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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, 12 Aug 2017 16:18:29 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Aug/12/t1502547532qmy2kzrx5hrqgux.htm/, Retrieved Fri, 10 May 2024 06:48:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307129, Retrieved Fri, 10 May 2024 06:48:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact140
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2017-08-12 14:18:29] [270a72b021b4bbf70c885af1fd2608d6] [Current]
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Dataseries X:
38327240.00
38147255.00
37964735.00
37587020.00
41323610.00
41125880.00
38327240.00
36466550.00
36646535.00
36646535.00
36846800.00
37206770.00
37767005.00
37767005.00
37407035.00
36466550.00
41323610.00
42063830.00
40945895.00
38327240.00
39447710.00
37767005.00
38524970.00
38887475.00
39265190.00
38327240.00
38524970.00
37206770.00
41323610.00
42624065.00
41506130.00
39447710.00
41686115.00
39265190.00
41506130.00
41323610.00
41883845.00
39825425.00
42063830.00
41883845.00
45242720.00
44484755.00
41506130.00
40005410.00
42063830.00
39265190.00
41323610.00
41686115.00
42444080.00
40765910.00
41686115.00
42246350.00
44304770.00
42624065.00
40385660.00
37964735.00
40205675.00
34045625.00
37026785.00
38704955.00
40385660.00
37964735.00
37964735.00
37964735.00
39265190.00
37407035.00
34968365.00
32927690.00
34408130.00
28628330.00
32169725.00
34228145.00
34605860.00
32547440.00
32727425.00
32169725.00
34045625.00
32727425.00
30129050.00
28250615.00
31426970.00
24529235.00
29008580.00
31049255.00
31049255.00
28628330.00
26389925.00
26209940.00
28250615.00
26389925.00
22851065.00
20412395.00
23031050.00
16873535.00
22470815.00
25449440.00
26389925.00
24331505.00
21730595.00
23591285.00
24331505.00
23771270.00
18171455.00
15573080.00
17431235.00
11833955.00
17613755.00
19672175.00
21350345.00
18551705.00
15933050.00
17431235.00
18171455.00
16691015.00
11093735.00
8655065.00
10893470.00
4735955.00
11453705.00
15573080.00




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307129&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=307129&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307129&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean3252870087769037.0617
Geometric Mean30545000
Harmonic Mean27578800
Quadratic Mean33908500
Winsorized Mean ( 1 / 40 )3255500086881837.4705
Winsorized Mean ( 2 / 40 )3258930086020637.8855
Winsorized Mean ( 3 / 40 )3255230085466138.088
Winsorized Mean ( 4 / 40 )3256430085214638.2145
Winsorized Mean ( 5 / 40 )3257260084813038.4052
Winsorized Mean ( 6 / 40 )3274970081126440.3688
Winsorized Mean ( 7 / 40 )3273910081022540.4074
Winsorized Mean ( 8 / 40 )3276310080598340.6498
Winsorized Mean ( 9 / 40 )3281990079615641.223
Winsorized Mean ( 10 / 40 )3282010079212241.4332
Winsorized Mean ( 11 / 40 )3287120078356441.9509
Winsorized Mean ( 12 / 40 )3285150078167042.0273
Winsorized Mean ( 13 / 40 )3287120077840242.2291
Winsorized Mean ( 14 / 40 )3293630076778642.8978
Winsorized Mean ( 15 / 40 )3291380076564842.9882
Winsorized Mean ( 16 / 40 )3296450075749343.5179
Winsorized Mean ( 17 / 40 )3312320073254945.2164
Winsorized Mean ( 18 / 40 )3320690071298246.5747
Winsorized Mean ( 19 / 40 )3335540069093748.2756
Winsorized Mean ( 20 / 40 )3341880068174549.0195
Winsorized Mean ( 21 / 40 )3354830066332050.5763
Winsorized Mean ( 22 / 40 )3361800065360351.4349
Winsorized Mean ( 23 / 40 )3361460064510652.1072
Winsorized Mean ( 24 / 40 )3369070062627553.7954
Winsorized Mean ( 25 / 40 )3369070061757354.5533
Winsorized Mean ( 26 / 40 )3372970059345256.8364
Winsorized Mean ( 27 / 40 )3372970059345256.8364
Winsorized Mean ( 28 / 40 )3373380058338757.8241
Winsorized Mean ( 29 / 40 )3390780054974661.6791
Winsorized Mean ( 30 / 40 )3405290052123765.3311
Winsorized Mean ( 31 / 40 )3400190050640967.143
Winsorized Mean ( 32 / 40 )3400190050640967.143
Winsorized Mean ( 33 / 40 )3395170050190867.6451
Winsorized Mean ( 34 / 40 )3447890043682978.9299
Winsorized Mean ( 35 / 40 )3447890043682978.9299
Winsorized Mean ( 36 / 40 )3459220042333281.7141
Winsorized Mean ( 37 / 40 )3447570041269783.5376
Winsorized Mean ( 38 / 40 )3453830039324387.8294
Winsorized Mean ( 39 / 40 )34844000345591100.824
Winsorized Mean ( 40 / 40 )35150700310979113.033
Trimmed Mean ( 1 / 40 )3265640085380938.2479
Trimmed Mean ( 2 / 40 )3276140083707139.1381
Trimmed Mean ( 3 / 40 )3285200082344539.8957
Trimmed Mean ( 4 / 40 )3295900081039540.6702
Trimmed Mean ( 5 / 40 )3306660079654341.5126
Trimmed Mean ( 6 / 40 )3317640078203342.4233
Trimmed Mean ( 7 / 40 )3325690077439642.9456
Trimmed Mean ( 8 / 40 )3334220076588943.5341
Trimmed Mean ( 9 / 40 )3342740075700444.1575
Trimmed Mean ( 10 / 40 )3350840074861944.7603
Trimmed Mean ( 11 / 40 )3359270073966045.4164
Trimmed Mean ( 12 / 40 )3367470073075646.082
Trimmed Mean ( 13 / 40 )3376220072075546.8429
Trimmed Mean ( 14 / 40 )3385160070972647.6968
Trimmed Mean ( 15 / 40 )3393880069859348.5817
Trimmed Mean ( 16 / 40 )3403200068596449.612
Trimmed Mean ( 17 / 40 )3412510067252750.7416
Trimmed Mean ( 18 / 40 )3420930066057451.7872
Trimmed Mean ( 19 / 40 )3429080064936752.8065
Trimmed Mean ( 20 / 40 )3436460063935153.7492
Trimmed Mean ( 21 / 40 )3443740062883454.7638
Trimmed Mean ( 22 / 40 )3450420061899955.742
Trimmed Mean ( 23 / 40 )3456950060868056.7943
Trimmed Mean ( 24 / 40 )3463870059748557.9742
Trimmed Mean ( 25 / 40 )3470650058673759.1516
Trimmed Mean ( 26 / 40 )3477820057496360.4876
Trimmed Mean ( 27 / 40 )3485150056411861.7805
Trimmed Mean ( 28 / 40 )3492940055086563.4083
Trimmed Mean ( 29 / 40 )3501200053613365.3048
Trimmed Mean ( 30 / 40 )3508820052356067.0185
Trimmed Mean ( 31 / 40 )3515960051263768.5857
Trimmed Mean ( 32 / 40 )3523960050102370.3354
Trimmed Mean ( 33 / 40 )3532560048626472.6468
Trimmed Mean ( 34 / 40 )3542160046801275.6853
Trimmed Mean ( 35 / 40 )3548820045824277.4442
Trimmed Mean ( 36 / 40 )3556030044540979.8373
Trimmed Mean ( 37 / 40 )3563040043158182.558
Trimmed Mean ( 38 / 40 )3571560041484586.0938
Trimmed Mean ( 39 / 40 )3580410039696690.1942
Trimmed Mean ( 40 / 40 )3587790038524893.1294
Median36936800
Midrange24989300
Midmean - Weighted Average at Xnp34930200
Midmean - Weighted Average at X(n+1)p35088200
Midmean - Empirical Distribution Function34930200
Midmean - Empirical Distribution Function - Averaging35088200
Midmean - Empirical Distribution Function - Interpolation35088200
Midmean - Closest Observation34930200
Midmean - True Basic - Statistics Graphics Toolkit35088200
Midmean - MS Excel (old versions)35012000
Number of observations120

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 32528700 & 877690 & 37.0617 \tabularnewline
Geometric Mean & 30545000 &  &  \tabularnewline
Harmonic Mean & 27578800 &  &  \tabularnewline
Quadratic Mean & 33908500 &  &  \tabularnewline
Winsorized Mean ( 1 / 40 ) & 32555000 & 868818 & 37.4705 \tabularnewline
Winsorized Mean ( 2 / 40 ) & 32589300 & 860206 & 37.8855 \tabularnewline
Winsorized Mean ( 3 / 40 ) & 32552300 & 854661 & 38.088 \tabularnewline
Winsorized Mean ( 4 / 40 ) & 32564300 & 852146 & 38.2145 \tabularnewline
Winsorized Mean ( 5 / 40 ) & 32572600 & 848130 & 38.4052 \tabularnewline
Winsorized Mean ( 6 / 40 ) & 32749700 & 811264 & 40.3688 \tabularnewline
Winsorized Mean ( 7 / 40 ) & 32739100 & 810225 & 40.4074 \tabularnewline
Winsorized Mean ( 8 / 40 ) & 32763100 & 805983 & 40.6498 \tabularnewline
Winsorized Mean ( 9 / 40 ) & 32819900 & 796156 & 41.223 \tabularnewline
Winsorized Mean ( 10 / 40 ) & 32820100 & 792122 & 41.4332 \tabularnewline
Winsorized Mean ( 11 / 40 ) & 32871200 & 783564 & 41.9509 \tabularnewline
Winsorized Mean ( 12 / 40 ) & 32851500 & 781670 & 42.0273 \tabularnewline
Winsorized Mean ( 13 / 40 ) & 32871200 & 778402 & 42.2291 \tabularnewline
Winsorized Mean ( 14 / 40 ) & 32936300 & 767786 & 42.8978 \tabularnewline
Winsorized Mean ( 15 / 40 ) & 32913800 & 765648 & 42.9882 \tabularnewline
Winsorized Mean ( 16 / 40 ) & 32964500 & 757493 & 43.5179 \tabularnewline
Winsorized Mean ( 17 / 40 ) & 33123200 & 732549 & 45.2164 \tabularnewline
Winsorized Mean ( 18 / 40 ) & 33206900 & 712982 & 46.5747 \tabularnewline
Winsorized Mean ( 19 / 40 ) & 33355400 & 690937 & 48.2756 \tabularnewline
Winsorized Mean ( 20 / 40 ) & 33418800 & 681745 & 49.0195 \tabularnewline
Winsorized Mean ( 21 / 40 ) & 33548300 & 663320 & 50.5763 \tabularnewline
Winsorized Mean ( 22 / 40 ) & 33618000 & 653603 & 51.4349 \tabularnewline
Winsorized Mean ( 23 / 40 ) & 33614600 & 645106 & 52.1072 \tabularnewline
Winsorized Mean ( 24 / 40 ) & 33690700 & 626275 & 53.7954 \tabularnewline
Winsorized Mean ( 25 / 40 ) & 33690700 & 617573 & 54.5533 \tabularnewline
Winsorized Mean ( 26 / 40 ) & 33729700 & 593452 & 56.8364 \tabularnewline
Winsorized Mean ( 27 / 40 ) & 33729700 & 593452 & 56.8364 \tabularnewline
Winsorized Mean ( 28 / 40 ) & 33733800 & 583387 & 57.8241 \tabularnewline
Winsorized Mean ( 29 / 40 ) & 33907800 & 549746 & 61.6791 \tabularnewline
Winsorized Mean ( 30 / 40 ) & 34052900 & 521237 & 65.3311 \tabularnewline
Winsorized Mean ( 31 / 40 ) & 34001900 & 506409 & 67.143 \tabularnewline
Winsorized Mean ( 32 / 40 ) & 34001900 & 506409 & 67.143 \tabularnewline
Winsorized Mean ( 33 / 40 ) & 33951700 & 501908 & 67.6451 \tabularnewline
Winsorized Mean ( 34 / 40 ) & 34478900 & 436829 & 78.9299 \tabularnewline
Winsorized Mean ( 35 / 40 ) & 34478900 & 436829 & 78.9299 \tabularnewline
Winsorized Mean ( 36 / 40 ) & 34592200 & 423332 & 81.7141 \tabularnewline
Winsorized Mean ( 37 / 40 ) & 34475700 & 412697 & 83.5376 \tabularnewline
Winsorized Mean ( 38 / 40 ) & 34538300 & 393243 & 87.8294 \tabularnewline
Winsorized Mean ( 39 / 40 ) & 34844000 & 345591 & 100.824 \tabularnewline
Winsorized Mean ( 40 / 40 ) & 35150700 & 310979 & 113.033 \tabularnewline
Trimmed Mean ( 1 / 40 ) & 32656400 & 853809 & 38.2479 \tabularnewline
Trimmed Mean ( 2 / 40 ) & 32761400 & 837071 & 39.1381 \tabularnewline
Trimmed Mean ( 3 / 40 ) & 32852000 & 823445 & 39.8957 \tabularnewline
Trimmed Mean ( 4 / 40 ) & 32959000 & 810395 & 40.6702 \tabularnewline
Trimmed Mean ( 5 / 40 ) & 33066600 & 796543 & 41.5126 \tabularnewline
Trimmed Mean ( 6 / 40 ) & 33176400 & 782033 & 42.4233 \tabularnewline
Trimmed Mean ( 7 / 40 ) & 33256900 & 774396 & 42.9456 \tabularnewline
Trimmed Mean ( 8 / 40 ) & 33342200 & 765889 & 43.5341 \tabularnewline
Trimmed Mean ( 9 / 40 ) & 33427400 & 757004 & 44.1575 \tabularnewline
Trimmed Mean ( 10 / 40 ) & 33508400 & 748619 & 44.7603 \tabularnewline
Trimmed Mean ( 11 / 40 ) & 33592700 & 739660 & 45.4164 \tabularnewline
Trimmed Mean ( 12 / 40 ) & 33674700 & 730756 & 46.082 \tabularnewline
Trimmed Mean ( 13 / 40 ) & 33762200 & 720755 & 46.8429 \tabularnewline
Trimmed Mean ( 14 / 40 ) & 33851600 & 709726 & 47.6968 \tabularnewline
Trimmed Mean ( 15 / 40 ) & 33938800 & 698593 & 48.5817 \tabularnewline
Trimmed Mean ( 16 / 40 ) & 34032000 & 685964 & 49.612 \tabularnewline
Trimmed Mean ( 17 / 40 ) & 34125100 & 672527 & 50.7416 \tabularnewline
Trimmed Mean ( 18 / 40 ) & 34209300 & 660574 & 51.7872 \tabularnewline
Trimmed Mean ( 19 / 40 ) & 34290800 & 649367 & 52.8065 \tabularnewline
Trimmed Mean ( 20 / 40 ) & 34364600 & 639351 & 53.7492 \tabularnewline
Trimmed Mean ( 21 / 40 ) & 34437400 & 628834 & 54.7638 \tabularnewline
Trimmed Mean ( 22 / 40 ) & 34504200 & 618999 & 55.742 \tabularnewline
Trimmed Mean ( 23 / 40 ) & 34569500 & 608680 & 56.7943 \tabularnewline
Trimmed Mean ( 24 / 40 ) & 34638700 & 597485 & 57.9742 \tabularnewline
Trimmed Mean ( 25 / 40 ) & 34706500 & 586737 & 59.1516 \tabularnewline
Trimmed Mean ( 26 / 40 ) & 34778200 & 574963 & 60.4876 \tabularnewline
Trimmed Mean ( 27 / 40 ) & 34851500 & 564118 & 61.7805 \tabularnewline
Trimmed Mean ( 28 / 40 ) & 34929400 & 550865 & 63.4083 \tabularnewline
Trimmed Mean ( 29 / 40 ) & 35012000 & 536133 & 65.3048 \tabularnewline
Trimmed Mean ( 30 / 40 ) & 35088200 & 523560 & 67.0185 \tabularnewline
Trimmed Mean ( 31 / 40 ) & 35159600 & 512637 & 68.5857 \tabularnewline
Trimmed Mean ( 32 / 40 ) & 35239600 & 501023 & 70.3354 \tabularnewline
Trimmed Mean ( 33 / 40 ) & 35325600 & 486264 & 72.6468 \tabularnewline
Trimmed Mean ( 34 / 40 ) & 35421600 & 468012 & 75.6853 \tabularnewline
Trimmed Mean ( 35 / 40 ) & 35488200 & 458242 & 77.4442 \tabularnewline
Trimmed Mean ( 36 / 40 ) & 35560300 & 445409 & 79.8373 \tabularnewline
Trimmed Mean ( 37 / 40 ) & 35630400 & 431581 & 82.558 \tabularnewline
Trimmed Mean ( 38 / 40 ) & 35715600 & 414845 & 86.0938 \tabularnewline
Trimmed Mean ( 39 / 40 ) & 35804100 & 396966 & 90.1942 \tabularnewline
Trimmed Mean ( 40 / 40 ) & 35877900 & 385248 & 93.1294 \tabularnewline
Median & 36936800 &  &  \tabularnewline
Midrange & 24989300 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 34930200 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 35088200 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 34930200 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 35088200 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 35088200 &  &  \tabularnewline
Midmean - Closest Observation & 34930200 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 35088200 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 35012000 &  &  \tabularnewline
Number of observations & 120 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307129&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]32528700[/C][C]877690[/C][C]37.0617[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]30545000[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]27578800[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]33908500[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 40 )[/C][C]32555000[/C][C]868818[/C][C]37.4705[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 40 )[/C][C]32589300[/C][C]860206[/C][C]37.8855[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 40 )[/C][C]32552300[/C][C]854661[/C][C]38.088[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 40 )[/C][C]32564300[/C][C]852146[/C][C]38.2145[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 40 )[/C][C]32572600[/C][C]848130[/C][C]38.4052[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 40 )[/C][C]32749700[/C][C]811264[/C][C]40.3688[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 40 )[/C][C]32739100[/C][C]810225[/C][C]40.4074[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 40 )[/C][C]32763100[/C][C]805983[/C][C]40.6498[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 40 )[/C][C]32819900[/C][C]796156[/C][C]41.223[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 40 )[/C][C]32820100[/C][C]792122[/C][C]41.4332[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 40 )[/C][C]32871200[/C][C]783564[/C][C]41.9509[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 40 )[/C][C]32851500[/C][C]781670[/C][C]42.0273[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 40 )[/C][C]32871200[/C][C]778402[/C][C]42.2291[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 40 )[/C][C]32936300[/C][C]767786[/C][C]42.8978[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 40 )[/C][C]32913800[/C][C]765648[/C][C]42.9882[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 40 )[/C][C]32964500[/C][C]757493[/C][C]43.5179[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 40 )[/C][C]33123200[/C][C]732549[/C][C]45.2164[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 40 )[/C][C]33206900[/C][C]712982[/C][C]46.5747[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 40 )[/C][C]33355400[/C][C]690937[/C][C]48.2756[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 40 )[/C][C]33418800[/C][C]681745[/C][C]49.0195[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 40 )[/C][C]33548300[/C][C]663320[/C][C]50.5763[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 40 )[/C][C]33618000[/C][C]653603[/C][C]51.4349[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 40 )[/C][C]33614600[/C][C]645106[/C][C]52.1072[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 40 )[/C][C]33690700[/C][C]626275[/C][C]53.7954[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 40 )[/C][C]33690700[/C][C]617573[/C][C]54.5533[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 40 )[/C][C]33729700[/C][C]593452[/C][C]56.8364[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 40 )[/C][C]33729700[/C][C]593452[/C][C]56.8364[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 40 )[/C][C]33733800[/C][C]583387[/C][C]57.8241[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 40 )[/C][C]33907800[/C][C]549746[/C][C]61.6791[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 40 )[/C][C]34052900[/C][C]521237[/C][C]65.3311[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 40 )[/C][C]34001900[/C][C]506409[/C][C]67.143[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 40 )[/C][C]34001900[/C][C]506409[/C][C]67.143[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 40 )[/C][C]33951700[/C][C]501908[/C][C]67.6451[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 40 )[/C][C]34478900[/C][C]436829[/C][C]78.9299[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 40 )[/C][C]34478900[/C][C]436829[/C][C]78.9299[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 40 )[/C][C]34592200[/C][C]423332[/C][C]81.7141[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 40 )[/C][C]34475700[/C][C]412697[/C][C]83.5376[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 40 )[/C][C]34538300[/C][C]393243[/C][C]87.8294[/C][/ROW]
[ROW][C]Winsorized Mean ( 39 / 40 )[/C][C]34844000[/C][C]345591[/C][C]100.824[/C][/ROW]
[ROW][C]Winsorized Mean ( 40 / 40 )[/C][C]35150700[/C][C]310979[/C][C]113.033[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 40 )[/C][C]32656400[/C][C]853809[/C][C]38.2479[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 40 )[/C][C]32761400[/C][C]837071[/C][C]39.1381[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 40 )[/C][C]32852000[/C][C]823445[/C][C]39.8957[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 40 )[/C][C]32959000[/C][C]810395[/C][C]40.6702[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 40 )[/C][C]33066600[/C][C]796543[/C][C]41.5126[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 40 )[/C][C]33176400[/C][C]782033[/C][C]42.4233[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 40 )[/C][C]33256900[/C][C]774396[/C][C]42.9456[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 40 )[/C][C]33342200[/C][C]765889[/C][C]43.5341[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 40 )[/C][C]33427400[/C][C]757004[/C][C]44.1575[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 40 )[/C][C]33508400[/C][C]748619[/C][C]44.7603[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 40 )[/C][C]33592700[/C][C]739660[/C][C]45.4164[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 40 )[/C][C]33674700[/C][C]730756[/C][C]46.082[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 40 )[/C][C]33762200[/C][C]720755[/C][C]46.8429[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 40 )[/C][C]33851600[/C][C]709726[/C][C]47.6968[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 40 )[/C][C]33938800[/C][C]698593[/C][C]48.5817[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 40 )[/C][C]34032000[/C][C]685964[/C][C]49.612[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 40 )[/C][C]34125100[/C][C]672527[/C][C]50.7416[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 40 )[/C][C]34209300[/C][C]660574[/C][C]51.7872[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 40 )[/C][C]34290800[/C][C]649367[/C][C]52.8065[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 40 )[/C][C]34364600[/C][C]639351[/C][C]53.7492[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 40 )[/C][C]34437400[/C][C]628834[/C][C]54.7638[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 40 )[/C][C]34504200[/C][C]618999[/C][C]55.742[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 40 )[/C][C]34569500[/C][C]608680[/C][C]56.7943[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 40 )[/C][C]34638700[/C][C]597485[/C][C]57.9742[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 40 )[/C][C]34706500[/C][C]586737[/C][C]59.1516[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 40 )[/C][C]34778200[/C][C]574963[/C][C]60.4876[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 40 )[/C][C]34851500[/C][C]564118[/C][C]61.7805[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 40 )[/C][C]34929400[/C][C]550865[/C][C]63.4083[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 40 )[/C][C]35012000[/C][C]536133[/C][C]65.3048[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 40 )[/C][C]35088200[/C][C]523560[/C][C]67.0185[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 40 )[/C][C]35159600[/C][C]512637[/C][C]68.5857[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 40 )[/C][C]35239600[/C][C]501023[/C][C]70.3354[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 40 )[/C][C]35325600[/C][C]486264[/C][C]72.6468[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 40 )[/C][C]35421600[/C][C]468012[/C][C]75.6853[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 40 )[/C][C]35488200[/C][C]458242[/C][C]77.4442[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 40 )[/C][C]35560300[/C][C]445409[/C][C]79.8373[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 40 )[/C][C]35630400[/C][C]431581[/C][C]82.558[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 40 )[/C][C]35715600[/C][C]414845[/C][C]86.0938[/C][/ROW]
[ROW][C]Trimmed Mean ( 39 / 40 )[/C][C]35804100[/C][C]396966[/C][C]90.1942[/C][/ROW]
[ROW][C]Trimmed Mean ( 40 / 40 )[/C][C]35877900[/C][C]385248[/C][C]93.1294[/C][/ROW]
[ROW][C]Median[/C][C]36936800[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]24989300[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]34930200[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]35088200[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]34930200[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]35088200[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]35088200[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]34930200[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]35088200[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]35012000[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]120[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307129&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307129&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 Mean3252870087769037.0617
Geometric Mean30545000
Harmonic Mean27578800
Quadratic Mean33908500
Winsorized Mean ( 1 / 40 )3255500086881837.4705
Winsorized Mean ( 2 / 40 )3258930086020637.8855
Winsorized Mean ( 3 / 40 )3255230085466138.088
Winsorized Mean ( 4 / 40 )3256430085214638.2145
Winsorized Mean ( 5 / 40 )3257260084813038.4052
Winsorized Mean ( 6 / 40 )3274970081126440.3688
Winsorized Mean ( 7 / 40 )3273910081022540.4074
Winsorized Mean ( 8 / 40 )3276310080598340.6498
Winsorized Mean ( 9 / 40 )3281990079615641.223
Winsorized Mean ( 10 / 40 )3282010079212241.4332
Winsorized Mean ( 11 / 40 )3287120078356441.9509
Winsorized Mean ( 12 / 40 )3285150078167042.0273
Winsorized Mean ( 13 / 40 )3287120077840242.2291
Winsorized Mean ( 14 / 40 )3293630076778642.8978
Winsorized Mean ( 15 / 40 )3291380076564842.9882
Winsorized Mean ( 16 / 40 )3296450075749343.5179
Winsorized Mean ( 17 / 40 )3312320073254945.2164
Winsorized Mean ( 18 / 40 )3320690071298246.5747
Winsorized Mean ( 19 / 40 )3335540069093748.2756
Winsorized Mean ( 20 / 40 )3341880068174549.0195
Winsorized Mean ( 21 / 40 )3354830066332050.5763
Winsorized Mean ( 22 / 40 )3361800065360351.4349
Winsorized Mean ( 23 / 40 )3361460064510652.1072
Winsorized Mean ( 24 / 40 )3369070062627553.7954
Winsorized Mean ( 25 / 40 )3369070061757354.5533
Winsorized Mean ( 26 / 40 )3372970059345256.8364
Winsorized Mean ( 27 / 40 )3372970059345256.8364
Winsorized Mean ( 28 / 40 )3373380058338757.8241
Winsorized Mean ( 29 / 40 )3390780054974661.6791
Winsorized Mean ( 30 / 40 )3405290052123765.3311
Winsorized Mean ( 31 / 40 )3400190050640967.143
Winsorized Mean ( 32 / 40 )3400190050640967.143
Winsorized Mean ( 33 / 40 )3395170050190867.6451
Winsorized Mean ( 34 / 40 )3447890043682978.9299
Winsorized Mean ( 35 / 40 )3447890043682978.9299
Winsorized Mean ( 36 / 40 )3459220042333281.7141
Winsorized Mean ( 37 / 40 )3447570041269783.5376
Winsorized Mean ( 38 / 40 )3453830039324387.8294
Winsorized Mean ( 39 / 40 )34844000345591100.824
Winsorized Mean ( 40 / 40 )35150700310979113.033
Trimmed Mean ( 1 / 40 )3265640085380938.2479
Trimmed Mean ( 2 / 40 )3276140083707139.1381
Trimmed Mean ( 3 / 40 )3285200082344539.8957
Trimmed Mean ( 4 / 40 )3295900081039540.6702
Trimmed Mean ( 5 / 40 )3306660079654341.5126
Trimmed Mean ( 6 / 40 )3317640078203342.4233
Trimmed Mean ( 7 / 40 )3325690077439642.9456
Trimmed Mean ( 8 / 40 )3334220076588943.5341
Trimmed Mean ( 9 / 40 )3342740075700444.1575
Trimmed Mean ( 10 / 40 )3350840074861944.7603
Trimmed Mean ( 11 / 40 )3359270073966045.4164
Trimmed Mean ( 12 / 40 )3367470073075646.082
Trimmed Mean ( 13 / 40 )3376220072075546.8429
Trimmed Mean ( 14 / 40 )3385160070972647.6968
Trimmed Mean ( 15 / 40 )3393880069859348.5817
Trimmed Mean ( 16 / 40 )3403200068596449.612
Trimmed Mean ( 17 / 40 )3412510067252750.7416
Trimmed Mean ( 18 / 40 )3420930066057451.7872
Trimmed Mean ( 19 / 40 )3429080064936752.8065
Trimmed Mean ( 20 / 40 )3436460063935153.7492
Trimmed Mean ( 21 / 40 )3443740062883454.7638
Trimmed Mean ( 22 / 40 )3450420061899955.742
Trimmed Mean ( 23 / 40 )3456950060868056.7943
Trimmed Mean ( 24 / 40 )3463870059748557.9742
Trimmed Mean ( 25 / 40 )3470650058673759.1516
Trimmed Mean ( 26 / 40 )3477820057496360.4876
Trimmed Mean ( 27 / 40 )3485150056411861.7805
Trimmed Mean ( 28 / 40 )3492940055086563.4083
Trimmed Mean ( 29 / 40 )3501200053613365.3048
Trimmed Mean ( 30 / 40 )3508820052356067.0185
Trimmed Mean ( 31 / 40 )3515960051263768.5857
Trimmed Mean ( 32 / 40 )3523960050102370.3354
Trimmed Mean ( 33 / 40 )3532560048626472.6468
Trimmed Mean ( 34 / 40 )3542160046801275.6853
Trimmed Mean ( 35 / 40 )3548820045824277.4442
Trimmed Mean ( 36 / 40 )3556030044540979.8373
Trimmed Mean ( 37 / 40 )3563040043158182.558
Trimmed Mean ( 38 / 40 )3571560041484586.0938
Trimmed Mean ( 39 / 40 )3580410039696690.1942
Trimmed Mean ( 40 / 40 )3587790038524893.1294
Median36936800
Midrange24989300
Midmean - Weighted Average at Xnp34930200
Midmean - Weighted Average at X(n+1)p35088200
Midmean - Empirical Distribution Function34930200
Midmean - Empirical Distribution Function - Averaging35088200
Midmean - Empirical Distribution Function - Interpolation35088200
Midmean - Closest Observation34930200
Midmean - True Basic - Statistics Graphics Toolkit35088200
Midmean - MS Excel (old versions)35012000
Number of observations120



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
geomean <- function(x) {
return(exp(mean(log(x))))
}
harmean <- function(x) {
return(1/mean(1/x))
}
quamean <- function(x) {
return(sqrt(mean(x*x)))
}
winmean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
win <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n
win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn
}
return(win)
}
trimean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
tri <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
tri[j,1] <- mean(x,trim=j/n)
tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2)
}
return(tri)
}
midrange <- function(x) {
return((max(x)+min(x))/2)
}
q1 <- function(data,n,p,i,f) {
np <- n*p;
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q2 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q3 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
q4 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- (data[i]+data[i+1])/2
} else {
qvalue <- data[i+1]
}
}
q5 <- function(data,n,p,i,f) {
np <- (n-1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i+1]
} else {
qvalue <- data[i+1] + f*(data[i+2]-data[i+1])
}
}
q6 <- function(data,n,p,i,f) {
np <- n*p+0.5
i <<- floor(np)
f <<- np - i
qvalue <- data[i]
}
q7 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- f*data[i] + (1-f)*data[i+1]
}
}
q8 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
if (f == 0.5) {
qvalue <- (data[i]+data[i+1])/2
} else {
if (f < 0.5) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
}
}
midmean <- function(x,def) {
x <-sort(x[!is.na(x)])
n<-length(x)
if (def==1) {
qvalue1 <- q1(x,n,0.25,i,f)
qvalue3 <- q1(x,n,0.75,i,f)
}
if (def==2) {
qvalue1 <- q2(x,n,0.25,i,f)
qvalue3 <- q2(x,n,0.75,i,f)
}
if (def==3) {
qvalue1 <- q3(x,n,0.25,i,f)
qvalue3 <- q3(x,n,0.75,i,f)
}
if (def==4) {
qvalue1 <- q4(x,n,0.25,i,f)
qvalue3 <- q4(x,n,0.75,i,f)
}
if (def==5) {
qvalue1 <- q5(x,n,0.25,i,f)
qvalue3 <- q5(x,n,0.75,i,f)
}
if (def==6) {
qvalue1 <- q6(x,n,0.25,i,f)
qvalue3 <- q6(x,n,0.75,i,f)
}
if (def==7) {
qvalue1 <- q7(x,n,0.25,i,f)
qvalue3 <- q7(x,n,0.75,i,f)
}
if (def==8) {
qvalue1 <- q8(x,n,0.25,i,f)
qvalue3 <- q8(x,n,0.75,i,f)
}
midm <- 0
myn <- 0
roundno4 <- round(n/4)
round3no4 <- round(3*n/4)
for (i in 1:n) {
if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){
midm = midm + x[i]
myn = myn + 1
}
}
midm = midm / myn
return(midm)
}
(arm <- mean(x))
sqrtn <- sqrt(length(x))
(armse <- sd(x) / sqrtn)
(armose <- arm / armse)
(geo <- geomean(x))
(har <- harmean(x))
(qua <- quamean(x))
(win <- winmean(x))
(tri <- trimean(x))
(midr <- midrange(x))
midm <- array(NA,dim=8)
for (j in 1:8) midm[j] <- midmean(x,j)
midm
bitmap(file='test1.png')
lb <- win[,1] - 2*win[,2]
ub <- win[,1] + 2*win[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
bitmap(file='test2.png')
lb <- tri[,1] - 2*tri[,2]
ub <- tri[,1] + 2*tri[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Measure',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.element(a,'S.E.',header=TRUE)
a<-table.element(a,'Value/S.E.',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Arithmetic Mean',header=TRUE)
a<-table.element(a,signif(arm,6))
a<-table.element(a, signif(armse,6))
a<-table.element(a,signif(armose,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Geometric Mean',header=TRUE)
a<-table.element(a,signif(geo,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Harmonic Mean',header=TRUE)
a<-table.element(a,signif(har,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Quadratic Mean',header=TRUE)
a<-table.element(a,signif(qua,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
for (j in 1:length(win[,1])) {
a<-table.row.start(a)
mylabel <- paste('Winsorized Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(win[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a, mylabel,header=TRUE)
a<-table.element(a,signif(win[j,1],6))
a<-table.element(a,signif(win[j,2],6))
a<-table.element(a,signif(win[j,1]/win[j,2],6))
a<-table.row.end(a)
}
for (j in 1:length(tri[,1])) {
a<-table.row.start(a)
mylabel <- paste('Trimmed Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(tri[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a, mylabel,header=TRUE)
a<-table.element(a,signif(tri[j,1],6))
a<-table.element(a,signif(tri[j,2],6))
a<-table.element(a,signif(tri[j,1]/tri[j,2],6))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'Median',header=TRUE)
a<-table.element(a,signif(median(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Midrange',header=TRUE)
a<-table.element(a,signif(midr,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Weighted Average at Xnp',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[1],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Weighted Average at X(n+1)p',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[2],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[3],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Averaging',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[4],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Interpolation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[5],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Closest Observation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[6],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'True Basic - Statistics Graphics Toolkit',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[7],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'MS Excel (old versions)',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[8],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of observations',header=TRUE)
a<-table.element(a,signif(length(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')