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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSat, 13 Aug 2016 11:07:12 +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/2016/Aug/13/t1471082851aigfh5qnqe4g70h.htm/, Retrieved Wed, 01 May 2024 21:12:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296500, Retrieved Wed, 01 May 2024 21:12:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact164
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2016-08-13 09:35:09] [74be16979710d4c4e7c6647856088456]
- RMP     [Central Tendency] [] [2016-08-13 10:07:12] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
29312
29336
29357
29380
29402
29426
29448
29471
29495
29517
29540
29563
29586
29609
29631
29654
29677
29700
29723
29746
29769
29792
29815
29837
29861
29884
29905
29928
29951
29974
29996
30020
30043
30065
30089
30111
30134
30158
30179
30202
30224
30248
30270
30293
30317
30339
30362
30385
30408
30431
30452
30476
30498
30521
30544
30567
30590
30613
30636
30659
30682
30705
30727
30750
30773
30796
30818
30842
30865
30887
30911
30933
30956
30980
31001
31024
31046
31070
31092
31115
31139
31161
31184
31207
31230
31253
31274
31298
31320
31343
31366
31389
31412
31435
31458
31481
31504
31527
31548
31571
31594
31617
31640
31663
31686
31709
31732
31754




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296500&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]2 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=296500&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296500&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean30533.21296296368.7976450606584443.811891177991
Geometric Mean30524.9166764842
Harmonic Mean30516.6190009664
Quadratic Mean30541.5051569172
Winsorized Mean ( 1 / 36 )30533.231481481568.7276287356377444.264294333916
Winsorized Mean ( 2 / 36 )30533.194444444468.5959803862652445.116379597048
Winsorized Mean ( 3 / 36 )30533.194444444468.392952562757446.437729332234
Winsorized Mean ( 4 / 36 )30533.157407407468.1324278100116448.144274156054
Winsorized Mean ( 5 / 36 )30533.203703703767.7976850043214450.357614743889
Winsorized Mean ( 6 / 36 )30533.148148148167.4190126240946452.886314404967
Winsorized Mean ( 7 / 36 )30533.148148148166.9740729514096455.895047181919
Winsorized Mean ( 8 / 36 )30533.222222222266.4621243456716459.407858578488
Winsorized Mean ( 9 / 36 )30533.138888888965.9184813632935463.195423459667
Winsorized Mean ( 10 / 36 )30533.324074074165.3356854069161467.329972646801
Winsorized Mean ( 11 / 36 )30533.324074074164.6742186401642472.109670840494
Winsorized Mean ( 12 / 36 )30533.324074074163.9619941517169477.366668738462
Winsorized Mean ( 13 / 36 )30533.324074074163.2001932095224483.120739407385
Winsorized Mean ( 14 / 36 )30533.194444444462.4074426569833489.255658371828
Winsorized Mean ( 15 / 36 )30533.194444444461.5495470256908496.075047176218
Winsorized Mean ( 16 / 36 )30533.194444444460.6452375318524503.47225416353
Winsorized Mean ( 17 / 36 )30533.194444444459.6954722265419511.482584953382
Winsorized Mean ( 18 / 36 )30533.194444444458.7011640678174520.14631957161
Winsorized Mean ( 19 / 36 )30533.194444444457.6631843352386529.509335921036
Winsorized Mean ( 20 / 36 )30533.379629629656.6057361593874539.40433781579
Winsorized Mean ( 21 / 36 )30533.185185185255.4583128409229550.561018196981
Winsorized Mean ( 22 / 36 )30533.592592592654.3445207554863561.852274490986
Winsorized Mean ( 23 / 36 )30533.379629629653.1652916640926574.310394505963
Winsorized Mean ( 24 / 36 )30533.601851851951.8928722165563588.396836552635
Winsorized Mean ( 25 / 36 )30533.601851851950.6084114390006603.330572599669
Winsorized Mean ( 26 / 36 )30533.120370370449.3426075969932618.798273081761
Winsorized Mean ( 27 / 36 )30533.370370370448.0104418386656635.973534111075
Winsorized Mean ( 28 / 36 )30533.111111111146.5807868242405655.487233960199
Winsorized Mean ( 29 / 36 )30533.111111111145.1448235574672676.336924259853
Winsorized Mean ( 30 / 36 )30533.111111111143.7362891205804698.118466953877
Winsorized Mean ( 31 / 36 )30533.111111111142.1623112960753724.180201998397
Winsorized Mean ( 32 / 36 )30533.407407407440.6523518824572751.085878024774
Winsorized Mean ( 33 / 36 )30533.101851851939.108081147564780.736383783272
Winsorized Mean ( 34 / 36 )30534.046296296337.529972755279813.590952900474
Winsorized Mean ( 35 / 36 )30533.398148148135.8826472228971850.923789387102
Winsorized Mean ( 36 / 36 )30533.398148148134.2019002279043892.7398169309
Trimmed Mean ( 1 / 36 )30533.216981132168.16435795463447.935224468114
Trimmed Mean ( 2 / 36 )30533.201923076967.5257514287208452.171227673154
Trimmed Mean ( 3 / 36 )30533.205882352966.8783123735625456.54868968289
Trimmed Mean ( 4 / 36 )30533.2166.2250727565939461.052117107109
Trimmed Mean ( 5 / 36 )30533.224489795965.5640893063181465.70042858589
Trimmed Mean ( 6 / 36 )30533.229166666764.8987630636029470.474747519349
Trimmed Mean ( 7 / 36 )30533.244680851164.2253038603393475.408333563464
Trimmed Mean ( 8 / 36 )30533.260869565263.5453381632756480.495686262806
Trimmed Mean ( 9 / 36 )30533.266666666762.8607755569439485.728443471198
Trimmed Mean ( 10 / 36 )30533.284090909162.1674537550856491.145804542643
Trimmed Mean ( 11 / 36 )30533.279069767461.4627502801556496.776973542391
Trimmed Mean ( 12 / 36 )30533.273809523860.7504992936388502.601199406454
Trimmed Mean ( 13 / 36 )30533.268292682960.0304952333278508.629292062402
Trimmed Mean ( 14 / 36 )30533.262559.3025277060426514.872867668486
Trimmed Mean ( 15 / 36 )30533.269230769258.5638184961965521.367458864593
Trimmed Mean ( 16 / 36 )30533.276315789557.8164385010165528.107180369691
Trimmed Mean ( 17 / 36 )30533.283783783857.0601328733207535.107127275199
Trimmed Mean ( 18 / 36 )30533.291666666756.2946412582021542.383626296188
Trimmed Mean ( 19 / 36 )30533.355.5196991880324549.954348574382
Trimmed Mean ( 20 / 36 )30533.308823529454.7350400396711557.838430398504
Trimmed Mean ( 21 / 36 )30533.30303030353.9370952340128566.090978719386
Trimmed Mean ( 22 / 36 )30533.312553.131943407128574.669596894582
Trimmed Mean ( 23 / 36 )30533.290322580652.3089982638141583.710094553707
Trimmed Mean ( 24 / 36 )30533.283333333351.4704736359483593.219396994398
Trimmed Mean ( 25 / 36 )30533.258620689750.6232873032707603.146501288488
Trimmed Mean ( 26 / 36 )30533.232142857149.7635382028043613.566342859771
Trimmed Mean ( 27 / 36 )30533.240740740748.8818863041814624.633029722687
Trimmed Mean ( 28 / 36 )30533.230769230847.9807702131261636.363914826815
Trimmed Mean ( 29 / 36 )30533.2447.0686217242486648.696283882687
Trimmed Mean ( 30 / 36 )30533.2546.1405067727721661.74500749129
Trimmed Mean ( 31 / 36 )30533.260869565245.1843506189119675.748582226731
Trimmed Mean ( 32 / 36 )30533.272727272744.2211595869912690.467482364594
Trimmed Mean ( 33 / 36 )30533.261904761943.2334647387244706.241382440328
Trimmed Mean ( 34 / 36 )30533.27542.2188891298548723.21360484136
Trimmed Mean ( 35 / 36 )30533.210526315841.1745608789839741.555219400054
Trimmed Mean ( 36 / 36 )30533.194444444440.1054328632657761.323149124046
Median30532.5
Midrange30533
Midmean - Weighted Average at Xnp30521.8181818182
Midmean - Weighted Average at X(n+1)p30533.2407407407
Midmean - Empirical Distribution Function30521.8181818182
Midmean - Empirical Distribution Function - Averaging30533.2407407407
Midmean - Empirical Distribution Function - Interpolation30533.2407407407
Midmean - Closest Observation30521.8181818182
Midmean - True Basic - Statistics Graphics Toolkit30533.2407407407
Midmean - MS Excel (old versions)30533.2321428571
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 30533.212962963 & 68.7976450606584 & 443.811891177991 \tabularnewline
Geometric Mean & 30524.9166764842 &  &  \tabularnewline
Harmonic Mean & 30516.6190009664 &  &  \tabularnewline
Quadratic Mean & 30541.5051569172 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 30533.2314814815 & 68.7276287356377 & 444.264294333916 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 30533.1944444444 & 68.5959803862652 & 445.116379597048 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 30533.1944444444 & 68.392952562757 & 446.437729332234 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 30533.1574074074 & 68.1324278100116 & 448.144274156054 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 30533.2037037037 & 67.7976850043214 & 450.357614743889 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 30533.1481481481 & 67.4190126240946 & 452.886314404967 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 30533.1481481481 & 66.9740729514096 & 455.895047181919 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 30533.2222222222 & 66.4621243456716 & 459.407858578488 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 30533.1388888889 & 65.9184813632935 & 463.195423459667 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 30533.3240740741 & 65.3356854069161 & 467.329972646801 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 30533.3240740741 & 64.6742186401642 & 472.109670840494 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 30533.3240740741 & 63.9619941517169 & 477.366668738462 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 30533.3240740741 & 63.2001932095224 & 483.120739407385 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 30533.1944444444 & 62.4074426569833 & 489.255658371828 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 30533.1944444444 & 61.5495470256908 & 496.075047176218 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 30533.1944444444 & 60.6452375318524 & 503.47225416353 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 30533.1944444444 & 59.6954722265419 & 511.482584953382 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 30533.1944444444 & 58.7011640678174 & 520.14631957161 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 30533.1944444444 & 57.6631843352386 & 529.509335921036 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 30533.3796296296 & 56.6057361593874 & 539.40433781579 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 30533.1851851852 & 55.4583128409229 & 550.561018196981 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 30533.5925925926 & 54.3445207554863 & 561.852274490986 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 30533.3796296296 & 53.1652916640926 & 574.310394505963 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 30533.6018518519 & 51.8928722165563 & 588.396836552635 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 30533.6018518519 & 50.6084114390006 & 603.330572599669 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 30533.1203703704 & 49.3426075969932 & 618.798273081761 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 30533.3703703704 & 48.0104418386656 & 635.973534111075 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 30533.1111111111 & 46.5807868242405 & 655.487233960199 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 30533.1111111111 & 45.1448235574672 & 676.336924259853 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 30533.1111111111 & 43.7362891205804 & 698.118466953877 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 30533.1111111111 & 42.1623112960753 & 724.180201998397 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 30533.4074074074 & 40.6523518824572 & 751.085878024774 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 30533.1018518519 & 39.108081147564 & 780.736383783272 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 30534.0462962963 & 37.529972755279 & 813.590952900474 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 30533.3981481481 & 35.8826472228971 & 850.923789387102 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 30533.3981481481 & 34.2019002279043 & 892.7398169309 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 30533.2169811321 & 68.16435795463 & 447.935224468114 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 30533.2019230769 & 67.5257514287208 & 452.171227673154 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 30533.2058823529 & 66.8783123735625 & 456.54868968289 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 30533.21 & 66.2250727565939 & 461.052117107109 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 30533.2244897959 & 65.5640893063181 & 465.70042858589 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 30533.2291666667 & 64.8987630636029 & 470.474747519349 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 30533.2446808511 & 64.2253038603393 & 475.408333563464 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 30533.2608695652 & 63.5453381632756 & 480.495686262806 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 30533.2666666667 & 62.8607755569439 & 485.728443471198 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 30533.2840909091 & 62.1674537550856 & 491.145804542643 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 30533.2790697674 & 61.4627502801556 & 496.776973542391 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 30533.2738095238 & 60.7504992936388 & 502.601199406454 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 30533.2682926829 & 60.0304952333278 & 508.629292062402 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 30533.2625 & 59.3025277060426 & 514.872867668486 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 30533.2692307692 & 58.5638184961965 & 521.367458864593 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 30533.2763157895 & 57.8164385010165 & 528.107180369691 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 30533.2837837838 & 57.0601328733207 & 535.107127275199 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 30533.2916666667 & 56.2946412582021 & 542.383626296188 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 30533.3 & 55.5196991880324 & 549.954348574382 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 30533.3088235294 & 54.7350400396711 & 557.838430398504 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 30533.303030303 & 53.9370952340128 & 566.090978719386 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 30533.3125 & 53.131943407128 & 574.669596894582 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 30533.2903225806 & 52.3089982638141 & 583.710094553707 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 30533.2833333333 & 51.4704736359483 & 593.219396994398 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 30533.2586206897 & 50.6232873032707 & 603.146501288488 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 30533.2321428571 & 49.7635382028043 & 613.566342859771 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 30533.2407407407 & 48.8818863041814 & 624.633029722687 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 30533.2307692308 & 47.9807702131261 & 636.363914826815 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 30533.24 & 47.0686217242486 & 648.696283882687 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 30533.25 & 46.1405067727721 & 661.74500749129 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 30533.2608695652 & 45.1843506189119 & 675.748582226731 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 30533.2727272727 & 44.2211595869912 & 690.467482364594 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 30533.2619047619 & 43.2334647387244 & 706.241382440328 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 30533.275 & 42.2188891298548 & 723.21360484136 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 30533.2105263158 & 41.1745608789839 & 741.555219400054 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 30533.1944444444 & 40.1054328632657 & 761.323149124046 \tabularnewline
Median & 30532.5 &  &  \tabularnewline
Midrange & 30533 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 30521.8181818182 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 30533.2407407407 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 30521.8181818182 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 30533.2407407407 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 30533.2407407407 &  &  \tabularnewline
Midmean - Closest Observation & 30521.8181818182 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 30533.2407407407 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 30533.2321428571 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296500&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]30533.212962963[/C][C]68.7976450606584[/C][C]443.811891177991[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]30524.9166764842[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]30516.6190009664[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]30541.5051569172[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]30533.2314814815[/C][C]68.7276287356377[/C][C]444.264294333916[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]30533.1944444444[/C][C]68.5959803862652[/C][C]445.116379597048[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]30533.1944444444[/C][C]68.392952562757[/C][C]446.437729332234[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]30533.1574074074[/C][C]68.1324278100116[/C][C]448.144274156054[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]30533.2037037037[/C][C]67.7976850043214[/C][C]450.357614743889[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]30533.1481481481[/C][C]67.4190126240946[/C][C]452.886314404967[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]30533.1481481481[/C][C]66.9740729514096[/C][C]455.895047181919[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]30533.2222222222[/C][C]66.4621243456716[/C][C]459.407858578488[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]30533.1388888889[/C][C]65.9184813632935[/C][C]463.195423459667[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]30533.3240740741[/C][C]65.3356854069161[/C][C]467.329972646801[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]30533.3240740741[/C][C]64.6742186401642[/C][C]472.109670840494[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]30533.3240740741[/C][C]63.9619941517169[/C][C]477.366668738462[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]30533.3240740741[/C][C]63.2001932095224[/C][C]483.120739407385[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]30533.1944444444[/C][C]62.4074426569833[/C][C]489.255658371828[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]30533.1944444444[/C][C]61.5495470256908[/C][C]496.075047176218[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]30533.1944444444[/C][C]60.6452375318524[/C][C]503.47225416353[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]30533.1944444444[/C][C]59.6954722265419[/C][C]511.482584953382[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]30533.1944444444[/C][C]58.7011640678174[/C][C]520.14631957161[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]30533.1944444444[/C][C]57.6631843352386[/C][C]529.509335921036[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]30533.3796296296[/C][C]56.6057361593874[/C][C]539.40433781579[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]30533.1851851852[/C][C]55.4583128409229[/C][C]550.561018196981[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]30533.5925925926[/C][C]54.3445207554863[/C][C]561.852274490986[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]30533.3796296296[/C][C]53.1652916640926[/C][C]574.310394505963[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]30533.6018518519[/C][C]51.8928722165563[/C][C]588.396836552635[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]30533.6018518519[/C][C]50.6084114390006[/C][C]603.330572599669[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]30533.1203703704[/C][C]49.3426075969932[/C][C]618.798273081761[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]30533.3703703704[/C][C]48.0104418386656[/C][C]635.973534111075[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]30533.1111111111[/C][C]46.5807868242405[/C][C]655.487233960199[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]30533.1111111111[/C][C]45.1448235574672[/C][C]676.336924259853[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]30533.1111111111[/C][C]43.7362891205804[/C][C]698.118466953877[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]30533.1111111111[/C][C]42.1623112960753[/C][C]724.180201998397[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]30533.4074074074[/C][C]40.6523518824572[/C][C]751.085878024774[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]30533.1018518519[/C][C]39.108081147564[/C][C]780.736383783272[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]30534.0462962963[/C][C]37.529972755279[/C][C]813.590952900474[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]30533.3981481481[/C][C]35.8826472228971[/C][C]850.923789387102[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]30533.3981481481[/C][C]34.2019002279043[/C][C]892.7398169309[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]30533.2169811321[/C][C]68.16435795463[/C][C]447.935224468114[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]30533.2019230769[/C][C]67.5257514287208[/C][C]452.171227673154[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]30533.2058823529[/C][C]66.8783123735625[/C][C]456.54868968289[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]30533.21[/C][C]66.2250727565939[/C][C]461.052117107109[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]30533.2244897959[/C][C]65.5640893063181[/C][C]465.70042858589[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]30533.2291666667[/C][C]64.8987630636029[/C][C]470.474747519349[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]30533.2446808511[/C][C]64.2253038603393[/C][C]475.408333563464[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]30533.2608695652[/C][C]63.5453381632756[/C][C]480.495686262806[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]30533.2666666667[/C][C]62.8607755569439[/C][C]485.728443471198[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]30533.2840909091[/C][C]62.1674537550856[/C][C]491.145804542643[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]30533.2790697674[/C][C]61.4627502801556[/C][C]496.776973542391[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]30533.2738095238[/C][C]60.7504992936388[/C][C]502.601199406454[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]30533.2682926829[/C][C]60.0304952333278[/C][C]508.629292062402[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]30533.2625[/C][C]59.3025277060426[/C][C]514.872867668486[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]30533.2692307692[/C][C]58.5638184961965[/C][C]521.367458864593[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]30533.2763157895[/C][C]57.8164385010165[/C][C]528.107180369691[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]30533.2837837838[/C][C]57.0601328733207[/C][C]535.107127275199[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]30533.2916666667[/C][C]56.2946412582021[/C][C]542.383626296188[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]30533.3[/C][C]55.5196991880324[/C][C]549.954348574382[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]30533.3088235294[/C][C]54.7350400396711[/C][C]557.838430398504[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]30533.303030303[/C][C]53.9370952340128[/C][C]566.090978719386[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]30533.3125[/C][C]53.131943407128[/C][C]574.669596894582[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]30533.2903225806[/C][C]52.3089982638141[/C][C]583.710094553707[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]30533.2833333333[/C][C]51.4704736359483[/C][C]593.219396994398[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]30533.2586206897[/C][C]50.6232873032707[/C][C]603.146501288488[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]30533.2321428571[/C][C]49.7635382028043[/C][C]613.566342859771[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]30533.2407407407[/C][C]48.8818863041814[/C][C]624.633029722687[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]30533.2307692308[/C][C]47.9807702131261[/C][C]636.363914826815[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]30533.24[/C][C]47.0686217242486[/C][C]648.696283882687[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]30533.25[/C][C]46.1405067727721[/C][C]661.74500749129[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]30533.2608695652[/C][C]45.1843506189119[/C][C]675.748582226731[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]30533.2727272727[/C][C]44.2211595869912[/C][C]690.467482364594[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]30533.2619047619[/C][C]43.2334647387244[/C][C]706.241382440328[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]30533.275[/C][C]42.2188891298548[/C][C]723.21360484136[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]30533.2105263158[/C][C]41.1745608789839[/C][C]741.555219400054[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]30533.1944444444[/C][C]40.1054328632657[/C][C]761.323149124046[/C][/ROW]
[ROW][C]Median[/C][C]30532.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]30533[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]30521.8181818182[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]30533.2407407407[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]30521.8181818182[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]30533.2407407407[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]30533.2407407407[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]30521.8181818182[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]30533.2407407407[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]30533.2321428571[/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=296500&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296500&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 Mean30533.21296296368.7976450606584443.811891177991
Geometric Mean30524.9166764842
Harmonic Mean30516.6190009664
Quadratic Mean30541.5051569172
Winsorized Mean ( 1 / 36 )30533.231481481568.7276287356377444.264294333916
Winsorized Mean ( 2 / 36 )30533.194444444468.5959803862652445.116379597048
Winsorized Mean ( 3 / 36 )30533.194444444468.392952562757446.437729332234
Winsorized Mean ( 4 / 36 )30533.157407407468.1324278100116448.144274156054
Winsorized Mean ( 5 / 36 )30533.203703703767.7976850043214450.357614743889
Winsorized Mean ( 6 / 36 )30533.148148148167.4190126240946452.886314404967
Winsorized Mean ( 7 / 36 )30533.148148148166.9740729514096455.895047181919
Winsorized Mean ( 8 / 36 )30533.222222222266.4621243456716459.407858578488
Winsorized Mean ( 9 / 36 )30533.138888888965.9184813632935463.195423459667
Winsorized Mean ( 10 / 36 )30533.324074074165.3356854069161467.329972646801
Winsorized Mean ( 11 / 36 )30533.324074074164.6742186401642472.109670840494
Winsorized Mean ( 12 / 36 )30533.324074074163.9619941517169477.366668738462
Winsorized Mean ( 13 / 36 )30533.324074074163.2001932095224483.120739407385
Winsorized Mean ( 14 / 36 )30533.194444444462.4074426569833489.255658371828
Winsorized Mean ( 15 / 36 )30533.194444444461.5495470256908496.075047176218
Winsorized Mean ( 16 / 36 )30533.194444444460.6452375318524503.47225416353
Winsorized Mean ( 17 / 36 )30533.194444444459.6954722265419511.482584953382
Winsorized Mean ( 18 / 36 )30533.194444444458.7011640678174520.14631957161
Winsorized Mean ( 19 / 36 )30533.194444444457.6631843352386529.509335921036
Winsorized Mean ( 20 / 36 )30533.379629629656.6057361593874539.40433781579
Winsorized Mean ( 21 / 36 )30533.185185185255.4583128409229550.561018196981
Winsorized Mean ( 22 / 36 )30533.592592592654.3445207554863561.852274490986
Winsorized Mean ( 23 / 36 )30533.379629629653.1652916640926574.310394505963
Winsorized Mean ( 24 / 36 )30533.601851851951.8928722165563588.396836552635
Winsorized Mean ( 25 / 36 )30533.601851851950.6084114390006603.330572599669
Winsorized Mean ( 26 / 36 )30533.120370370449.3426075969932618.798273081761
Winsorized Mean ( 27 / 36 )30533.370370370448.0104418386656635.973534111075
Winsorized Mean ( 28 / 36 )30533.111111111146.5807868242405655.487233960199
Winsorized Mean ( 29 / 36 )30533.111111111145.1448235574672676.336924259853
Winsorized Mean ( 30 / 36 )30533.111111111143.7362891205804698.118466953877
Winsorized Mean ( 31 / 36 )30533.111111111142.1623112960753724.180201998397
Winsorized Mean ( 32 / 36 )30533.407407407440.6523518824572751.085878024774
Winsorized Mean ( 33 / 36 )30533.101851851939.108081147564780.736383783272
Winsorized Mean ( 34 / 36 )30534.046296296337.529972755279813.590952900474
Winsorized Mean ( 35 / 36 )30533.398148148135.8826472228971850.923789387102
Winsorized Mean ( 36 / 36 )30533.398148148134.2019002279043892.7398169309
Trimmed Mean ( 1 / 36 )30533.216981132168.16435795463447.935224468114
Trimmed Mean ( 2 / 36 )30533.201923076967.5257514287208452.171227673154
Trimmed Mean ( 3 / 36 )30533.205882352966.8783123735625456.54868968289
Trimmed Mean ( 4 / 36 )30533.2166.2250727565939461.052117107109
Trimmed Mean ( 5 / 36 )30533.224489795965.5640893063181465.70042858589
Trimmed Mean ( 6 / 36 )30533.229166666764.8987630636029470.474747519349
Trimmed Mean ( 7 / 36 )30533.244680851164.2253038603393475.408333563464
Trimmed Mean ( 8 / 36 )30533.260869565263.5453381632756480.495686262806
Trimmed Mean ( 9 / 36 )30533.266666666762.8607755569439485.728443471198
Trimmed Mean ( 10 / 36 )30533.284090909162.1674537550856491.145804542643
Trimmed Mean ( 11 / 36 )30533.279069767461.4627502801556496.776973542391
Trimmed Mean ( 12 / 36 )30533.273809523860.7504992936388502.601199406454
Trimmed Mean ( 13 / 36 )30533.268292682960.0304952333278508.629292062402
Trimmed Mean ( 14 / 36 )30533.262559.3025277060426514.872867668486
Trimmed Mean ( 15 / 36 )30533.269230769258.5638184961965521.367458864593
Trimmed Mean ( 16 / 36 )30533.276315789557.8164385010165528.107180369691
Trimmed Mean ( 17 / 36 )30533.283783783857.0601328733207535.107127275199
Trimmed Mean ( 18 / 36 )30533.291666666756.2946412582021542.383626296188
Trimmed Mean ( 19 / 36 )30533.355.5196991880324549.954348574382
Trimmed Mean ( 20 / 36 )30533.308823529454.7350400396711557.838430398504
Trimmed Mean ( 21 / 36 )30533.30303030353.9370952340128566.090978719386
Trimmed Mean ( 22 / 36 )30533.312553.131943407128574.669596894582
Trimmed Mean ( 23 / 36 )30533.290322580652.3089982638141583.710094553707
Trimmed Mean ( 24 / 36 )30533.283333333351.4704736359483593.219396994398
Trimmed Mean ( 25 / 36 )30533.258620689750.6232873032707603.146501288488
Trimmed Mean ( 26 / 36 )30533.232142857149.7635382028043613.566342859771
Trimmed Mean ( 27 / 36 )30533.240740740748.8818863041814624.633029722687
Trimmed Mean ( 28 / 36 )30533.230769230847.9807702131261636.363914826815
Trimmed Mean ( 29 / 36 )30533.2447.0686217242486648.696283882687
Trimmed Mean ( 30 / 36 )30533.2546.1405067727721661.74500749129
Trimmed Mean ( 31 / 36 )30533.260869565245.1843506189119675.748582226731
Trimmed Mean ( 32 / 36 )30533.272727272744.2211595869912690.467482364594
Trimmed Mean ( 33 / 36 )30533.261904761943.2334647387244706.241382440328
Trimmed Mean ( 34 / 36 )30533.27542.2188891298548723.21360484136
Trimmed Mean ( 35 / 36 )30533.210526315841.1745608789839741.555219400054
Trimmed Mean ( 36 / 36 )30533.194444444440.1054328632657761.323149124046
Median30532.5
Midrange30533
Midmean - Weighted Average at Xnp30521.8181818182
Midmean - Weighted Average at X(n+1)p30533.2407407407
Midmean - Empirical Distribution Function30521.8181818182
Midmean - Empirical Distribution Function - Averaging30533.2407407407
Midmean - Empirical Distribution Function - Interpolation30533.2407407407
Midmean - Closest Observation30521.8181818182
Midmean - True Basic - Statistics Graphics Toolkit30533.2407407407
Midmean - MS Excel (old versions)30533.2321428571
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')