395[/C][C]70.6663[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 40 )[/C][C]5477440[/C][C]76184.5[/C][C]71.8971[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 40 )[/C][C]5485480[/C][C]74914.5[/C][C]73.2233[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 40 )[/C][C]5494000[/C][C]73536.7[/C][C]74.711[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 40 )[/C][C]5502330[/C][C]72213.8[/C][C]76.195[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 40 )[/C][C]5511160[/C][C]70764.7[/C][C]77.8801[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 40 )[/C][C]5520180[/C][C]69429.9[/C][C]79.5073[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 40 )[/C][C]5529770[/C][C]67798.7[/C][C]81.5616[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 40 )[/C][C]5539940[/C][C]65985.6[/C][C]83.9569[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 40 )[/C][C]5549320[/C][C]64438.1[/C][C]86.1185[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 40 )[/C][C]5558100[/C][C]63093.8[/C][C]88.0927[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 40 )[/C][C]5567950[/C][C]61664.3[/C][C]90.2945[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 40 )[/C][C]5578530[/C][C]59847.9[/C][C]93.2118[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 40 )[/C][C]5590360[/C][C]57601.5[/C][C]97.0522[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 40 )[/C][C]5598550[/C][C]56399[/C][C]99.2668[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 40 )[/C][C]5607420[/C][C]54819.6[/C][C]102.289[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 40 )[/C][C]5616050[/C][C]53117.6[/C][C]105.729[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 40 )[/C][C]5626530[/C][C]51057.8[/C][C]110.199[/C][/ROW]
[ROW][C]Trimmed Mean ( 39 / 40 )[/C][C]5637420[/C][C]48857.4[/C][C]115.385[/C][/ROW]
[ROW][C]Trimmed Mean ( 40 / 40 )[/C][C]5646510[/C][C]47415.2[/C][C]119.087[/C][/ROW]
[ROW][C]Median[/C][C]5776840[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]4306380[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]5529870[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]5549320[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]5529870[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]5549320[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]5549320[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]5529870[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]5549320[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]5539940[/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=307119&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307119&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 Mean523430010802348.4552
Geometric Mean5070600
Harmonic Mean4868130
Quadratic Mean5365300
Winsorized Mean ( 1 / 40 )523754010693148.9804
Winsorized Mean ( 2 / 40 )524176010587149.5106
Winsorized Mean ( 3 / 40 )523721010518949.7885
Winsorized Mean ( 4 / 40 )523868010488049.9495
Winsorized Mean ( 5 / 40 )523971010438550.1959
Winsorized Mean ( 6 / 40 )526150099847.852.6952
Winsorized Mean ( 7 / 40 )52601909972052.7496
Winsorized Mean ( 8 / 40 )526315099197.953.057
Winsorized Mean ( 9 / 40 )527014097988.453.7833
Winsorized Mean ( 10 / 40 )527017097491.954.0575
Winsorized Mean ( 11 / 40 )527646096438.754.7131
Winsorized Mean ( 12 / 40 )527403096205.554.8204
Winsorized Mean ( 13 / 40 )527646095803.455.0759
Winsorized Mean ( 14 / 40 )528447094496.755.9222
Winsorized Mean ( 15 / 40 )528170094233.656.049
Winsorized Mean ( 16 / 40 )528794093229.956.7194
Winsorized Mean ( 17 / 40 )530748090159.858.8674
Winsorized Mean ( 18 / 40 )531777087751.660.6003
Winsorized Mean ( 19 / 40 )533605085038.462.7487
Winsorized Mean ( 20 / 40 )53438508390763.6878
Winsorized Mean ( 21 / 40 )535979081639.465.652
Winsorized Mean ( 22 / 40 )536837080443.566.7347
Winsorized Mean ( 23 / 40 )536795079397.667.6085
Winsorized Mean ( 24 / 40 )53773107708069.7628
Winsorized Mean ( 25 / 40 )53773107600970.7457
Winsorized Mean ( 26 / 40 )538211073040.373.6869
Winsorized Mean ( 27 / 40 )538211073040.373.6869
Winsorized Mean ( 28 / 40 )538262071801.574.9654
Winsorized Mean ( 29 / 40 )54040406766179.8693
Winsorized Mean ( 30 / 40 )542190064152.284.5162
Winsorized Mean ( 31 / 40 )541561062327.386.8899
Winsorized Mean ( 32 / 40 )541561062327.386.8899
Winsorized Mean ( 33 / 40 )540944061773.387.5691
Winsorized Mean ( 34 / 40 )547432053763.6101.822
Winsorized Mean ( 35 / 40 )547432053763.6101.822
Winsorized Mean ( 36 / 40 )548827052102.4105.336
Winsorized Mean ( 37 / 40 )547393050793.5107.768
Winsorized Mean ( 38 / 40 )548164048399.2113.259
Winsorized Mean ( 39 / 40 )551926042534.2129.76
Winsorized Mean ( 40 / 40 )555701038274.3145.189
Trimmed Mean ( 1 / 40 )525002010508449.9602
Trimmed Mean ( 2 / 40 )526294010302451.0845
Trimmed Mean ( 3 / 40 )527409010134752.0398
Trimmed Mean ( 4 / 40 )528726099740.953.0099
Trimmed Mean ( 5 / 40 )530051098036.154.0669
Trimmed Mean ( 6 / 40 )531402096250.255.2104
Trimmed Mean ( 7 / 40 )532392095310.355.8589
Trimmed Mean ( 8 / 40 )533443094263.256.5908
Trimmed Mean ( 9 / 40 )534491093169.757.3675
Trimmed Mean ( 10 / 40 )535488092137.858.1182
Trimmed Mean ( 11 / 40 )536525091035.158.9361
Trimmed Mean ( 12 / 40 )537534089939.259.7664
Trimmed Mean ( 13 / 40 )538612088708.460.7172
Trimmed Mean ( 14 / 40 )539713087350.961.7867
Trimmed Mean ( 15 / 40 )540785085980.762.8961
Trimmed Mean ( 16 / 40 )541932084426.364.19
Trimmed Mean ( 17 / 40 )543078082772.565.6109
Trimmed Mean ( 18 / 40 )544114081301.566.9255
Trimmed Mean ( 19 / 40 )545117079922.168.2061
Trimmed Mean ( 20 / 40 )546026078689.469.39
Trimmed Mean ( 21 / 40 )54692207739570.6663
Trimmed Mean ( 22 / 40 )547744076184.571.8971
Trimmed Mean ( 23 / 40 )548548074914.573.2233
Trimmed Mean ( 24 / 40 )549400073536.774.711
Trimmed Mean ( 25 / 40 )550233072213.876.195
Trimmed Mean ( 26 / 40 )551116070764.777.8801
Trimmed Mean ( 27 / 40 )552018069429.979.5073
Trimmed Mean ( 28 / 40 )552977067798.781.5616
Trimmed Mean ( 29 / 40 )553994065985.683.9569
Trimmed Mean ( 30 / 40 )554932064438.186.1185
Trimmed Mean ( 31 / 40 )555810063093.888.0927
Trimmed Mean ( 32 / 40 )556795061664.390.2945
Trimmed Mean ( 33 / 40 )557853059847.993.2118
Trimmed Mean ( 34 / 40 )559036057601.597.0522
Trimmed Mean ( 35 / 40 )55985505639999.2668
Trimmed Mean ( 36 / 40 )560742054819.6102.289
Trimmed Mean ( 37 / 40 )561605053117.6105.729
Trimmed Mean ( 38 / 40 )562653051057.8110.199
Trimmed Mean ( 39 / 40 )563742048857.4115.385
Trimmed Mean ( 40 / 40 )564651047415.2119.087
Median5776840
Midrange4306380
Midmean - Weighted Average at Xnp5529870
Midmean - Weighted Average at X(n+1)p5549320
Midmean - Empirical Distribution Function5529870
Midmean - Empirical Distribution Function - Averaging5549320
Midmean - Empirical Distribution Function - Interpolation5549320
Midmean - Closest Observation5529870
Midmean - True Basic - Statistics Graphics Toolkit5549320
Midmean - MS Excel (old versions)5539940
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')