Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationThu, 08 Oct 2015 18:02:01 +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/Oct/08/t1444323793ww79s1ejovwq35g.htm/, Retrieved Wed, 15 May 2024 21:49:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=281569, Retrieved Wed, 15 May 2024 21:49:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact64
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [centrummaten] [2015-10-08 17:02:01] [1d0d2a0cfdb7bd945f85de3fbad0315e] [Current]
Feedback Forum

Post a new message
Dataseries X:
173019
173690
172439
171914
171968
169500
173898
172308
171568
164939
161275
160770
162466
160185
154836
154103
150495
142707
149962
149967
144572
143819
141070
144119
145330
143279
139063
139202
133632
134476
141859
140693
138047
138346
140167
146796
152228
155410
159032
160312
157687
160141
167421
167628
164403
163405
163229
171154
173323
172381
168983
165380
161641
161933
172018
168455
164332
161193
157645
161694
163411
161834
159511
156359
154223
151497
160607
159672
155601
154668
153960
157307
165218
165616
162212
159787
157454
156485
165887
166836
163541
163973
164805
167521
174347
173374
172198
171055
168385
167281
177670
177280
174846
174476
174595
178392
185345
183293
181081
177795
173552
170734
179293
178659
175894
174815
173506
175376




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=281569&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=281569&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281569&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 Mean162117.9074074071154.13840806018140.466608056037
Geometric Mean161664.728389501
Harmonic Mean161197.7908095
Quadratic Mean162556.893723113
Winsorized Mean ( 1 / 36 )162106.7222222221148.93449072283141.093094106902
Winsorized Mean ( 2 / 36 )162131.8888888891128.15042158233143.714779330122
Winsorized Mean ( 3 / 36 )162090.5277777781119.03088275329144.849020948346
Winsorized Mean ( 4 / 36 )162093.6018518521110.50028001689145.964485348339
Winsorized Mean ( 5 / 36 )162087.6759259261107.54328307686146.348841081525
Winsorized Mean ( 6 / 36 )162108.120370371092.82930967722148.338005702145
Winsorized Mean ( 7 / 36 )162134.1111111111085.3981840565149.377540420383
Winsorized Mean ( 8 / 36 )162133.1481481481076.43486173742150.62049169093
Winsorized Mean ( 9 / 36 )162083.3981481481049.80168650392154.394301544631
Winsorized Mean ( 10 / 36 )162113.9537037041029.98350277515157.394709009329
Winsorized Mean ( 11 / 36 )162118.2314814811013.3755039531159.978439235082
Winsorized Mean ( 12 / 36 )162174.7870370371002.6246904128161.750242725687
Winsorized Mean ( 13 / 36 )162184.416666667993.360333768277163.268464778965
Winsorized Mean ( 14 / 36 )162227.712962963981.6342397022165.262891616513
Winsorized Mean ( 15 / 36 )162315.074074074962.006727381785168.725508308901
Winsorized Mean ( 16 / 36 )162465.740740741919.01485307254176.782497255153
Winsorized Mean ( 17 / 36 )162931.351851852839.292406370557194.129424518963
Winsorized Mean ( 18 / 36 )162909.185185185836.426700718391194.768035316502
Winsorized Mean ( 19 / 36 )162993.981481481822.145760980758198.254359770756
Winsorized Mean ( 20 / 36 )163155.092592593793.281340580216205.671158826525
Winsorized Mean ( 21 / 36 )163287.314814815772.813227414375211.2894927551
Winsorized Mean ( 22 / 36 )163578.203703704719.574617470055227.326256002229
Winsorized Mean ( 23 / 36 )163485.138888889700.817711885338233.277692781311
Winsorized Mean ( 24 / 36 )163498.916666667695.950443583963234.928963942734
Winsorized Mean ( 25 / 36 )163585.027777778681.213846260374240.137555447239
Winsorized Mean ( 26 / 36 )163598.990740741673.114023651392243.047960660925
Winsorized Mean ( 27 / 36 )163697.490740741650.461402588516251.66364997109
Winsorized Mean ( 28 / 36 )163734.046296296643.035938312914254.626587008299
Winsorized Mean ( 29 / 36 )163923.083333333617.606023640478265.416911524096
Winsorized Mean ( 30 / 36 )163861.972222222602.038536434694272.178543906212
Winsorized Mean ( 31 / 36 )163979.083333333561.199015886352292.194174778347
Winsorized Mean ( 32 / 36 )163993.305555556552.868536952201296.622604823204
Winsorized Mean ( 33 / 36 )163953.583333333534.759180493763306.593302768452
Winsorized Mean ( 34 / 36 )163578.324074074488.203574676465335.061709006286
Winsorized Mean ( 35 / 36 )163846.657407407421.206798221231388.993383058718
Winsorized Mean ( 36 / 36 )163830.324074074384.356376917443426.245885102782
Trimmed Mean ( 1 / 36 )162167.5188679251123.21721312409144.377700922937
Trimmed Mean ( 2 / 36 )162230.6538461541094.33138949046148.246367968747
Trimmed Mean ( 3 / 36 )162282.9411764711074.21247174127151.071548176512
Trimmed Mean ( 4 / 36 )162352.211055.29032189912153.846014344023
Trimmed Mean ( 5 / 36 )162423.4591836731036.68339579226156.676049643435
Trimmed Mean ( 6 / 36 )162499.0104166671016.39187282445159.878305564465
Trimmed Mean ( 7 / 36 )162573.861702128996.919620949435163.076198206729
Trimmed Mean ( 8 / 36 )162647.608695652976.372797742323166.583511002912
Trimmed Mean ( 9 / 36 )162724.777777778954.706046723222170.444901167525
Trimmed Mean ( 10 / 36 )162812.238636364934.879495220468174.15318174025
Trimmed Mean ( 11 / 36 )162899.930232558915.634936541436177.909255896098
Trimmed Mean ( 12 / 36 )162991.297619048896.239091330844181.861401935747
Trimmed Mean ( 13 / 36 )163080.914634146875.593765278743186.251799751258
Trimmed Mean ( 14 / 36 )163174.0125853.081113141821191.27608147254
Trimmed Mean ( 15 / 36 )163267.602564103828.73293717905197.008704782332
Trimmed Mean ( 16 / 36 )163357.842105263803.477197801461203.313600625203
Trimmed Mean ( 17 / 36 )163439.216216216780.868687534286209.30435401668
Trimmed Mean ( 18 / 36 )163484.027777778766.962958660869213.157657656928
Trimmed Mean ( 19 / 36 )163533.3750.817202364503217.807076722529
Trimmed Mean ( 20 / 36 )163578.382352941733.796076108544222.920764608646
Trimmed Mean ( 21 / 36 )163613.015151515717.93792268944227.892983474965
Trimmed Mean ( 22 / 36 )163639.1875702.050097727892233.087621566609
Trimmed Mean ( 23 / 36 )163644.016129032690.955457659579236.837287143416
Trimmed Mean ( 24 / 36 )163656.45680.064871625233240.648292285544
Trimmed Mean ( 25 / 36 )163668.672413793667.29218615138245.272874177885
Trimmed Mean ( 26 / 36 )163675.125653.770160009239250.355759580227
Trimmed Mean ( 27 / 36 )163680.981481481638.193893879442256.475317378078
Trimmed Mean ( 28 / 36 )163679.711538462622.526181908676262.928237068868
Trimmed Mean ( 29 / 36 )163675.52603.997174773768270.987227814941
Trimmed Mean ( 30 / 36 )163656.3125585.117249082592279.698321586994
Trimmed Mean ( 31 / 36 )163640.217391304563.946871887875290.169563036143
Trimmed Mean ( 32 / 36 )163613.386363636544.886097855568300.270803398264
Trimmed Mean ( 33 / 36 )163582.857142857521.534871350114313.656605011636
Trimmed Mean ( 34 / 36 )163552.525494.811433893943330.535055976608
Trimmed Mean ( 35 / 36 )163550.368421053471.198054509282347.094744674568
Trimmed Mean ( 36 / 36 )163524.972222222456.190625162213358.45754647868
Median163408
Midrange159488.5
Midmean - Weighted Average at Xnp163520.163636364
Midmean - Weighted Average at X(n+1)p163680.981481481
Midmean - Empirical Distribution Function163520.163636364
Midmean - Empirical Distribution Function - Averaging163680.981481481
Midmean - Empirical Distribution Function - Interpolation163680.981481481
Midmean - Closest Observation163520.163636364
Midmean - True Basic - Statistics Graphics Toolkit163680.981481481
Midmean - MS Excel (old versions)163675.125
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 162117.907407407 & 1154.13840806018 & 140.466608056037 \tabularnewline
Geometric Mean & 161664.728389501 &  &  \tabularnewline
Harmonic Mean & 161197.7908095 &  &  \tabularnewline
Quadratic Mean & 162556.893723113 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 162106.722222222 & 1148.93449072283 & 141.093094106902 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 162131.888888889 & 1128.15042158233 & 143.714779330122 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 162090.527777778 & 1119.03088275329 & 144.849020948346 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 162093.601851852 & 1110.50028001689 & 145.964485348339 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 162087.675925926 & 1107.54328307686 & 146.348841081525 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 162108.12037037 & 1092.82930967722 & 148.338005702145 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 162134.111111111 & 1085.3981840565 & 149.377540420383 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 162133.148148148 & 1076.43486173742 & 150.62049169093 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 162083.398148148 & 1049.80168650392 & 154.394301544631 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 162113.953703704 & 1029.98350277515 & 157.394709009329 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 162118.231481481 & 1013.3755039531 & 159.978439235082 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 162174.787037037 & 1002.6246904128 & 161.750242725687 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 162184.416666667 & 993.360333768277 & 163.268464778965 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 162227.712962963 & 981.6342397022 & 165.262891616513 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 162315.074074074 & 962.006727381785 & 168.725508308901 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 162465.740740741 & 919.01485307254 & 176.782497255153 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 162931.351851852 & 839.292406370557 & 194.129424518963 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 162909.185185185 & 836.426700718391 & 194.768035316502 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 162993.981481481 & 822.145760980758 & 198.254359770756 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 163155.092592593 & 793.281340580216 & 205.671158826525 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 163287.314814815 & 772.813227414375 & 211.2894927551 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 163578.203703704 & 719.574617470055 & 227.326256002229 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 163485.138888889 & 700.817711885338 & 233.277692781311 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 163498.916666667 & 695.950443583963 & 234.928963942734 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 163585.027777778 & 681.213846260374 & 240.137555447239 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 163598.990740741 & 673.114023651392 & 243.047960660925 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 163697.490740741 & 650.461402588516 & 251.66364997109 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 163734.046296296 & 643.035938312914 & 254.626587008299 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 163923.083333333 & 617.606023640478 & 265.416911524096 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 163861.972222222 & 602.038536434694 & 272.178543906212 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 163979.083333333 & 561.199015886352 & 292.194174778347 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 163993.305555556 & 552.868536952201 & 296.622604823204 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 163953.583333333 & 534.759180493763 & 306.593302768452 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 163578.324074074 & 488.203574676465 & 335.061709006286 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 163846.657407407 & 421.206798221231 & 388.993383058718 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 163830.324074074 & 384.356376917443 & 426.245885102782 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 162167.518867925 & 1123.21721312409 & 144.377700922937 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 162230.653846154 & 1094.33138949046 & 148.246367968747 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 162282.941176471 & 1074.21247174127 & 151.071548176512 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 162352.21 & 1055.29032189912 & 153.846014344023 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 162423.459183673 & 1036.68339579226 & 156.676049643435 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 162499.010416667 & 1016.39187282445 & 159.878305564465 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 162573.861702128 & 996.919620949435 & 163.076198206729 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 162647.608695652 & 976.372797742323 & 166.583511002912 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 162724.777777778 & 954.706046723222 & 170.444901167525 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 162812.238636364 & 934.879495220468 & 174.15318174025 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 162899.930232558 & 915.634936541436 & 177.909255896098 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 162991.297619048 & 896.239091330844 & 181.861401935747 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 163080.914634146 & 875.593765278743 & 186.251799751258 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 163174.0125 & 853.081113141821 & 191.27608147254 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 163267.602564103 & 828.73293717905 & 197.008704782332 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 163357.842105263 & 803.477197801461 & 203.313600625203 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 163439.216216216 & 780.868687534286 & 209.30435401668 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 163484.027777778 & 766.962958660869 & 213.157657656928 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 163533.3 & 750.817202364503 & 217.807076722529 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 163578.382352941 & 733.796076108544 & 222.920764608646 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 163613.015151515 & 717.93792268944 & 227.892983474965 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 163639.1875 & 702.050097727892 & 233.087621566609 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 163644.016129032 & 690.955457659579 & 236.837287143416 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 163656.45 & 680.064871625233 & 240.648292285544 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 163668.672413793 & 667.29218615138 & 245.272874177885 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 163675.125 & 653.770160009239 & 250.355759580227 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 163680.981481481 & 638.193893879442 & 256.475317378078 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 163679.711538462 & 622.526181908676 & 262.928237068868 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 163675.52 & 603.997174773768 & 270.987227814941 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 163656.3125 & 585.117249082592 & 279.698321586994 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 163640.217391304 & 563.946871887875 & 290.169563036143 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 163613.386363636 & 544.886097855568 & 300.270803398264 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 163582.857142857 & 521.534871350114 & 313.656605011636 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 163552.525 & 494.811433893943 & 330.535055976608 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 163550.368421053 & 471.198054509282 & 347.094744674568 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 163524.972222222 & 456.190625162213 & 358.45754647868 \tabularnewline
Median & 163408 &  &  \tabularnewline
Midrange & 159488.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 163520.163636364 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 163680.981481481 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 163520.163636364 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 163680.981481481 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 163680.981481481 &  &  \tabularnewline
Midmean - Closest Observation & 163520.163636364 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 163680.981481481 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 163675.125 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=281569&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]162117.907407407[/C][C]1154.13840806018[/C][C]140.466608056037[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]161664.728389501[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]161197.7908095[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]162556.893723113[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]162106.722222222[/C][C]1148.93449072283[/C][C]141.093094106902[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]162131.888888889[/C][C]1128.15042158233[/C][C]143.714779330122[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]162090.527777778[/C][C]1119.03088275329[/C][C]144.849020948346[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]162093.601851852[/C][C]1110.50028001689[/C][C]145.964485348339[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]162087.675925926[/C][C]1107.54328307686[/C][C]146.348841081525[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]162108.12037037[/C][C]1092.82930967722[/C][C]148.338005702145[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]162134.111111111[/C][C]1085.3981840565[/C][C]149.377540420383[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]162133.148148148[/C][C]1076.43486173742[/C][C]150.62049169093[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]162083.398148148[/C][C]1049.80168650392[/C][C]154.394301544631[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]162113.953703704[/C][C]1029.98350277515[/C][C]157.394709009329[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]162118.231481481[/C][C]1013.3755039531[/C][C]159.978439235082[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]162174.787037037[/C][C]1002.6246904128[/C][C]161.750242725687[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]162184.416666667[/C][C]993.360333768277[/C][C]163.268464778965[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]162227.712962963[/C][C]981.6342397022[/C][C]165.262891616513[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]162315.074074074[/C][C]962.006727381785[/C][C]168.725508308901[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]162465.740740741[/C][C]919.01485307254[/C][C]176.782497255153[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]162931.351851852[/C][C]839.292406370557[/C][C]194.129424518963[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]162909.185185185[/C][C]836.426700718391[/C][C]194.768035316502[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]162993.981481481[/C][C]822.145760980758[/C][C]198.254359770756[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]163155.092592593[/C][C]793.281340580216[/C][C]205.671158826525[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]163287.314814815[/C][C]772.813227414375[/C][C]211.2894927551[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]163578.203703704[/C][C]719.574617470055[/C][C]227.326256002229[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]163485.138888889[/C][C]700.817711885338[/C][C]233.277692781311[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]163498.916666667[/C][C]695.950443583963[/C][C]234.928963942734[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]163585.027777778[/C][C]681.213846260374[/C][C]240.137555447239[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]163598.990740741[/C][C]673.114023651392[/C][C]243.047960660925[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]163697.490740741[/C][C]650.461402588516[/C][C]251.66364997109[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]163734.046296296[/C][C]643.035938312914[/C][C]254.626587008299[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]163923.083333333[/C][C]617.606023640478[/C][C]265.416911524096[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]163861.972222222[/C][C]602.038536434694[/C][C]272.178543906212[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]163979.083333333[/C][C]561.199015886352[/C][C]292.194174778347[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]163993.305555556[/C][C]552.868536952201[/C][C]296.622604823204[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]163953.583333333[/C][C]534.759180493763[/C][C]306.593302768452[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]163578.324074074[/C][C]488.203574676465[/C][C]335.061709006286[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]163846.657407407[/C][C]421.206798221231[/C][C]388.993383058718[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]163830.324074074[/C][C]384.356376917443[/C][C]426.245885102782[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]162167.518867925[/C][C]1123.21721312409[/C][C]144.377700922937[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]162230.653846154[/C][C]1094.33138949046[/C][C]148.246367968747[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]162282.941176471[/C][C]1074.21247174127[/C][C]151.071548176512[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]162352.21[/C][C]1055.29032189912[/C][C]153.846014344023[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]162423.459183673[/C][C]1036.68339579226[/C][C]156.676049643435[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]162499.010416667[/C][C]1016.39187282445[/C][C]159.878305564465[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]162573.861702128[/C][C]996.919620949435[/C][C]163.076198206729[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]162647.608695652[/C][C]976.372797742323[/C][C]166.583511002912[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]162724.777777778[/C][C]954.706046723222[/C][C]170.444901167525[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]162812.238636364[/C][C]934.879495220468[/C][C]174.15318174025[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]162899.930232558[/C][C]915.634936541436[/C][C]177.909255896098[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]162991.297619048[/C][C]896.239091330844[/C][C]181.861401935747[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]163080.914634146[/C][C]875.593765278743[/C][C]186.251799751258[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]163174.0125[/C][C]853.081113141821[/C][C]191.27608147254[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]163267.602564103[/C][C]828.73293717905[/C][C]197.008704782332[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]163357.842105263[/C][C]803.477197801461[/C][C]203.313600625203[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]163439.216216216[/C][C]780.868687534286[/C][C]209.30435401668[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]163484.027777778[/C][C]766.962958660869[/C][C]213.157657656928[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]163533.3[/C][C]750.817202364503[/C][C]217.807076722529[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]163578.382352941[/C][C]733.796076108544[/C][C]222.920764608646[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]163613.015151515[/C][C]717.93792268944[/C][C]227.892983474965[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]163639.1875[/C][C]702.050097727892[/C][C]233.087621566609[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]163644.016129032[/C][C]690.955457659579[/C][C]236.837287143416[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]163656.45[/C][C]680.064871625233[/C][C]240.648292285544[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]163668.672413793[/C][C]667.29218615138[/C][C]245.272874177885[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]163675.125[/C][C]653.770160009239[/C][C]250.355759580227[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]163680.981481481[/C][C]638.193893879442[/C][C]256.475317378078[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]163679.711538462[/C][C]622.526181908676[/C][C]262.928237068868[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]163675.52[/C][C]603.997174773768[/C][C]270.987227814941[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]163656.3125[/C][C]585.117249082592[/C][C]279.698321586994[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]163640.217391304[/C][C]563.946871887875[/C][C]290.169563036143[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]163613.386363636[/C][C]544.886097855568[/C][C]300.270803398264[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]163582.857142857[/C][C]521.534871350114[/C][C]313.656605011636[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]163552.525[/C][C]494.811433893943[/C][C]330.535055976608[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]163550.368421053[/C][C]471.198054509282[/C][C]347.094744674568[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]163524.972222222[/C][C]456.190625162213[/C][C]358.45754647868[/C][/ROW]
[ROW][C]Median[/C][C]163408[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]159488.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]163520.163636364[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]163680.981481481[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]163520.163636364[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]163680.981481481[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]163680.981481481[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]163520.163636364[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]163680.981481481[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]163675.125[/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=281569&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281569&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 Mean162117.9074074071154.13840806018140.466608056037
Geometric Mean161664.728389501
Harmonic Mean161197.7908095
Quadratic Mean162556.893723113
Winsorized Mean ( 1 / 36 )162106.7222222221148.93449072283141.093094106902
Winsorized Mean ( 2 / 36 )162131.8888888891128.15042158233143.714779330122
Winsorized Mean ( 3 / 36 )162090.5277777781119.03088275329144.849020948346
Winsorized Mean ( 4 / 36 )162093.6018518521110.50028001689145.964485348339
Winsorized Mean ( 5 / 36 )162087.6759259261107.54328307686146.348841081525
Winsorized Mean ( 6 / 36 )162108.120370371092.82930967722148.338005702145
Winsorized Mean ( 7 / 36 )162134.1111111111085.3981840565149.377540420383
Winsorized Mean ( 8 / 36 )162133.1481481481076.43486173742150.62049169093
Winsorized Mean ( 9 / 36 )162083.3981481481049.80168650392154.394301544631
Winsorized Mean ( 10 / 36 )162113.9537037041029.98350277515157.394709009329
Winsorized Mean ( 11 / 36 )162118.2314814811013.3755039531159.978439235082
Winsorized Mean ( 12 / 36 )162174.7870370371002.6246904128161.750242725687
Winsorized Mean ( 13 / 36 )162184.416666667993.360333768277163.268464778965
Winsorized Mean ( 14 / 36 )162227.712962963981.6342397022165.262891616513
Winsorized Mean ( 15 / 36 )162315.074074074962.006727381785168.725508308901
Winsorized Mean ( 16 / 36 )162465.740740741919.01485307254176.782497255153
Winsorized Mean ( 17 / 36 )162931.351851852839.292406370557194.129424518963
Winsorized Mean ( 18 / 36 )162909.185185185836.426700718391194.768035316502
Winsorized Mean ( 19 / 36 )162993.981481481822.145760980758198.254359770756
Winsorized Mean ( 20 / 36 )163155.092592593793.281340580216205.671158826525
Winsorized Mean ( 21 / 36 )163287.314814815772.813227414375211.2894927551
Winsorized Mean ( 22 / 36 )163578.203703704719.574617470055227.326256002229
Winsorized Mean ( 23 / 36 )163485.138888889700.817711885338233.277692781311
Winsorized Mean ( 24 / 36 )163498.916666667695.950443583963234.928963942734
Winsorized Mean ( 25 / 36 )163585.027777778681.213846260374240.137555447239
Winsorized Mean ( 26 / 36 )163598.990740741673.114023651392243.047960660925
Winsorized Mean ( 27 / 36 )163697.490740741650.461402588516251.66364997109
Winsorized Mean ( 28 / 36 )163734.046296296643.035938312914254.626587008299
Winsorized Mean ( 29 / 36 )163923.083333333617.606023640478265.416911524096
Winsorized Mean ( 30 / 36 )163861.972222222602.038536434694272.178543906212
Winsorized Mean ( 31 / 36 )163979.083333333561.199015886352292.194174778347
Winsorized Mean ( 32 / 36 )163993.305555556552.868536952201296.622604823204
Winsorized Mean ( 33 / 36 )163953.583333333534.759180493763306.593302768452
Winsorized Mean ( 34 / 36 )163578.324074074488.203574676465335.061709006286
Winsorized Mean ( 35 / 36 )163846.657407407421.206798221231388.993383058718
Winsorized Mean ( 36 / 36 )163830.324074074384.356376917443426.245885102782
Trimmed Mean ( 1 / 36 )162167.5188679251123.21721312409144.377700922937
Trimmed Mean ( 2 / 36 )162230.6538461541094.33138949046148.246367968747
Trimmed Mean ( 3 / 36 )162282.9411764711074.21247174127151.071548176512
Trimmed Mean ( 4 / 36 )162352.211055.29032189912153.846014344023
Trimmed Mean ( 5 / 36 )162423.4591836731036.68339579226156.676049643435
Trimmed Mean ( 6 / 36 )162499.0104166671016.39187282445159.878305564465
Trimmed Mean ( 7 / 36 )162573.861702128996.919620949435163.076198206729
Trimmed Mean ( 8 / 36 )162647.608695652976.372797742323166.583511002912
Trimmed Mean ( 9 / 36 )162724.777777778954.706046723222170.444901167525
Trimmed Mean ( 10 / 36 )162812.238636364934.879495220468174.15318174025
Trimmed Mean ( 11 / 36 )162899.930232558915.634936541436177.909255896098
Trimmed Mean ( 12 / 36 )162991.297619048896.239091330844181.861401935747
Trimmed Mean ( 13 / 36 )163080.914634146875.593765278743186.251799751258
Trimmed Mean ( 14 / 36 )163174.0125853.081113141821191.27608147254
Trimmed Mean ( 15 / 36 )163267.602564103828.73293717905197.008704782332
Trimmed Mean ( 16 / 36 )163357.842105263803.477197801461203.313600625203
Trimmed Mean ( 17 / 36 )163439.216216216780.868687534286209.30435401668
Trimmed Mean ( 18 / 36 )163484.027777778766.962958660869213.157657656928
Trimmed Mean ( 19 / 36 )163533.3750.817202364503217.807076722529
Trimmed Mean ( 20 / 36 )163578.382352941733.796076108544222.920764608646
Trimmed Mean ( 21 / 36 )163613.015151515717.93792268944227.892983474965
Trimmed Mean ( 22 / 36 )163639.1875702.050097727892233.087621566609
Trimmed Mean ( 23 / 36 )163644.016129032690.955457659579236.837287143416
Trimmed Mean ( 24 / 36 )163656.45680.064871625233240.648292285544
Trimmed Mean ( 25 / 36 )163668.672413793667.29218615138245.272874177885
Trimmed Mean ( 26 / 36 )163675.125653.770160009239250.355759580227
Trimmed Mean ( 27 / 36 )163680.981481481638.193893879442256.475317378078
Trimmed Mean ( 28 / 36 )163679.711538462622.526181908676262.928237068868
Trimmed Mean ( 29 / 36 )163675.52603.997174773768270.987227814941
Trimmed Mean ( 30 / 36 )163656.3125585.117249082592279.698321586994
Trimmed Mean ( 31 / 36 )163640.217391304563.946871887875290.169563036143
Trimmed Mean ( 32 / 36 )163613.386363636544.886097855568300.270803398264
Trimmed Mean ( 33 / 36 )163582.857142857521.534871350114313.656605011636
Trimmed Mean ( 34 / 36 )163552.525494.811433893943330.535055976608
Trimmed Mean ( 35 / 36 )163550.368421053471.198054509282347.094744674568
Trimmed Mean ( 36 / 36 )163524.972222222456.190625162213358.45754647868
Median163408
Midrange159488.5
Midmean - Weighted Average at Xnp163520.163636364
Midmean - Weighted Average at X(n+1)p163680.981481481
Midmean - Empirical Distribution Function163520.163636364
Midmean - Empirical Distribution Function - Averaging163680.981481481
Midmean - Empirical Distribution Function - Interpolation163680.981481481
Midmean - Closest Observation163520.163636364
Midmean - True Basic - Statistics Graphics Toolkit163680.981481481
Midmean - MS Excel (old versions)163675.125
Number of observations108



Parameters (Session):
par1 = 0.1 ; par2 = 0.99 ; par3 = 0.1 ;
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')