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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 computationMon, 04 Apr 2011 16:52:05 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Apr/04/t1301935701y8uw7fw43gkohtu.htm/, Retrieved Wed, 08 May 2024 06:45:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=120155, Retrieved Wed, 08 May 2024 06:45:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W51
Estimated Impact86
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2011-04-04 16:52:05] [164acd287bf1b95108b808ea4c161e74] [Current]
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Dataseries X:
70938
34077
45409
40809
37013
44953
19848
32745
43412
34931
33008
8620
68906
39556
50669
36432
40891
48428
36222
33425
39401
37967
34801
12657
69116
41519
51321
38529
41547
52073
38401
40898
40439
41888
37898
8771
68184
50530
47221
41756
45633
48138
39486
39341
41117
41629
29722
7054
56676
34870
35117
30169
30936
35699
33228
27733
33666
35429
27438
8170
63410
38040
45389
37353
37024
50957
37994
36454
46080
43373
37395
10963
75001




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 216.218.223.82

\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 & 'George Udny Yule' @ 216.218.223.82 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=120155&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]'George Udny Yule' @ 216.218.223.82[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=120155&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=120155&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'George Udny Yule' @ 216.218.223.82







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean39395.79452054791609.1359215390724.4825772597677
Geometric Mean36158.3537370382
Harmonic Mean31074.1695492202
Quadratic Mean41694.8384301022
Winsorized Mean ( 1 / 24 )39355.42465753421588.6762324596324.7724639252664
Winsorized Mean ( 2 / 24 )39317.83561643841571.8588608854225.0135916110755
Winsorized Mean ( 3 / 24 )39315.41095890411567.9105411119125.0750345303648
Winsorized Mean ( 4 / 24 )39395.95890410961525.7394711931525.8208951448974
Winsorized Mean ( 5 / 24 )391851413.7023496243227.7179987784649
Winsorized Mean ( 6 / 24 )39222.56164383561140.7688223663334.3825680320357
Winsorized Mean ( 7 / 24 )39508.9863013699894.13143987369444.1870004112046
Winsorized Mean ( 8 / 24 )39458.904109589872.25451055806145.2378332607802
Winsorized Mean ( 9 / 24 )39659.2465753425820.1291661876648.3573176158299
Winsorized Mean ( 10 / 24 )39681.0273972603802.40870426522349.4523890211245
Winsorized Mean ( 11 / 24 )39775.6575342466779.79253773672751.0079997042439
Winsorized Mean ( 12 / 24 )39727.4931506849670.34561416970859.2641949330742
Winsorized Mean ( 13 / 24 )39722.6849315068654.35200116565360.7053770153456
Winsorized Mean ( 14 / 24 )39589.0136986301617.50952749727364.1107739002537
Winsorized Mean ( 15 / 24 )39395.0410958904572.50795274010768.8113429819446
Winsorized Mean ( 16 / 24 )39349.8904109589549.15347977932971.6555423208303
Winsorized Mean ( 17 / 24 )39393.4383561644527.29113171939274.7090857145847
Winsorized Mean ( 18 / 24 )39567.0273972603502.2212233103178.7840608098173
Winsorized Mean ( 19 / 24 )39471.5068493151481.74078964011181.9351562046524
Winsorized Mean ( 20 / 24 )39066.0273972603415.23518210572294.0816893191717
Winsorized Mean ( 21 / 24 )39108.3150684932406.25045269929796.266514433747
Winsorized Mean ( 22 / 24 )38754.8082191781330.908382420481117.116429434939
Winsorized Mean ( 23 / 24 )38798.2876712329313.673079481278123.690205533078
Winsorized Mean ( 24 / 24 )38928.4794520548285.034433491989136.574655121971
Trimmed Mean ( 1 / 24 )39349.83098591551507.5654455545726.1015739661241
Trimmed Mean ( 2 / 24 )39343.91304347831409.8052501861127.9073390018121
Trimmed Mean ( 3 / 24 )39358.11940298511301.917230871130.2308921563708
Trimmed Mean ( 4 / 24 )39374.10769230771169.1726718486233.6768970404106
Trimmed Mean ( 5 / 24 )39367.77777777781018.187128878338.6645800768939
Trimmed Mean ( 6 / 24 )39411.5245901639868.03575214280145.4031121331974
Trimmed Mean ( 7 / 24 )39450.4915254237779.04987403747450.6392374097555
Trimmed Mean ( 8 / 24 )39439.7894736842745.33671628138652.9153986542568
Trimmed Mean ( 9 / 24 )39436.6181818182709.49049271511655.5844209143664
Trimmed Mean ( 10 / 24 )39402.5471698113678.26361138983958.0932641942431
Trimmed Mean ( 11 / 24 )39362.6862745098643.39847104366861.1793282795013
Trimmed Mean ( 12 / 24 )39306.7551020408604.59227457718365.0136575587733
Trimmed Mean ( 13 / 24 )39252.2978723404582.40375439317167.3970550090957
Trimmed Mean ( 14 / 24 )39193.6557.42722168436370.3116002867061
Trimmed Mean ( 15 / 24 )39145.6511627907534.06095736678173.2980957001625
Trimmed Mean ( 16 / 24 )39116.0487804878514.58149340521976.0152653793263
Trimmed Mean ( 17 / 24 )39088.6923076923494.27182656328479.0833913789492
Trimmed Mean ( 18 / 24 )39053.3243243243472.16026611520382.7120093048992
Trimmed Mean ( 19 / 24 )38993.8447.77956724300987.0825800294683
Trimmed Mean ( 20 / 24 )38938.1818181818419.66674967779492.7835761305304
Trimmed Mean ( 21 / 24 )38923.1290322581401.48023356031696.9490544704748
Trimmed Mean ( 22 / 24 )38900.9310344828377.313996622022103.099623609914
Trimmed Mean ( 23 / 24 )38918.8888888889367.123799474443106.010258513895
Trimmed Mean ( 24 / 24 )38934.2356.353602479335109.257208932686
Median38529
Midrange41027.5
Midmean - Weighted Average at Xnp38877.3333333333
Midmean - Weighted Average at X(n+1)p39053.3243243243
Midmean - Empirical Distribution Function39053.3243243243
Midmean - Empirical Distribution Function - Averaging39053.3243243243
Midmean - Empirical Distribution Function - Interpolation39053.3243243243
Midmean - Closest Observation38922.3684210526
Midmean - True Basic - Statistics Graphics Toolkit39053.3243243243
Midmean - MS Excel (old versions)39053.3243243243
Number of observations73

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 39395.7945205479 & 1609.13592153907 & 24.4825772597677 \tabularnewline
Geometric Mean & 36158.3537370382 &  &  \tabularnewline
Harmonic Mean & 31074.1695492202 &  &  \tabularnewline
Quadratic Mean & 41694.8384301022 &  &  \tabularnewline
Winsorized Mean ( 1 / 24 ) & 39355.4246575342 & 1588.67623245963 & 24.7724639252664 \tabularnewline
Winsorized Mean ( 2 / 24 ) & 39317.8356164384 & 1571.85886088542 & 25.0135916110755 \tabularnewline
Winsorized Mean ( 3 / 24 ) & 39315.4109589041 & 1567.91054111191 & 25.0750345303648 \tabularnewline
Winsorized Mean ( 4 / 24 ) & 39395.9589041096 & 1525.73947119315 & 25.8208951448974 \tabularnewline
Winsorized Mean ( 5 / 24 ) & 39185 & 1413.70234962432 & 27.7179987784649 \tabularnewline
Winsorized Mean ( 6 / 24 ) & 39222.5616438356 & 1140.76882236633 & 34.3825680320357 \tabularnewline
Winsorized Mean ( 7 / 24 ) & 39508.9863013699 & 894.131439873694 & 44.1870004112046 \tabularnewline
Winsorized Mean ( 8 / 24 ) & 39458.904109589 & 872.254510558061 & 45.2378332607802 \tabularnewline
Winsorized Mean ( 9 / 24 ) & 39659.2465753425 & 820.12916618766 & 48.3573176158299 \tabularnewline
Winsorized Mean ( 10 / 24 ) & 39681.0273972603 & 802.408704265223 & 49.4523890211245 \tabularnewline
Winsorized Mean ( 11 / 24 ) & 39775.6575342466 & 779.792537736727 & 51.0079997042439 \tabularnewline
Winsorized Mean ( 12 / 24 ) & 39727.4931506849 & 670.345614169708 & 59.2641949330742 \tabularnewline
Winsorized Mean ( 13 / 24 ) & 39722.6849315068 & 654.352001165653 & 60.7053770153456 \tabularnewline
Winsorized Mean ( 14 / 24 ) & 39589.0136986301 & 617.509527497273 & 64.1107739002537 \tabularnewline
Winsorized Mean ( 15 / 24 ) & 39395.0410958904 & 572.507952740107 & 68.8113429819446 \tabularnewline
Winsorized Mean ( 16 / 24 ) & 39349.8904109589 & 549.153479779329 & 71.6555423208303 \tabularnewline
Winsorized Mean ( 17 / 24 ) & 39393.4383561644 & 527.291131719392 & 74.7090857145847 \tabularnewline
Winsorized Mean ( 18 / 24 ) & 39567.0273972603 & 502.22122331031 & 78.7840608098173 \tabularnewline
Winsorized Mean ( 19 / 24 ) & 39471.5068493151 & 481.740789640111 & 81.9351562046524 \tabularnewline
Winsorized Mean ( 20 / 24 ) & 39066.0273972603 & 415.235182105722 & 94.0816893191717 \tabularnewline
Winsorized Mean ( 21 / 24 ) & 39108.3150684932 & 406.250452699297 & 96.266514433747 \tabularnewline
Winsorized Mean ( 22 / 24 ) & 38754.8082191781 & 330.908382420481 & 117.116429434939 \tabularnewline
Winsorized Mean ( 23 / 24 ) & 38798.2876712329 & 313.673079481278 & 123.690205533078 \tabularnewline
Winsorized Mean ( 24 / 24 ) & 38928.4794520548 & 285.034433491989 & 136.574655121971 \tabularnewline
Trimmed Mean ( 1 / 24 ) & 39349.8309859155 & 1507.56544555457 & 26.1015739661241 \tabularnewline
Trimmed Mean ( 2 / 24 ) & 39343.9130434783 & 1409.80525018611 & 27.9073390018121 \tabularnewline
Trimmed Mean ( 3 / 24 ) & 39358.1194029851 & 1301.9172308711 & 30.2308921563708 \tabularnewline
Trimmed Mean ( 4 / 24 ) & 39374.1076923077 & 1169.17267184862 & 33.6768970404106 \tabularnewline
Trimmed Mean ( 5 / 24 ) & 39367.7777777778 & 1018.1871288783 & 38.6645800768939 \tabularnewline
Trimmed Mean ( 6 / 24 ) & 39411.5245901639 & 868.035752142801 & 45.4031121331974 \tabularnewline
Trimmed Mean ( 7 / 24 ) & 39450.4915254237 & 779.049874037474 & 50.6392374097555 \tabularnewline
Trimmed Mean ( 8 / 24 ) & 39439.7894736842 & 745.336716281386 & 52.9153986542568 \tabularnewline
Trimmed Mean ( 9 / 24 ) & 39436.6181818182 & 709.490492715116 & 55.5844209143664 \tabularnewline
Trimmed Mean ( 10 / 24 ) & 39402.5471698113 & 678.263611389839 & 58.0932641942431 \tabularnewline
Trimmed Mean ( 11 / 24 ) & 39362.6862745098 & 643.398471043668 & 61.1793282795013 \tabularnewline
Trimmed Mean ( 12 / 24 ) & 39306.7551020408 & 604.592274577183 & 65.0136575587733 \tabularnewline
Trimmed Mean ( 13 / 24 ) & 39252.2978723404 & 582.403754393171 & 67.3970550090957 \tabularnewline
Trimmed Mean ( 14 / 24 ) & 39193.6 & 557.427221684363 & 70.3116002867061 \tabularnewline
Trimmed Mean ( 15 / 24 ) & 39145.6511627907 & 534.060957366781 & 73.2980957001625 \tabularnewline
Trimmed Mean ( 16 / 24 ) & 39116.0487804878 & 514.581493405219 & 76.0152653793263 \tabularnewline
Trimmed Mean ( 17 / 24 ) & 39088.6923076923 & 494.271826563284 & 79.0833913789492 \tabularnewline
Trimmed Mean ( 18 / 24 ) & 39053.3243243243 & 472.160266115203 & 82.7120093048992 \tabularnewline
Trimmed Mean ( 19 / 24 ) & 38993.8 & 447.779567243009 & 87.0825800294683 \tabularnewline
Trimmed Mean ( 20 / 24 ) & 38938.1818181818 & 419.666749677794 & 92.7835761305304 \tabularnewline
Trimmed Mean ( 21 / 24 ) & 38923.1290322581 & 401.480233560316 & 96.9490544704748 \tabularnewline
Trimmed Mean ( 22 / 24 ) & 38900.9310344828 & 377.313996622022 & 103.099623609914 \tabularnewline
Trimmed Mean ( 23 / 24 ) & 38918.8888888889 & 367.123799474443 & 106.010258513895 \tabularnewline
Trimmed Mean ( 24 / 24 ) & 38934.2 & 356.353602479335 & 109.257208932686 \tabularnewline
Median & 38529 &  &  \tabularnewline
Midrange & 41027.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 38877.3333333333 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 39053.3243243243 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 39053.3243243243 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 39053.3243243243 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 39053.3243243243 &  &  \tabularnewline
Midmean - Closest Observation & 38922.3684210526 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 39053.3243243243 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 39053.3243243243 &  &  \tabularnewline
Number of observations & 73 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=120155&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]39395.7945205479[/C][C]1609.13592153907[/C][C]24.4825772597677[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]36158.3537370382[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]31074.1695492202[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]41694.8384301022[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 24 )[/C][C]39355.4246575342[/C][C]1588.67623245963[/C][C]24.7724639252664[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 24 )[/C][C]39317.8356164384[/C][C]1571.85886088542[/C][C]25.0135916110755[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 24 )[/C][C]39315.4109589041[/C][C]1567.91054111191[/C][C]25.0750345303648[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 24 )[/C][C]39395.9589041096[/C][C]1525.73947119315[/C][C]25.8208951448974[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 24 )[/C][C]39185[/C][C]1413.70234962432[/C][C]27.7179987784649[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 24 )[/C][C]39222.5616438356[/C][C]1140.76882236633[/C][C]34.3825680320357[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 24 )[/C][C]39508.9863013699[/C][C]894.131439873694[/C][C]44.1870004112046[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 24 )[/C][C]39458.904109589[/C][C]872.254510558061[/C][C]45.2378332607802[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 24 )[/C][C]39659.2465753425[/C][C]820.12916618766[/C][C]48.3573176158299[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 24 )[/C][C]39681.0273972603[/C][C]802.408704265223[/C][C]49.4523890211245[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 24 )[/C][C]39775.6575342466[/C][C]779.792537736727[/C][C]51.0079997042439[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 24 )[/C][C]39727.4931506849[/C][C]670.345614169708[/C][C]59.2641949330742[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 24 )[/C][C]39722.6849315068[/C][C]654.352001165653[/C][C]60.7053770153456[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 24 )[/C][C]39589.0136986301[/C][C]617.509527497273[/C][C]64.1107739002537[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 24 )[/C][C]39395.0410958904[/C][C]572.507952740107[/C][C]68.8113429819446[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 24 )[/C][C]39349.8904109589[/C][C]549.153479779329[/C][C]71.6555423208303[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 24 )[/C][C]39393.4383561644[/C][C]527.291131719392[/C][C]74.7090857145847[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 24 )[/C][C]39567.0273972603[/C][C]502.22122331031[/C][C]78.7840608098173[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 24 )[/C][C]39471.5068493151[/C][C]481.740789640111[/C][C]81.9351562046524[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 24 )[/C][C]39066.0273972603[/C][C]415.235182105722[/C][C]94.0816893191717[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 24 )[/C][C]39108.3150684932[/C][C]406.250452699297[/C][C]96.266514433747[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 24 )[/C][C]38754.8082191781[/C][C]330.908382420481[/C][C]117.116429434939[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 24 )[/C][C]38798.2876712329[/C][C]313.673079481278[/C][C]123.690205533078[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 24 )[/C][C]38928.4794520548[/C][C]285.034433491989[/C][C]136.574655121971[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 24 )[/C][C]39349.8309859155[/C][C]1507.56544555457[/C][C]26.1015739661241[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 24 )[/C][C]39343.9130434783[/C][C]1409.80525018611[/C][C]27.9073390018121[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 24 )[/C][C]39358.1194029851[/C][C]1301.9172308711[/C][C]30.2308921563708[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 24 )[/C][C]39374.1076923077[/C][C]1169.17267184862[/C][C]33.6768970404106[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 24 )[/C][C]39367.7777777778[/C][C]1018.1871288783[/C][C]38.6645800768939[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 24 )[/C][C]39411.5245901639[/C][C]868.035752142801[/C][C]45.4031121331974[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 24 )[/C][C]39450.4915254237[/C][C]779.049874037474[/C][C]50.6392374097555[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 24 )[/C][C]39439.7894736842[/C][C]745.336716281386[/C][C]52.9153986542568[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 24 )[/C][C]39436.6181818182[/C][C]709.490492715116[/C][C]55.5844209143664[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 24 )[/C][C]39402.5471698113[/C][C]678.263611389839[/C][C]58.0932641942431[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 24 )[/C][C]39362.6862745098[/C][C]643.398471043668[/C][C]61.1793282795013[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 24 )[/C][C]39306.7551020408[/C][C]604.592274577183[/C][C]65.0136575587733[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 24 )[/C][C]39252.2978723404[/C][C]582.403754393171[/C][C]67.3970550090957[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 24 )[/C][C]39193.6[/C][C]557.427221684363[/C][C]70.3116002867061[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 24 )[/C][C]39145.6511627907[/C][C]534.060957366781[/C][C]73.2980957001625[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 24 )[/C][C]39116.0487804878[/C][C]514.581493405219[/C][C]76.0152653793263[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 24 )[/C][C]39088.6923076923[/C][C]494.271826563284[/C][C]79.0833913789492[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 24 )[/C][C]39053.3243243243[/C][C]472.160266115203[/C][C]82.7120093048992[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 24 )[/C][C]38993.8[/C][C]447.779567243009[/C][C]87.0825800294683[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 24 )[/C][C]38938.1818181818[/C][C]419.666749677794[/C][C]92.7835761305304[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 24 )[/C][C]38923.1290322581[/C][C]401.480233560316[/C][C]96.9490544704748[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 24 )[/C][C]38900.9310344828[/C][C]377.313996622022[/C][C]103.099623609914[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 24 )[/C][C]38918.8888888889[/C][C]367.123799474443[/C][C]106.010258513895[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 24 )[/C][C]38934.2[/C][C]356.353602479335[/C][C]109.257208932686[/C][/ROW]
[ROW][C]Median[/C][C]38529[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]41027.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]38877.3333333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]39053.3243243243[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]39053.3243243243[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]39053.3243243243[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]39053.3243243243[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]38922.3684210526[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]39053.3243243243[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]39053.3243243243[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]73[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=120155&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=120155&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 Mean39395.79452054791609.1359215390724.4825772597677
Geometric Mean36158.3537370382
Harmonic Mean31074.1695492202
Quadratic Mean41694.8384301022
Winsorized Mean ( 1 / 24 )39355.42465753421588.6762324596324.7724639252664
Winsorized Mean ( 2 / 24 )39317.83561643841571.8588608854225.0135916110755
Winsorized Mean ( 3 / 24 )39315.41095890411567.9105411119125.0750345303648
Winsorized Mean ( 4 / 24 )39395.95890410961525.7394711931525.8208951448974
Winsorized Mean ( 5 / 24 )391851413.7023496243227.7179987784649
Winsorized Mean ( 6 / 24 )39222.56164383561140.7688223663334.3825680320357
Winsorized Mean ( 7 / 24 )39508.9863013699894.13143987369444.1870004112046
Winsorized Mean ( 8 / 24 )39458.904109589872.25451055806145.2378332607802
Winsorized Mean ( 9 / 24 )39659.2465753425820.1291661876648.3573176158299
Winsorized Mean ( 10 / 24 )39681.0273972603802.40870426522349.4523890211245
Winsorized Mean ( 11 / 24 )39775.6575342466779.79253773672751.0079997042439
Winsorized Mean ( 12 / 24 )39727.4931506849670.34561416970859.2641949330742
Winsorized Mean ( 13 / 24 )39722.6849315068654.35200116565360.7053770153456
Winsorized Mean ( 14 / 24 )39589.0136986301617.50952749727364.1107739002537
Winsorized Mean ( 15 / 24 )39395.0410958904572.50795274010768.8113429819446
Winsorized Mean ( 16 / 24 )39349.8904109589549.15347977932971.6555423208303
Winsorized Mean ( 17 / 24 )39393.4383561644527.29113171939274.7090857145847
Winsorized Mean ( 18 / 24 )39567.0273972603502.2212233103178.7840608098173
Winsorized Mean ( 19 / 24 )39471.5068493151481.74078964011181.9351562046524
Winsorized Mean ( 20 / 24 )39066.0273972603415.23518210572294.0816893191717
Winsorized Mean ( 21 / 24 )39108.3150684932406.25045269929796.266514433747
Winsorized Mean ( 22 / 24 )38754.8082191781330.908382420481117.116429434939
Winsorized Mean ( 23 / 24 )38798.2876712329313.673079481278123.690205533078
Winsorized Mean ( 24 / 24 )38928.4794520548285.034433491989136.574655121971
Trimmed Mean ( 1 / 24 )39349.83098591551507.5654455545726.1015739661241
Trimmed Mean ( 2 / 24 )39343.91304347831409.8052501861127.9073390018121
Trimmed Mean ( 3 / 24 )39358.11940298511301.917230871130.2308921563708
Trimmed Mean ( 4 / 24 )39374.10769230771169.1726718486233.6768970404106
Trimmed Mean ( 5 / 24 )39367.77777777781018.187128878338.6645800768939
Trimmed Mean ( 6 / 24 )39411.5245901639868.03575214280145.4031121331974
Trimmed Mean ( 7 / 24 )39450.4915254237779.04987403747450.6392374097555
Trimmed Mean ( 8 / 24 )39439.7894736842745.33671628138652.9153986542568
Trimmed Mean ( 9 / 24 )39436.6181818182709.49049271511655.5844209143664
Trimmed Mean ( 10 / 24 )39402.5471698113678.26361138983958.0932641942431
Trimmed Mean ( 11 / 24 )39362.6862745098643.39847104366861.1793282795013
Trimmed Mean ( 12 / 24 )39306.7551020408604.59227457718365.0136575587733
Trimmed Mean ( 13 / 24 )39252.2978723404582.40375439317167.3970550090957
Trimmed Mean ( 14 / 24 )39193.6557.42722168436370.3116002867061
Trimmed Mean ( 15 / 24 )39145.6511627907534.06095736678173.2980957001625
Trimmed Mean ( 16 / 24 )39116.0487804878514.58149340521976.0152653793263
Trimmed Mean ( 17 / 24 )39088.6923076923494.27182656328479.0833913789492
Trimmed Mean ( 18 / 24 )39053.3243243243472.16026611520382.7120093048992
Trimmed Mean ( 19 / 24 )38993.8447.77956724300987.0825800294683
Trimmed Mean ( 20 / 24 )38938.1818181818419.66674967779492.7835761305304
Trimmed Mean ( 21 / 24 )38923.1290322581401.48023356031696.9490544704748
Trimmed Mean ( 22 / 24 )38900.9310344828377.313996622022103.099623609914
Trimmed Mean ( 23 / 24 )38918.8888888889367.123799474443106.010258513895
Trimmed Mean ( 24 / 24 )38934.2356.353602479335109.257208932686
Median38529
Midrange41027.5
Midmean - Weighted Average at Xnp38877.3333333333
Midmean - Weighted Average at X(n+1)p39053.3243243243
Midmean - Empirical Distribution Function39053.3243243243
Midmean - Empirical Distribution Function - Averaging39053.3243243243
Midmean - Empirical Distribution Function - Interpolation39053.3243243243
Midmean - Closest Observation38922.3684210526
Midmean - True Basic - Statistics Graphics Toolkit39053.3243243243
Midmean - MS Excel (old versions)39053.3243243243
Number of observations73



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')