Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSun, 16 Aug 2015 23:38:34 +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/16/t1439764792yjavczu6vzdsneu.htm/, Retrieved Sun, 19 May 2024 15:24:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=280221, Retrieved Sun, 19 May 2024 15:24:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2014-09-20 19:01:39] [46d78fa4bef23992fc20db72a2a0da97]
- R PD  [Univariate Data Series] [] [2015-08-16 14:59:07] [46d78fa4bef23992fc20db72a2a0da97]
- RMPD    [Harrell-Davis Quantiles] [] [2015-08-16 22:28:46] [46d78fa4bef23992fc20db72a2a0da97]
- RMP         [Central Tendency] [] [2015-08-16 22:38:34] [fced41568b3cc41e6659ad201d611503] [Current]
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Post a new message
Dataseries X:
193590
193745
193885
194040
194190
194345
194495
194650
194805
194955
195110
195260
195415
195570
195710
195865
196015
196170
196320
196475
196630
196780
196935
197085
197240
197395
197540
197695
197845
198000
198150
198305
198460
198610
198765
198915
199070
199225
199365
199520
199670
199825
199975
200130
200285
200435
200590
200740
200895
201050
201190
201345
201495
201650
201800
201955
202110
202260
202415
202565
202720
202875
203015
203170
203320
203475
203625
203780
203935
204085
204240
204390
204545
204700
204845
205000
205150
205305
205455
205610
205765
205915
206070
206220
206375
206530
206670
206825
206975
207130
207280
207435
207590
207740
207895
208045
208200
208355
208495
208650
208800
208955
209105
209260
209415
209565
209720
209870




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280221&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280221&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280221&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'Gertrude Mary Cox' @ cox.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean201727.87037037458.691699810081439.789667992455
Geometric Mean201672.050810043
Harmonic Mean201616.221913186
Quadratic Mean201783.662069655
Winsorized Mean ( 1 / 36 )201727.916666667458.227478217832440.235311621294
Winsorized Mean ( 2 / 36 )201727.638888889457.344872280389441.084291342429
Winsorized Mean ( 3 / 36 )201727.777777778455.998757067872442.386683408771
Winsorized Mean ( 4 / 36 )201727.592592593454.233187376863444.105798956573
Winsorized Mean ( 5 / 36 )201727.592592593452.025715717548446.27459363096
Winsorized Mean ( 6 / 36 )201727.592592593449.501442417465448.780745858524
Winsorized Mean ( 7 / 36 )201727.592592593446.503455875615451.794022953293
Winsorized Mean ( 8 / 36 )201727.962962963443.181467622872455.181404685055
Winsorized Mean ( 9 / 36 )201727.546296296439.496670084793458.996757034306
Winsorized Mean ( 10 / 36 )201728.935185185435.589849523792463.116703490049
Winsorized Mean ( 11 / 36 )201728.425925926431.204600643051467.825309899502
Winsorized Mean ( 12 / 36 )201728.425925926426.40565119457473.09041369594
Winsorized Mean ( 13 / 36 )201729.027777778421.355705109311478.761828383086
Winsorized Mean ( 14 / 36 )201727.083333333416.159208766746484.735358689131
Winsorized Mean ( 15 / 36 )201727.777777778410.470693758986491.45476362857
Winsorized Mean ( 16 / 36 )201727.037037037404.474027165005498.739161203897
Winsorized Mean ( 17 / 36 )201727.037037037398.072790247459506.759170632173
Winsorized Mean ( 18 / 36 )201727.037037037391.587092494498515.152416674386
Winsorized Mean ( 19 / 36 )201727.037037037384.590279962537524.524533112712
Winsorized Mean ( 20 / 36 )201727.962962963377.422291114386534.488735064737
Winsorized Mean ( 21 / 36 )201726.990740741369.974967929343545.244971219962
Winsorized Mean ( 22 / 36 )201730.046296296362.505138332487556.48879137065
Winsorized Mean ( 23 / 36 )201728.981481481354.510829415174569.034750826281
Winsorized Mean ( 24 / 36 )201728.981481481346.11648293807582.83552337372
Winsorized Mean ( 25 / 36 )201730.138888889337.597398598877597.546485032541
Winsorized Mean ( 26 / 36 )201727.731481481328.964742699744613.219914772461
Winsorized Mean ( 27 / 36 )201728.981481481319.934867295574630.531405303544
Winsorized Mean ( 28 / 36 )201727.685185185310.65607549058649.360180278536
Winsorized Mean ( 29 / 36 )201727.685185185300.976728810703670.243463613628
Winsorized Mean ( 30 / 36 )201727.685185185291.37216570761692.336842454668
Winsorized Mean ( 31 / 36 )201727.685185185281.205477426146717.367552835687
Winsorized Mean ( 32 / 36 )201729.166666667270.9689252402744.473435423801
Winsorized Mean ( 33 / 36 )201727.638888889260.501033755066774.383256684353
Winsorized Mean ( 34 / 36 )201730.787037037249.979716744132806.988621574925
Winsorized Mean ( 35 / 36 )201729.166666667239.056820216024843.85447143643
Winsorized Mean ( 36 / 36 )201729.166666667227.729620634265885.827526980535
Trimmed Mean ( 1 / 36 )201727.830188679454.471737111549443.873213042433
Trimmed Mean ( 2 / 36 )201727.740384615450.213686090549448.071097385615
Trimmed Mean ( 3 / 36 )201727.794117647445.899519125906452.406395308729
Trimmed Mean ( 4 / 36 )201727.8441.543901291453456.869179734959
Trimmed Mean ( 5 / 36 )201727.857142857437.145648628549461.466007441079
Trimmed Mean ( 6 / 36 )201727.916666667432.712880290159466.193464200548
Trimmed Mean ( 7 / 36 )201727.978723404428.226106730055471.078188725587
Trimmed Mean ( 8 / 36 )201728.043478261423.70283448718476.107373042283
Trimmed Mean ( 9 / 36 )201728.055555556419.132580980921481.298912824766
Trimmed Mean ( 10 / 36 )201728.125414.513958183396486.661838564066
Trimmed Mean ( 11 / 36 )201728.023255814409.823426986436492.231556256277
Trimmed Mean ( 12 / 36 )201727.976190476405.079446878602497.996078904818
Trimmed Mean ( 13 / 36 )201727.926829268400.29207711125503.95183508267
Trimmed Mean ( 14 / 36 )201727.8125395.448730091441510.123809105048
Trimmed Mean ( 15 / 36 )201727.884615385390.521911843573516.559707656528
Trimmed Mean ( 16 / 36 )201727.894736842385.532535127369523.244801298539
Trimmed Mean ( 17 / 36 )201727.972972973380.478175911151530.19591068498
Trimmed Mean ( 18 / 36 )201728.055555556375.370742080063537.410173306817
Trimmed Mean ( 19 / 36 )201728.142857143370.179593415477544.946686541767
Trimmed Mean ( 20 / 36 )201728.235294118364.931120972546552.784412457095
Trimmed Mean ( 21 / 36 )201728.257575758359.60838082196560.966507829059
Trimmed Mean ( 22 / 36 )201728.359375354.208314334999569.518984199258
Trimmed Mean ( 23 / 36 )201728.225806452348.69133025728578.529513933161
Trimmed Mean ( 24 / 36 )201728.166666667343.085389188979587.982388709508
Trimmed Mean ( 25 / 36 )201728.103448276337.406141361515597.879169105383
Trimmed Mean ( 26 / 36 )201727.946428571331.631537848667608.289391706242
Trimmed Mean ( 27 / 36 )201727.962962963325.734388203418619.302014980948
Trimmed Mean ( 28 / 36 )201727.884615385319.728401725856630.935142222215
Trimmed Mean ( 29 / 36 )201727.9313.607322709695643.249967051116
Trimmed Mean ( 30 / 36 )201727.916666667307.391141189907656.258068745185
Trimmed Mean ( 31 / 36 )201727.934782609301.02151270833670.144578597177
Trimmed Mean ( 32 / 36 )201727.954545455294.545073228814684.87974466558
Trimmed Mean ( 33 / 36 )201727.857142857287.927894113084700.619360844657
Trimmed Mean ( 34 / 36 )201727.875281.161104897266717.481442085348
Trimmed Mean ( 35 / 36 )201727.631578947274.196468433931735.7047037517
Trimmed Mean ( 36 / 36 )201727.5267.053031116614755.383674757511
Median201725
Midrange201730
Midmean - Weighted Average at Xnp201651.818181818
Midmean - Weighted Average at X(n+1)p201727.962962963
Midmean - Empirical Distribution Function201651.818181818
Midmean - Empirical Distribution Function - Averaging201727.962962963
Midmean - Empirical Distribution Function - Interpolation201727.962962963
Midmean - Closest Observation201651.818181818
Midmean - True Basic - Statistics Graphics Toolkit201727.962962963
Midmean - MS Excel (old versions)201727.946428571
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 201727.87037037 & 458.691699810081 & 439.789667992455 \tabularnewline
Geometric Mean & 201672.050810043 &  &  \tabularnewline
Harmonic Mean & 201616.221913186 &  &  \tabularnewline
Quadratic Mean & 201783.662069655 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 201727.916666667 & 458.227478217832 & 440.235311621294 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 201727.638888889 & 457.344872280389 & 441.084291342429 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 201727.777777778 & 455.998757067872 & 442.386683408771 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 201727.592592593 & 454.233187376863 & 444.105798956573 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 201727.592592593 & 452.025715717548 & 446.27459363096 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 201727.592592593 & 449.501442417465 & 448.780745858524 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 201727.592592593 & 446.503455875615 & 451.794022953293 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 201727.962962963 & 443.181467622872 & 455.181404685055 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 201727.546296296 & 439.496670084793 & 458.996757034306 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 201728.935185185 & 435.589849523792 & 463.116703490049 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 201728.425925926 & 431.204600643051 & 467.825309899502 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 201728.425925926 & 426.40565119457 & 473.09041369594 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 201729.027777778 & 421.355705109311 & 478.761828383086 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 201727.083333333 & 416.159208766746 & 484.735358689131 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 201727.777777778 & 410.470693758986 & 491.45476362857 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 201727.037037037 & 404.474027165005 & 498.739161203897 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 201727.037037037 & 398.072790247459 & 506.759170632173 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 201727.037037037 & 391.587092494498 & 515.152416674386 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 201727.037037037 & 384.590279962537 & 524.524533112712 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 201727.962962963 & 377.422291114386 & 534.488735064737 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 201726.990740741 & 369.974967929343 & 545.244971219962 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 201730.046296296 & 362.505138332487 & 556.48879137065 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 201728.981481481 & 354.510829415174 & 569.034750826281 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 201728.981481481 & 346.11648293807 & 582.83552337372 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 201730.138888889 & 337.597398598877 & 597.546485032541 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 201727.731481481 & 328.964742699744 & 613.219914772461 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 201728.981481481 & 319.934867295574 & 630.531405303544 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 201727.685185185 & 310.65607549058 & 649.360180278536 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 201727.685185185 & 300.976728810703 & 670.243463613628 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 201727.685185185 & 291.37216570761 & 692.336842454668 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 201727.685185185 & 281.205477426146 & 717.367552835687 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 201729.166666667 & 270.9689252402 & 744.473435423801 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 201727.638888889 & 260.501033755066 & 774.383256684353 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 201730.787037037 & 249.979716744132 & 806.988621574925 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 201729.166666667 & 239.056820216024 & 843.85447143643 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 201729.166666667 & 227.729620634265 & 885.827526980535 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 201727.830188679 & 454.471737111549 & 443.873213042433 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 201727.740384615 & 450.213686090549 & 448.071097385615 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 201727.794117647 & 445.899519125906 & 452.406395308729 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 201727.8 & 441.543901291453 & 456.869179734959 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 201727.857142857 & 437.145648628549 & 461.466007441079 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 201727.916666667 & 432.712880290159 & 466.193464200548 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 201727.978723404 & 428.226106730055 & 471.078188725587 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 201728.043478261 & 423.70283448718 & 476.107373042283 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 201728.055555556 & 419.132580980921 & 481.298912824766 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 201728.125 & 414.513958183396 & 486.661838564066 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 201728.023255814 & 409.823426986436 & 492.231556256277 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 201727.976190476 & 405.079446878602 & 497.996078904818 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 201727.926829268 & 400.29207711125 & 503.95183508267 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 201727.8125 & 395.448730091441 & 510.123809105048 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 201727.884615385 & 390.521911843573 & 516.559707656528 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 201727.894736842 & 385.532535127369 & 523.244801298539 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 201727.972972973 & 380.478175911151 & 530.19591068498 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 201728.055555556 & 375.370742080063 & 537.410173306817 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 201728.142857143 & 370.179593415477 & 544.946686541767 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 201728.235294118 & 364.931120972546 & 552.784412457095 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 201728.257575758 & 359.60838082196 & 560.966507829059 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 201728.359375 & 354.208314334999 & 569.518984199258 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 201728.225806452 & 348.69133025728 & 578.529513933161 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 201728.166666667 & 343.085389188979 & 587.982388709508 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 201728.103448276 & 337.406141361515 & 597.879169105383 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 201727.946428571 & 331.631537848667 & 608.289391706242 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 201727.962962963 & 325.734388203418 & 619.302014980948 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 201727.884615385 & 319.728401725856 & 630.935142222215 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 201727.9 & 313.607322709695 & 643.249967051116 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 201727.916666667 & 307.391141189907 & 656.258068745185 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 201727.934782609 & 301.02151270833 & 670.144578597177 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 201727.954545455 & 294.545073228814 & 684.87974466558 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 201727.857142857 & 287.927894113084 & 700.619360844657 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 201727.875 & 281.161104897266 & 717.481442085348 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 201727.631578947 & 274.196468433931 & 735.7047037517 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 201727.5 & 267.053031116614 & 755.383674757511 \tabularnewline
Median & 201725 &  &  \tabularnewline
Midrange & 201730 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 201651.818181818 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 201727.962962963 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 201651.818181818 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 201727.962962963 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 201727.962962963 &  &  \tabularnewline
Midmean - Closest Observation & 201651.818181818 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 201727.962962963 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 201727.946428571 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280221&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]201727.87037037[/C][C]458.691699810081[/C][C]439.789667992455[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]201672.050810043[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]201616.221913186[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]201783.662069655[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]201727.916666667[/C][C]458.227478217832[/C][C]440.235311621294[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]201727.638888889[/C][C]457.344872280389[/C][C]441.084291342429[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]201727.777777778[/C][C]455.998757067872[/C][C]442.386683408771[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]201727.592592593[/C][C]454.233187376863[/C][C]444.105798956573[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]201727.592592593[/C][C]452.025715717548[/C][C]446.27459363096[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]201727.592592593[/C][C]449.501442417465[/C][C]448.780745858524[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]201727.592592593[/C][C]446.503455875615[/C][C]451.794022953293[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]201727.962962963[/C][C]443.181467622872[/C][C]455.181404685055[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]201727.546296296[/C][C]439.496670084793[/C][C]458.996757034306[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]201728.935185185[/C][C]435.589849523792[/C][C]463.116703490049[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]201728.425925926[/C][C]431.204600643051[/C][C]467.825309899502[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]201728.425925926[/C][C]426.40565119457[/C][C]473.09041369594[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]201729.027777778[/C][C]421.355705109311[/C][C]478.761828383086[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]201727.083333333[/C][C]416.159208766746[/C][C]484.735358689131[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]201727.777777778[/C][C]410.470693758986[/C][C]491.45476362857[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]201727.037037037[/C][C]404.474027165005[/C][C]498.739161203897[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]201727.037037037[/C][C]398.072790247459[/C][C]506.759170632173[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]201727.037037037[/C][C]391.587092494498[/C][C]515.152416674386[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]201727.037037037[/C][C]384.590279962537[/C][C]524.524533112712[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]201727.962962963[/C][C]377.422291114386[/C][C]534.488735064737[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]201726.990740741[/C][C]369.974967929343[/C][C]545.244971219962[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]201730.046296296[/C][C]362.505138332487[/C][C]556.48879137065[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]201728.981481481[/C][C]354.510829415174[/C][C]569.034750826281[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]201728.981481481[/C][C]346.11648293807[/C][C]582.83552337372[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]201730.138888889[/C][C]337.597398598877[/C][C]597.546485032541[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]201727.731481481[/C][C]328.964742699744[/C][C]613.219914772461[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]201728.981481481[/C][C]319.934867295574[/C][C]630.531405303544[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]201727.685185185[/C][C]310.65607549058[/C][C]649.360180278536[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]201727.685185185[/C][C]300.976728810703[/C][C]670.243463613628[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]201727.685185185[/C][C]291.37216570761[/C][C]692.336842454668[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]201727.685185185[/C][C]281.205477426146[/C][C]717.367552835687[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]201729.166666667[/C][C]270.9689252402[/C][C]744.473435423801[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]201727.638888889[/C][C]260.501033755066[/C][C]774.383256684353[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]201730.787037037[/C][C]249.979716744132[/C][C]806.988621574925[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]201729.166666667[/C][C]239.056820216024[/C][C]843.85447143643[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]201729.166666667[/C][C]227.729620634265[/C][C]885.827526980535[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]201727.830188679[/C][C]454.471737111549[/C][C]443.873213042433[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]201727.740384615[/C][C]450.213686090549[/C][C]448.071097385615[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]201727.794117647[/C][C]445.899519125906[/C][C]452.406395308729[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]201727.8[/C][C]441.543901291453[/C][C]456.869179734959[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]201727.857142857[/C][C]437.145648628549[/C][C]461.466007441079[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]201727.916666667[/C][C]432.712880290159[/C][C]466.193464200548[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]201727.978723404[/C][C]428.226106730055[/C][C]471.078188725587[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]201728.043478261[/C][C]423.70283448718[/C][C]476.107373042283[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]201728.055555556[/C][C]419.132580980921[/C][C]481.298912824766[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]201728.125[/C][C]414.513958183396[/C][C]486.661838564066[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]201728.023255814[/C][C]409.823426986436[/C][C]492.231556256277[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]201727.976190476[/C][C]405.079446878602[/C][C]497.996078904818[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]201727.926829268[/C][C]400.29207711125[/C][C]503.95183508267[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]201727.8125[/C][C]395.448730091441[/C][C]510.123809105048[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]201727.884615385[/C][C]390.521911843573[/C][C]516.559707656528[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]201727.894736842[/C][C]385.532535127369[/C][C]523.244801298539[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]201727.972972973[/C][C]380.478175911151[/C][C]530.19591068498[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]201728.055555556[/C][C]375.370742080063[/C][C]537.410173306817[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]201728.142857143[/C][C]370.179593415477[/C][C]544.946686541767[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]201728.235294118[/C][C]364.931120972546[/C][C]552.784412457095[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]201728.257575758[/C][C]359.60838082196[/C][C]560.966507829059[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]201728.359375[/C][C]354.208314334999[/C][C]569.518984199258[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]201728.225806452[/C][C]348.69133025728[/C][C]578.529513933161[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]201728.166666667[/C][C]343.085389188979[/C][C]587.982388709508[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]201728.103448276[/C][C]337.406141361515[/C][C]597.879169105383[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]201727.946428571[/C][C]331.631537848667[/C][C]608.289391706242[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]201727.962962963[/C][C]325.734388203418[/C][C]619.302014980948[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]201727.884615385[/C][C]319.728401725856[/C][C]630.935142222215[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]201727.9[/C][C]313.607322709695[/C][C]643.249967051116[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]201727.916666667[/C][C]307.391141189907[/C][C]656.258068745185[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]201727.934782609[/C][C]301.02151270833[/C][C]670.144578597177[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]201727.954545455[/C][C]294.545073228814[/C][C]684.87974466558[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]201727.857142857[/C][C]287.927894113084[/C][C]700.619360844657[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]201727.875[/C][C]281.161104897266[/C][C]717.481442085348[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]201727.631578947[/C][C]274.196468433931[/C][C]735.7047037517[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]201727.5[/C][C]267.053031116614[/C][C]755.383674757511[/C][/ROW]
[ROW][C]Median[/C][C]201725[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]201730[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]201651.818181818[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]201727.962962963[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]201651.818181818[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]201727.962962963[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]201727.962962963[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]201651.818181818[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]201727.962962963[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]201727.946428571[/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=280221&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280221&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 Mean201727.87037037458.691699810081439.789667992455
Geometric Mean201672.050810043
Harmonic Mean201616.221913186
Quadratic Mean201783.662069655
Winsorized Mean ( 1 / 36 )201727.916666667458.227478217832440.235311621294
Winsorized Mean ( 2 / 36 )201727.638888889457.344872280389441.084291342429
Winsorized Mean ( 3 / 36 )201727.777777778455.998757067872442.386683408771
Winsorized Mean ( 4 / 36 )201727.592592593454.233187376863444.105798956573
Winsorized Mean ( 5 / 36 )201727.592592593452.025715717548446.27459363096
Winsorized Mean ( 6 / 36 )201727.592592593449.501442417465448.780745858524
Winsorized Mean ( 7 / 36 )201727.592592593446.503455875615451.794022953293
Winsorized Mean ( 8 / 36 )201727.962962963443.181467622872455.181404685055
Winsorized Mean ( 9 / 36 )201727.546296296439.496670084793458.996757034306
Winsorized Mean ( 10 / 36 )201728.935185185435.589849523792463.116703490049
Winsorized Mean ( 11 / 36 )201728.425925926431.204600643051467.825309899502
Winsorized Mean ( 12 / 36 )201728.425925926426.40565119457473.09041369594
Winsorized Mean ( 13 / 36 )201729.027777778421.355705109311478.761828383086
Winsorized Mean ( 14 / 36 )201727.083333333416.159208766746484.735358689131
Winsorized Mean ( 15 / 36 )201727.777777778410.470693758986491.45476362857
Winsorized Mean ( 16 / 36 )201727.037037037404.474027165005498.739161203897
Winsorized Mean ( 17 / 36 )201727.037037037398.072790247459506.759170632173
Winsorized Mean ( 18 / 36 )201727.037037037391.587092494498515.152416674386
Winsorized Mean ( 19 / 36 )201727.037037037384.590279962537524.524533112712
Winsorized Mean ( 20 / 36 )201727.962962963377.422291114386534.488735064737
Winsorized Mean ( 21 / 36 )201726.990740741369.974967929343545.244971219962
Winsorized Mean ( 22 / 36 )201730.046296296362.505138332487556.48879137065
Winsorized Mean ( 23 / 36 )201728.981481481354.510829415174569.034750826281
Winsorized Mean ( 24 / 36 )201728.981481481346.11648293807582.83552337372
Winsorized Mean ( 25 / 36 )201730.138888889337.597398598877597.546485032541
Winsorized Mean ( 26 / 36 )201727.731481481328.964742699744613.219914772461
Winsorized Mean ( 27 / 36 )201728.981481481319.934867295574630.531405303544
Winsorized Mean ( 28 / 36 )201727.685185185310.65607549058649.360180278536
Winsorized Mean ( 29 / 36 )201727.685185185300.976728810703670.243463613628
Winsorized Mean ( 30 / 36 )201727.685185185291.37216570761692.336842454668
Winsorized Mean ( 31 / 36 )201727.685185185281.205477426146717.367552835687
Winsorized Mean ( 32 / 36 )201729.166666667270.9689252402744.473435423801
Winsorized Mean ( 33 / 36 )201727.638888889260.501033755066774.383256684353
Winsorized Mean ( 34 / 36 )201730.787037037249.979716744132806.988621574925
Winsorized Mean ( 35 / 36 )201729.166666667239.056820216024843.85447143643
Winsorized Mean ( 36 / 36 )201729.166666667227.729620634265885.827526980535
Trimmed Mean ( 1 / 36 )201727.830188679454.471737111549443.873213042433
Trimmed Mean ( 2 / 36 )201727.740384615450.213686090549448.071097385615
Trimmed Mean ( 3 / 36 )201727.794117647445.899519125906452.406395308729
Trimmed Mean ( 4 / 36 )201727.8441.543901291453456.869179734959
Trimmed Mean ( 5 / 36 )201727.857142857437.145648628549461.466007441079
Trimmed Mean ( 6 / 36 )201727.916666667432.712880290159466.193464200548
Trimmed Mean ( 7 / 36 )201727.978723404428.226106730055471.078188725587
Trimmed Mean ( 8 / 36 )201728.043478261423.70283448718476.107373042283
Trimmed Mean ( 9 / 36 )201728.055555556419.132580980921481.298912824766
Trimmed Mean ( 10 / 36 )201728.125414.513958183396486.661838564066
Trimmed Mean ( 11 / 36 )201728.023255814409.823426986436492.231556256277
Trimmed Mean ( 12 / 36 )201727.976190476405.079446878602497.996078904818
Trimmed Mean ( 13 / 36 )201727.926829268400.29207711125503.95183508267
Trimmed Mean ( 14 / 36 )201727.8125395.448730091441510.123809105048
Trimmed Mean ( 15 / 36 )201727.884615385390.521911843573516.559707656528
Trimmed Mean ( 16 / 36 )201727.894736842385.532535127369523.244801298539
Trimmed Mean ( 17 / 36 )201727.972972973380.478175911151530.19591068498
Trimmed Mean ( 18 / 36 )201728.055555556375.370742080063537.410173306817
Trimmed Mean ( 19 / 36 )201728.142857143370.179593415477544.946686541767
Trimmed Mean ( 20 / 36 )201728.235294118364.931120972546552.784412457095
Trimmed Mean ( 21 / 36 )201728.257575758359.60838082196560.966507829059
Trimmed Mean ( 22 / 36 )201728.359375354.208314334999569.518984199258
Trimmed Mean ( 23 / 36 )201728.225806452348.69133025728578.529513933161
Trimmed Mean ( 24 / 36 )201728.166666667343.085389188979587.982388709508
Trimmed Mean ( 25 / 36 )201728.103448276337.406141361515597.879169105383
Trimmed Mean ( 26 / 36 )201727.946428571331.631537848667608.289391706242
Trimmed Mean ( 27 / 36 )201727.962962963325.734388203418619.302014980948
Trimmed Mean ( 28 / 36 )201727.884615385319.728401725856630.935142222215
Trimmed Mean ( 29 / 36 )201727.9313.607322709695643.249967051116
Trimmed Mean ( 30 / 36 )201727.916666667307.391141189907656.258068745185
Trimmed Mean ( 31 / 36 )201727.934782609301.02151270833670.144578597177
Trimmed Mean ( 32 / 36 )201727.954545455294.545073228814684.87974466558
Trimmed Mean ( 33 / 36 )201727.857142857287.927894113084700.619360844657
Trimmed Mean ( 34 / 36 )201727.875281.161104897266717.481442085348
Trimmed Mean ( 35 / 36 )201727.631578947274.196468433931735.7047037517
Trimmed Mean ( 36 / 36 )201727.5267.053031116614755.383674757511
Median201725
Midrange201730
Midmean - Weighted Average at Xnp201651.818181818
Midmean - Weighted Average at X(n+1)p201727.962962963
Midmean - Empirical Distribution Function201651.818181818
Midmean - Empirical Distribution Function - Averaging201727.962962963
Midmean - Empirical Distribution Function - Interpolation201727.962962963
Midmean - Closest Observation201651.818181818
Midmean - True Basic - Statistics Graphics Toolkit201727.962962963
Midmean - MS Excel (old versions)201727.946428571
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')