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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 computationTue, 11 Aug 2015 21:28:21 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Aug/11/t1439324934z5ij1ri8qy0z2o3.htm/, Retrieved Wed, 15 May 2024 12:31:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=280021, Retrieved Wed, 15 May 2024 12:31:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2015-08-11 20:28:21] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
48600
46800
49500
39600
51300
50400
54000
55800
62100
54000
51300
63900
54000
40500
47700
36000
50400
41400
54900
49500
52200
58500
57600
68400
49500
41400
45900
33300
47700
36900
52200
49500
44100
63000
56700
64800
48600
45000
40500
33300
44100
39600
54000
52200
45000
60300
55800
72000
57600
35100
35100
35100
41400
41400
55800
51300
45900
57600
53100
76500
60300
35100
36900
30600
42300
48600
61200
60300
48600
56700
50400
72000
54900
44100
39600
29700
44100
53100
62100
58500
43200
62100
48600
74700
62100
45000
41400
27900
44100
42300
63900
63900
48600
63000
46800
72900
62100
45900
35100
24300
47700
45900
60300
69300
51300
57600
43200
74700




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280021&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280021&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280021&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean505251053.6623933937947.9517920700022
Geometric Mean49311.0228862582
Harmonic Mean48044.3881394417
Quadratic Mean51687.2082821272
Winsorized Mean ( 1 / 36 )50541.66666666671042.6755239204448.4730537038321
Winsorized Mean ( 2 / 36 )505751036.1542617803648.8102996489152
Winsorized Mean ( 3 / 36 )505501020.9602406970249.5122121165944
Winsorized Mean ( 4 / 36 )50616.6666666667996.94887595446750.771577046222
Winsorized Mean ( 5 / 36 )50616.6666666667996.94887595446750.771577046222
Winsorized Mean ( 6 / 36 )50566.6666666667952.38128615926553.094981391949
Winsorized Mean ( 7 / 36 )50508.3333333333941.84033355704753.6272779299848
Winsorized Mean ( 8 / 36 )50241.6666666667897.88136174638755.9557963971389
Winsorized Mean ( 9 / 36 )50166.6666666667886.76960496789256.5723795511497
Winsorized Mean ( 10 / 36 )50166.6666666667886.76960496789256.5723795511497
Winsorized Mean ( 11 / 36 )50258.3333333333872.489351650557.6033773228968
Winsorized Mean ( 12 / 36 )50258.3333333333843.07198922979559.6133354866265
Winsorized Mean ( 13 / 36 )50258.3333333333843.07198922979559.6133354866265
Winsorized Mean ( 14 / 36 )50491.6666666667777.75195588348264.9200124598993
Winsorized Mean ( 15 / 36 )50491.6666666667777.75195588348264.9200124598993
Winsorized Mean ( 16 / 36 )50491.6666666667777.75195588348264.9200124598993
Winsorized Mean ( 17 / 36 )50633.3333333333759.64548762850666.6538986381696
Winsorized Mean ( 18 / 36 )50633.3333333333759.64548762850666.6538986381696
Winsorized Mean ( 19 / 36 )50633.3333333333718.19188566243270.5011214191471
Winsorized Mean ( 20 / 36 )50466.6666666667695.71825022546472.538943243636
Winsorized Mean ( 21 / 36 )50466.6666666667695.71825022546472.538943243636
Winsorized Mean ( 22 / 36 )50466.6666666667695.71825022546472.538943243636
Winsorized Mean ( 23 / 36 )50466.6666666667695.71825022546472.538943243636
Winsorized Mean ( 24 / 36 )50266.6666666667620.19911049297981.0492401814493
Winsorized Mean ( 25 / 36 )50266.6666666667620.19911049297981.0492401814493
Winsorized Mean ( 26 / 36 )50266.6666666667568.05309596361988.4893807002259
Winsorized Mean ( 27 / 36 )50266.6666666667568.05309596361988.4893807002259
Winsorized Mean ( 28 / 36 )50500541.58818027108593.2442801368428
Winsorized Mean ( 29 / 36 )50500541.58818027108593.2442801368428
Winsorized Mean ( 30 / 36 )50250511.52602915655598.2354702122514
Winsorized Mean ( 31 / 36 )50250511.52602915655598.2354702122514
Winsorized Mean ( 32 / 36 )49983.3333333333480.715868913363103.976874003179
Winsorized Mean ( 33 / 36 )50258.3333333333449.947354714458111.698252710538
Winsorized Mean ( 34 / 36 )50258.3333333333449.947354714458111.698252710538
Winsorized Mean ( 35 / 36 )49966.6666666667417.012317689634119.820601327788
Winsorized Mean ( 36 / 36 )50266.6666666667384.357969614024130.780862218481
Trimmed Mean ( 1 / 36 )50527.3584905661015.0294947173849.7792022335615
Trimmed Mean ( 2 / 36 )50512.5983.94191235723151.3368719897165
Trimmed Mean ( 3 / 36 )50479.4117647059952.79920316900652.9801154291603
Trimmed Mean ( 4 / 36 )50454924.11510499110854.5970948072377
Trimmed Mean ( 5 / 36 )50409.1836734694899.76279307914356.024970204603
Trimmed Mean ( 6 / 36 )50362.5872.12591890222657.7468217701785
Trimmed Mean ( 7 / 36 )50323.4042553191851.94198003231159.0690509856206
Trimmed Mean ( 8 / 36 )50292.3913043478831.35983921756860.4941313399025
Trimmed Mean ( 9 / 36 )50300816.88638793073161.5752701271174
Trimmed Mean ( 10 / 36 )50318.1818181818802.38272621451962.7109484965771
Trimmed Mean ( 11 / 36 )50337.2093023256785.72950325732164.0642983286839
Trimmed Mean ( 12 / 36 )50346.4285714286769.04663101702365.4660283796421
Trimmed Mean ( 13 / 36 )50356.0975609756754.64455193292666.7282330893331
Trimmed Mean ( 14 / 36 )50366.25737.94090821622568.2524162019245
Trimmed Mean ( 15 / 36 )50353.8461538462728.56125767578569.1140870082526
Trimmed Mean ( 16 / 36 )50340.7894736842717.49607892217670.161762485596
Trimmed Mean ( 17 / 36 )50327.027027027704.44533729519471.4420613816027
Trimmed Mean ( 18 / 36 )50300691.65040424345972.7246014625251
Trimmed Mean ( 19 / 36 )50271.4285714286676.45141205116674.3163923909824
Trimmed Mean ( 20 / 36 )50241.1764705882664.53240372604975.6038022959975
Trimmed Mean ( 21 / 36 )50222.7272727273653.5853973146676.8418748017838
Trimmed Mean ( 22 / 36 )50203.125640.32004936984478.4031751768607
Trimmed Mean ( 23 / 36 )50182.2580645161624.22675252651280.3910724130407
Trimmed Mean ( 24 / 36 )50160604.63464244736982.9591896967204
Trimmed Mean ( 25 / 36 )50151.724137931593.06968206756484.5629538220395
Trimmed Mean ( 26 / 36 )50142.8571428571578.70128412879786.6472194170857
Trimmed Mean ( 27 / 36 )50133.3333333333569.32414232635588.0576276433317
Trimmed Mean ( 28 / 36 )50123.0769230769557.35596036163889.930099411792
Trimmed Mean ( 29 / 36 )50094546.4573101686391.6704728216401
Trimmed Mean ( 30 / 36 )50062.5532.32916048849294.0442562907132
Trimmed Mean ( 31 / 36 )50047.8260869565519.97527933096296.2503951175365
Trimmed Mean ( 32 / 36 )50031.8181818182503.70480221300299.3276577114332
Trimmed Mean ( 33 / 36 )50035.7142857143488.88720768876102.346131170543
Trimmed Mean ( 34 / 36 )50017.5475.676138209116105.150323891192
Trimmed Mean ( 35 / 36 )49997.3684210526457.550638354577109.271770663136
Trimmed Mean ( 36 / 36 )50000441.26441700446113.310745378988
Median49500
Midrange50400
Midmean - Weighted Average at Xnp50142.8571428571
Midmean - Weighted Average at X(n+1)p50142.8571428571
Midmean - Empirical Distribution Function50142.8571428571
Midmean - Empirical Distribution Function - Averaging50142.8571428571
Midmean - Empirical Distribution Function - Interpolation50142.8571428571
Midmean - Closest Observation50142.8571428571
Midmean - True Basic - Statistics Graphics Toolkit50142.8571428571
Midmean - MS Excel (old versions)50142.8571428571
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 50525 & 1053.66239339379 & 47.9517920700022 \tabularnewline
Geometric Mean & 49311.0228862582 &  &  \tabularnewline
Harmonic Mean & 48044.3881394417 &  &  \tabularnewline
Quadratic Mean & 51687.2082821272 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 50541.6666666667 & 1042.67552392044 & 48.4730537038321 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 50575 & 1036.15426178036 & 48.8102996489152 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 50550 & 1020.96024069702 & 49.5122121165944 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 50616.6666666667 & 996.948875954467 & 50.771577046222 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 50616.6666666667 & 996.948875954467 & 50.771577046222 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 50566.6666666667 & 952.381286159265 & 53.094981391949 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 50508.3333333333 & 941.840333557047 & 53.6272779299848 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 50241.6666666667 & 897.881361746387 & 55.9557963971389 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 50166.6666666667 & 886.769604967892 & 56.5723795511497 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 50166.6666666667 & 886.769604967892 & 56.5723795511497 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 50258.3333333333 & 872.4893516505 & 57.6033773228968 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 50258.3333333333 & 843.071989229795 & 59.6133354866265 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 50258.3333333333 & 843.071989229795 & 59.6133354866265 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 50491.6666666667 & 777.751955883482 & 64.9200124598993 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 50491.6666666667 & 777.751955883482 & 64.9200124598993 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 50491.6666666667 & 777.751955883482 & 64.9200124598993 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 50633.3333333333 & 759.645487628506 & 66.6538986381696 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 50633.3333333333 & 759.645487628506 & 66.6538986381696 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 50633.3333333333 & 718.191885662432 & 70.5011214191471 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 50466.6666666667 & 695.718250225464 & 72.538943243636 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 50466.6666666667 & 695.718250225464 & 72.538943243636 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 50466.6666666667 & 695.718250225464 & 72.538943243636 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 50466.6666666667 & 695.718250225464 & 72.538943243636 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 50266.6666666667 & 620.199110492979 & 81.0492401814493 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 50266.6666666667 & 620.199110492979 & 81.0492401814493 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 50266.6666666667 & 568.053095963619 & 88.4893807002259 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 50266.6666666667 & 568.053095963619 & 88.4893807002259 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 50500 & 541.588180271085 & 93.2442801368428 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 50500 & 541.588180271085 & 93.2442801368428 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 50250 & 511.526029156555 & 98.2354702122514 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 50250 & 511.526029156555 & 98.2354702122514 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 49983.3333333333 & 480.715868913363 & 103.976874003179 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 50258.3333333333 & 449.947354714458 & 111.698252710538 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 50258.3333333333 & 449.947354714458 & 111.698252710538 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 49966.6666666667 & 417.012317689634 & 119.820601327788 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 50266.6666666667 & 384.357969614024 & 130.780862218481 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 50527.358490566 & 1015.02949471738 & 49.7792022335615 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 50512.5 & 983.941912357231 & 51.3368719897165 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 50479.4117647059 & 952.799203169006 & 52.9801154291603 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 50454 & 924.115104991108 & 54.5970948072377 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 50409.1836734694 & 899.762793079143 & 56.024970204603 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 50362.5 & 872.125918902226 & 57.7468217701785 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 50323.4042553191 & 851.941980032311 & 59.0690509856206 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 50292.3913043478 & 831.359839217568 & 60.4941313399025 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 50300 & 816.886387930731 & 61.5752701271174 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 50318.1818181818 & 802.382726214519 & 62.7109484965771 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 50337.2093023256 & 785.729503257321 & 64.0642983286839 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 50346.4285714286 & 769.046631017023 & 65.4660283796421 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 50356.0975609756 & 754.644551932926 & 66.7282330893331 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 50366.25 & 737.940908216225 & 68.2524162019245 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 50353.8461538462 & 728.561257675785 & 69.1140870082526 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 50340.7894736842 & 717.496078922176 & 70.161762485596 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 50327.027027027 & 704.445337295194 & 71.4420613816027 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 50300 & 691.650404243459 & 72.7246014625251 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 50271.4285714286 & 676.451412051166 & 74.3163923909824 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 50241.1764705882 & 664.532403726049 & 75.6038022959975 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 50222.7272727273 & 653.58539731466 & 76.8418748017838 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 50203.125 & 640.320049369844 & 78.4031751768607 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 50182.2580645161 & 624.226752526512 & 80.3910724130407 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 50160 & 604.634642447369 & 82.9591896967204 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 50151.724137931 & 593.069682067564 & 84.5629538220395 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 50142.8571428571 & 578.701284128797 & 86.6472194170857 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 50133.3333333333 & 569.324142326355 & 88.0576276433317 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 50123.0769230769 & 557.355960361638 & 89.930099411792 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 50094 & 546.45731016863 & 91.6704728216401 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 50062.5 & 532.329160488492 & 94.0442562907132 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 50047.8260869565 & 519.975279330962 & 96.2503951175365 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 50031.8181818182 & 503.704802213002 & 99.3276577114332 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 50035.7142857143 & 488.88720768876 & 102.346131170543 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 50017.5 & 475.676138209116 & 105.150323891192 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 49997.3684210526 & 457.550638354577 & 109.271770663136 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 50000 & 441.26441700446 & 113.310745378988 \tabularnewline
Median & 49500 &  &  \tabularnewline
Midrange & 50400 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 50142.8571428571 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 50142.8571428571 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 50142.8571428571 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 50142.8571428571 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 50142.8571428571 &  &  \tabularnewline
Midmean - Closest Observation & 50142.8571428571 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 50142.8571428571 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 50142.8571428571 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280021&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]50525[/C][C]1053.66239339379[/C][C]47.9517920700022[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]49311.0228862582[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]48044.3881394417[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]51687.2082821272[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]50541.6666666667[/C][C]1042.67552392044[/C][C]48.4730537038321[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]50575[/C][C]1036.15426178036[/C][C]48.8102996489152[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]50550[/C][C]1020.96024069702[/C][C]49.5122121165944[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]50616.6666666667[/C][C]996.948875954467[/C][C]50.771577046222[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]50616.6666666667[/C][C]996.948875954467[/C][C]50.771577046222[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]50566.6666666667[/C][C]952.381286159265[/C][C]53.094981391949[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]50508.3333333333[/C][C]941.840333557047[/C][C]53.6272779299848[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]50241.6666666667[/C][C]897.881361746387[/C][C]55.9557963971389[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]50166.6666666667[/C][C]886.769604967892[/C][C]56.5723795511497[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]50166.6666666667[/C][C]886.769604967892[/C][C]56.5723795511497[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]50258.3333333333[/C][C]872.4893516505[/C][C]57.6033773228968[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]50258.3333333333[/C][C]843.071989229795[/C][C]59.6133354866265[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]50258.3333333333[/C][C]843.071989229795[/C][C]59.6133354866265[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]50491.6666666667[/C][C]777.751955883482[/C][C]64.9200124598993[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]50491.6666666667[/C][C]777.751955883482[/C][C]64.9200124598993[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]50491.6666666667[/C][C]777.751955883482[/C][C]64.9200124598993[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]50633.3333333333[/C][C]759.645487628506[/C][C]66.6538986381696[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]50633.3333333333[/C][C]759.645487628506[/C][C]66.6538986381696[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]50633.3333333333[/C][C]718.191885662432[/C][C]70.5011214191471[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]50466.6666666667[/C][C]695.718250225464[/C][C]72.538943243636[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]50466.6666666667[/C][C]695.718250225464[/C][C]72.538943243636[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]50466.6666666667[/C][C]695.718250225464[/C][C]72.538943243636[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]50466.6666666667[/C][C]695.718250225464[/C][C]72.538943243636[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]50266.6666666667[/C][C]620.199110492979[/C][C]81.0492401814493[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]50266.6666666667[/C][C]620.199110492979[/C][C]81.0492401814493[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]50266.6666666667[/C][C]568.053095963619[/C][C]88.4893807002259[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]50266.6666666667[/C][C]568.053095963619[/C][C]88.4893807002259[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]50500[/C][C]541.588180271085[/C][C]93.2442801368428[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]50500[/C][C]541.588180271085[/C][C]93.2442801368428[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]50250[/C][C]511.526029156555[/C][C]98.2354702122514[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]50250[/C][C]511.526029156555[/C][C]98.2354702122514[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]49983.3333333333[/C][C]480.715868913363[/C][C]103.976874003179[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]50258.3333333333[/C][C]449.947354714458[/C][C]111.698252710538[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]50258.3333333333[/C][C]449.947354714458[/C][C]111.698252710538[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]49966.6666666667[/C][C]417.012317689634[/C][C]119.820601327788[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]50266.6666666667[/C][C]384.357969614024[/C][C]130.780862218481[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]50527.358490566[/C][C]1015.02949471738[/C][C]49.7792022335615[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]50512.5[/C][C]983.941912357231[/C][C]51.3368719897165[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]50479.4117647059[/C][C]952.799203169006[/C][C]52.9801154291603[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]50454[/C][C]924.115104991108[/C][C]54.5970948072377[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]50409.1836734694[/C][C]899.762793079143[/C][C]56.024970204603[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]50362.5[/C][C]872.125918902226[/C][C]57.7468217701785[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]50323.4042553191[/C][C]851.941980032311[/C][C]59.0690509856206[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]50292.3913043478[/C][C]831.359839217568[/C][C]60.4941313399025[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]50300[/C][C]816.886387930731[/C][C]61.5752701271174[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]50318.1818181818[/C][C]802.382726214519[/C][C]62.7109484965771[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]50337.2093023256[/C][C]785.729503257321[/C][C]64.0642983286839[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]50346.4285714286[/C][C]769.046631017023[/C][C]65.4660283796421[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]50356.0975609756[/C][C]754.644551932926[/C][C]66.7282330893331[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]50366.25[/C][C]737.940908216225[/C][C]68.2524162019245[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]50353.8461538462[/C][C]728.561257675785[/C][C]69.1140870082526[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]50340.7894736842[/C][C]717.496078922176[/C][C]70.161762485596[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]50327.027027027[/C][C]704.445337295194[/C][C]71.4420613816027[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]50300[/C][C]691.650404243459[/C][C]72.7246014625251[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]50271.4285714286[/C][C]676.451412051166[/C][C]74.3163923909824[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]50241.1764705882[/C][C]664.532403726049[/C][C]75.6038022959975[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]50222.7272727273[/C][C]653.58539731466[/C][C]76.8418748017838[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]50203.125[/C][C]640.320049369844[/C][C]78.4031751768607[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]50182.2580645161[/C][C]624.226752526512[/C][C]80.3910724130407[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]50160[/C][C]604.634642447369[/C][C]82.9591896967204[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]50151.724137931[/C][C]593.069682067564[/C][C]84.5629538220395[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]50142.8571428571[/C][C]578.701284128797[/C][C]86.6472194170857[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]50133.3333333333[/C][C]569.324142326355[/C][C]88.0576276433317[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]50123.0769230769[/C][C]557.355960361638[/C][C]89.930099411792[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]50094[/C][C]546.45731016863[/C][C]91.6704728216401[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]50062.5[/C][C]532.329160488492[/C][C]94.0442562907132[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]50047.8260869565[/C][C]519.975279330962[/C][C]96.2503951175365[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]50031.8181818182[/C][C]503.704802213002[/C][C]99.3276577114332[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]50035.7142857143[/C][C]488.88720768876[/C][C]102.346131170543[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]50017.5[/C][C]475.676138209116[/C][C]105.150323891192[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]49997.3684210526[/C][C]457.550638354577[/C][C]109.271770663136[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]50000[/C][C]441.26441700446[/C][C]113.310745378988[/C][/ROW]
[ROW][C]Median[/C][C]49500[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]50400[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]50142.8571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]50142.8571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]50142.8571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]50142.8571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]50142.8571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]50142.8571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]50142.8571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]50142.8571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]108[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280021&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280021&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 Mean505251053.6623933937947.9517920700022
Geometric Mean49311.0228862582
Harmonic Mean48044.3881394417
Quadratic Mean51687.2082821272
Winsorized Mean ( 1 / 36 )50541.66666666671042.6755239204448.4730537038321
Winsorized Mean ( 2 / 36 )505751036.1542617803648.8102996489152
Winsorized Mean ( 3 / 36 )505501020.9602406970249.5122121165944
Winsorized Mean ( 4 / 36 )50616.6666666667996.94887595446750.771577046222
Winsorized Mean ( 5 / 36 )50616.6666666667996.94887595446750.771577046222
Winsorized Mean ( 6 / 36 )50566.6666666667952.38128615926553.094981391949
Winsorized Mean ( 7 / 36 )50508.3333333333941.84033355704753.6272779299848
Winsorized Mean ( 8 / 36 )50241.6666666667897.88136174638755.9557963971389
Winsorized Mean ( 9 / 36 )50166.6666666667886.76960496789256.5723795511497
Winsorized Mean ( 10 / 36 )50166.6666666667886.76960496789256.5723795511497
Winsorized Mean ( 11 / 36 )50258.3333333333872.489351650557.6033773228968
Winsorized Mean ( 12 / 36 )50258.3333333333843.07198922979559.6133354866265
Winsorized Mean ( 13 / 36 )50258.3333333333843.07198922979559.6133354866265
Winsorized Mean ( 14 / 36 )50491.6666666667777.75195588348264.9200124598993
Winsorized Mean ( 15 / 36 )50491.6666666667777.75195588348264.9200124598993
Winsorized Mean ( 16 / 36 )50491.6666666667777.75195588348264.9200124598993
Winsorized Mean ( 17 / 36 )50633.3333333333759.64548762850666.6538986381696
Winsorized Mean ( 18 / 36 )50633.3333333333759.64548762850666.6538986381696
Winsorized Mean ( 19 / 36 )50633.3333333333718.19188566243270.5011214191471
Winsorized Mean ( 20 / 36 )50466.6666666667695.71825022546472.538943243636
Winsorized Mean ( 21 / 36 )50466.6666666667695.71825022546472.538943243636
Winsorized Mean ( 22 / 36 )50466.6666666667695.71825022546472.538943243636
Winsorized Mean ( 23 / 36 )50466.6666666667695.71825022546472.538943243636
Winsorized Mean ( 24 / 36 )50266.6666666667620.19911049297981.0492401814493
Winsorized Mean ( 25 / 36 )50266.6666666667620.19911049297981.0492401814493
Winsorized Mean ( 26 / 36 )50266.6666666667568.05309596361988.4893807002259
Winsorized Mean ( 27 / 36 )50266.6666666667568.05309596361988.4893807002259
Winsorized Mean ( 28 / 36 )50500541.58818027108593.2442801368428
Winsorized Mean ( 29 / 36 )50500541.58818027108593.2442801368428
Winsorized Mean ( 30 / 36 )50250511.52602915655598.2354702122514
Winsorized Mean ( 31 / 36 )50250511.52602915655598.2354702122514
Winsorized Mean ( 32 / 36 )49983.3333333333480.715868913363103.976874003179
Winsorized Mean ( 33 / 36 )50258.3333333333449.947354714458111.698252710538
Winsorized Mean ( 34 / 36 )50258.3333333333449.947354714458111.698252710538
Winsorized Mean ( 35 / 36 )49966.6666666667417.012317689634119.820601327788
Winsorized Mean ( 36 / 36 )50266.6666666667384.357969614024130.780862218481
Trimmed Mean ( 1 / 36 )50527.3584905661015.0294947173849.7792022335615
Trimmed Mean ( 2 / 36 )50512.5983.94191235723151.3368719897165
Trimmed Mean ( 3 / 36 )50479.4117647059952.79920316900652.9801154291603
Trimmed Mean ( 4 / 36 )50454924.11510499110854.5970948072377
Trimmed Mean ( 5 / 36 )50409.1836734694899.76279307914356.024970204603
Trimmed Mean ( 6 / 36 )50362.5872.12591890222657.7468217701785
Trimmed Mean ( 7 / 36 )50323.4042553191851.94198003231159.0690509856206
Trimmed Mean ( 8 / 36 )50292.3913043478831.35983921756860.4941313399025
Trimmed Mean ( 9 / 36 )50300816.88638793073161.5752701271174
Trimmed Mean ( 10 / 36 )50318.1818181818802.38272621451962.7109484965771
Trimmed Mean ( 11 / 36 )50337.2093023256785.72950325732164.0642983286839
Trimmed Mean ( 12 / 36 )50346.4285714286769.04663101702365.4660283796421
Trimmed Mean ( 13 / 36 )50356.0975609756754.64455193292666.7282330893331
Trimmed Mean ( 14 / 36 )50366.25737.94090821622568.2524162019245
Trimmed Mean ( 15 / 36 )50353.8461538462728.56125767578569.1140870082526
Trimmed Mean ( 16 / 36 )50340.7894736842717.49607892217670.161762485596
Trimmed Mean ( 17 / 36 )50327.027027027704.44533729519471.4420613816027
Trimmed Mean ( 18 / 36 )50300691.65040424345972.7246014625251
Trimmed Mean ( 19 / 36 )50271.4285714286676.45141205116674.3163923909824
Trimmed Mean ( 20 / 36 )50241.1764705882664.53240372604975.6038022959975
Trimmed Mean ( 21 / 36 )50222.7272727273653.5853973146676.8418748017838
Trimmed Mean ( 22 / 36 )50203.125640.32004936984478.4031751768607
Trimmed Mean ( 23 / 36 )50182.2580645161624.22675252651280.3910724130407
Trimmed Mean ( 24 / 36 )50160604.63464244736982.9591896967204
Trimmed Mean ( 25 / 36 )50151.724137931593.06968206756484.5629538220395
Trimmed Mean ( 26 / 36 )50142.8571428571578.70128412879786.6472194170857
Trimmed Mean ( 27 / 36 )50133.3333333333569.32414232635588.0576276433317
Trimmed Mean ( 28 / 36 )50123.0769230769557.35596036163889.930099411792
Trimmed Mean ( 29 / 36 )50094546.4573101686391.6704728216401
Trimmed Mean ( 30 / 36 )50062.5532.32916048849294.0442562907132
Trimmed Mean ( 31 / 36 )50047.8260869565519.97527933096296.2503951175365
Trimmed Mean ( 32 / 36 )50031.8181818182503.70480221300299.3276577114332
Trimmed Mean ( 33 / 36 )50035.7142857143488.88720768876102.346131170543
Trimmed Mean ( 34 / 36 )50017.5475.676138209116105.150323891192
Trimmed Mean ( 35 / 36 )49997.3684210526457.550638354577109.271770663136
Trimmed Mean ( 36 / 36 )50000441.26441700446113.310745378988
Median49500
Midrange50400
Midmean - Weighted Average at Xnp50142.8571428571
Midmean - Weighted Average at X(n+1)p50142.8571428571
Midmean - Empirical Distribution Function50142.8571428571
Midmean - Empirical Distribution Function - Averaging50142.8571428571
Midmean - Empirical Distribution Function - Interpolation50142.8571428571
Midmean - Closest Observation50142.8571428571
Midmean - True Basic - Statistics Graphics Toolkit50142.8571428571
Midmean - MS Excel (old versions)50142.8571428571
Number of observations108



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,hyperlink('arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE)
a<-table.element(a,arm)
a<-table.element(a,hyperlink('arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean'))
a<-table.element(a,armose)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE)
a<-table.element(a,geo)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE)
a<-table.element(a,har)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE)
a<-table.element(a,qua)
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,hyperlink('winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE)
a<-table.element(a,win[j,1])
a<-table.element(a,win[j,2])
a<-table.element(a,win[j,1]/win[j,2])
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,hyperlink('arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE)
a<-table.element(a,tri[j,1])
a<-table.element(a,tri[j,2])
a<-table.element(a,tri[j,1]/tri[j,2])
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,hyperlink('median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE)
a<-table.element(a,median(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE)
a<-table.element(a,midr)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_1.htm','Weighted Average at Xnp',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[2])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_3.htm','Empirical Distribution Function',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[3])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[4])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[5])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_6.htm','Closest Observation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[6])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[7])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_8.htm','MS Excel (old versions)',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[8])
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,length(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')