Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSun, 13 Aug 2017 12:45:30 +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/13/t15026211456nzy12p9atl7yia.htm/, Retrieved Fri, 10 May 2024 12:44:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307169, Retrieved Fri, 10 May 2024 12:44:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2017-08-13 10:45:30] [270a72b021b4bbf70c885af1fd2608d6] [Current]
Feedback Forum

Post a new message
Dataseries X:
14741900
14195900
15014900
12011900
15560900
15287900
16379900
16925900
18836900
16379900
15560900
19382900
16379900
12284900
14468900
10919900
15287900
12557900
16652900
15014900
15833900
17744900
17471900
20747900
15014900
12557900
13922900
10100900
14468900
11192900
15833900
15014900
13376900
19109900
17198900
19655900
14741900
13649900
12284900
10100900
13376900
12011900
16379900
15833900
13649900
18290900
16925900
21839900
17471900
10646900
10646900
10646900
12557900
12557900
16925900
15560900
13922900
17471900
16106900
23204900
18290900
10646900
11192900
9281900
12830900
14741900
18563900
18290900
14741900
17198900
15287900
21839900
16652900
13376900
12011900
9008900
13376900
16106900
18836900
17744900
13103900
18836900
14741900
22658900
18836900
13649900
12557900
8462900
13376900
12830900
19382900
19382900
14741900
19109900
14195900
22112900
18836900
13922900
10646900
7370900
14468900
13922900
18290900
21020900
15560900
17471900
13103900
22658900




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307169&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]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=307169&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307169&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 time1 seconds
R ServerBig Analytics Cloud Computing Center







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean1532580031961147.9515
Geometric Mean14957600
Harmonic Mean14573400
Quadratic Mean15678400
Winsorized Mean ( 1 / 36 )1533090031627848.4727
Winsorized Mean ( 2 / 36 )1534100031430048.81
Winsorized Mean ( 3 / 36 )1533340030969149.5119
Winsorized Mean ( 4 / 36 )1535360030240850.7712
Winsorized Mean ( 5 / 36 )1535360030240850.7712
Winsorized Mean ( 6 / 36 )1533850028888953.0946
Winsorized Mean ( 7 / 36 )1532080028569253.6269
Winsorized Mean ( 8 / 36 )1523990027235755.9554
Winsorized Mean ( 9 / 36 )1521710026898756.572
Winsorized Mean ( 10 / 36 )1521710026898756.572
Winsorized Mean ( 11 / 36 )1524490026465557.603
Winsorized Mean ( 12 / 36 )1524490025573259.6129
Winsorized Mean ( 13 / 36 )1524490025573259.6129
Winsorized Mean ( 14 / 36 )1531570023591864.9196
Winsorized Mean ( 15 / 36 )1531570023591864.9196
Winsorized Mean ( 16 / 36 )1531570023591864.9196
Winsorized Mean ( 17 / 36 )1535870023042666.6535
Winsorized Mean ( 18 / 36 )1535870023042666.6535
Winsorized Mean ( 19 / 36 )1535870021785270.5007
Winsorized Mean ( 20 / 36 )1530810021103572.5385
Winsorized Mean ( 21 / 36 )1530810021103572.5385
Winsorized Mean ( 22 / 36 )1530810021103572.5385
Winsorized Mean ( 23 / 36 )1530810021103572.5385
Winsorized Mean ( 24 / 36 )1524750018812781.0487
Winsorized Mean ( 25 / 36 )1524750018812781.0487
Winsorized Mean ( 26 / 36 )1524750017230988.4888
Winsorized Mean ( 27 / 36 )1524750017230988.4888
Winsorized Mean ( 28 / 36 )1531820016428293.2437
Winsorized Mean ( 29 / 36 )1531820016428293.2437
Winsorized Mean ( 30 / 36 )1524240015516398.2348
Winsorized Mean ( 31 / 36 )1524240015516398.2348
Winsorized Mean ( 32 / 36 )15161500145817103.976
Winsorized Mean ( 33 / 36 )15244900136484111.698
Winsorized Mean ( 34 / 36 )15244900136484111.698
Winsorized Mean ( 35 / 36 )15156500126494119.82
Winsorized Mean ( 36 / 36 )15247500116589130.78
Trimmed Mean ( 1 / 36 )1532650030789249.7789
Trimmed Mean ( 2 / 36 )1532200029846251.3365
Trimmed Mean ( 3 / 36 )1531200028901652.9798
Trimmed Mean ( 4 / 36 )1530430028031554.5967
Trimmed Mean ( 5 / 36 )1529070027292856.0246
Trimmed Mean ( 6 / 36 )1527650026454557.7464
Trimmed Mean ( 7 / 36 )1526470025842259.0687
Trimmed Mean ( 8 / 36 )1525530025217960.4937
Trimmed Mean ( 9 / 36 )1525760024778961.5749
Trimmed Mean ( 10 / 36 )1526310024338962.7105
Trimmed Mean ( 11 / 36 )1526890023833864.0639
Trimmed Mean ( 12 / 36 )1527160023327765.4656
Trimmed Mean ( 13 / 36 )1527460022890966.7278
Trimmed Mean ( 14 / 36 )1527770022384268.252
Trimmed Mean ( 15 / 36 )1527390022099769.1136
Trimmed Mean ( 16 / 36 )1526990021764070.1613
Trimmed Mean ( 17 / 36 )1526580021368271.4416
Trimmed Mean ( 18 / 36 )1525760020980172.7241
Trimmed Mean ( 19 / 36 )1524890020519074.3159
Trimmed Mean ( 20 / 36 )1523970020157575.6033
Trimmed Mean ( 21 / 36 )1523410019825476.8414
Trimmed Mean ( 22 / 36 )1522820019423078.4027
Trimmed Mean ( 23 / 36 )1522190018934980.3905
Trimmed Mean ( 24 / 36 )1521510018340682.9586
Trimmed Mean ( 25 / 36 )1521260017989884.5624
Trimmed Mean ( 26 / 36 )1520990017553986.6466
Trimmed Mean ( 27 / 36 )1520700017269588.057
Trimmed Mean ( 28 / 36 )1520390016906589.9295
Trimmed Mean ( 29 / 36 )1519510016575991.6699
Trimmed Mean ( 30 / 36 )1518550016147394.0436
Trimmed Mean ( 31 / 36 )1518110015772696.2498
Trimmed Mean ( 32 / 36 )1517620015279099.327
Trimmed Mean ( 33 / 36 )15177400148296102.345
Trimmed Mean ( 34 / 36 )15171900144288105.15
Trimmed Mean ( 35 / 36 )15165800138790109.271
Trimmed Mean ( 36 / 36 )15166600133850113.31
Median15014900
Midrange15287900
Midmean - Weighted Average at Xnp15209900
Midmean - Weighted Average at X(n+1)p15209900
Midmean - Empirical Distribution Function15209900
Midmean - Empirical Distribution Function - Averaging15209900
Midmean - Empirical Distribution Function - Interpolation15209900
Midmean - Closest Observation15209900
Midmean - True Basic - Statistics Graphics Toolkit15209900
Midmean - MS Excel (old versions)15209900
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 15325800 & 319611 & 47.9515 \tabularnewline
Geometric Mean & 14957600 &  &  \tabularnewline
Harmonic Mean & 14573400 &  &  \tabularnewline
Quadratic Mean & 15678400 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 15330900 & 316278 & 48.4727 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 15341000 & 314300 & 48.81 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 15333400 & 309691 & 49.5119 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 15353600 & 302408 & 50.7712 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 15353600 & 302408 & 50.7712 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 15338500 & 288889 & 53.0946 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 15320800 & 285692 & 53.6269 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 15239900 & 272357 & 55.9554 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 15217100 & 268987 & 56.572 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 15217100 & 268987 & 56.572 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 15244900 & 264655 & 57.603 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 15244900 & 255732 & 59.6129 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 15244900 & 255732 & 59.6129 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 15315700 & 235918 & 64.9196 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 15315700 & 235918 & 64.9196 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 15315700 & 235918 & 64.9196 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 15358700 & 230426 & 66.6535 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 15358700 & 230426 & 66.6535 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 15358700 & 217852 & 70.5007 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 15308100 & 211035 & 72.5385 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 15308100 & 211035 & 72.5385 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 15308100 & 211035 & 72.5385 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 15308100 & 211035 & 72.5385 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 15247500 & 188127 & 81.0487 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 15247500 & 188127 & 81.0487 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 15247500 & 172309 & 88.4888 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 15247500 & 172309 & 88.4888 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 15318200 & 164282 & 93.2437 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 15318200 & 164282 & 93.2437 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 15242400 & 155163 & 98.2348 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 15242400 & 155163 & 98.2348 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 15161500 & 145817 & 103.976 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 15244900 & 136484 & 111.698 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 15244900 & 136484 & 111.698 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 15156500 & 126494 & 119.82 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 15247500 & 116589 & 130.78 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 15326500 & 307892 & 49.7789 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 15322000 & 298462 & 51.3365 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 15312000 & 289016 & 52.9798 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 15304300 & 280315 & 54.5967 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 15290700 & 272928 & 56.0246 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 15276500 & 264545 & 57.7464 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 15264700 & 258422 & 59.0687 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 15255300 & 252179 & 60.4937 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 15257600 & 247789 & 61.5749 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 15263100 & 243389 & 62.7105 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 15268900 & 238338 & 64.0639 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 15271600 & 233277 & 65.4656 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 15274600 & 228909 & 66.7278 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 15277700 & 223842 & 68.252 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 15273900 & 220997 & 69.1136 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 15269900 & 217640 & 70.1613 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 15265800 & 213682 & 71.4416 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 15257600 & 209801 & 72.7241 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 15248900 & 205190 & 74.3159 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 15239700 & 201575 & 75.6033 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 15234100 & 198254 & 76.8414 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 15228200 & 194230 & 78.4027 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 15221900 & 189349 & 80.3905 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 15215100 & 183406 & 82.9586 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 15212600 & 179898 & 84.5624 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 15209900 & 175539 & 86.6466 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 15207000 & 172695 & 88.057 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 15203900 & 169065 & 89.9295 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 15195100 & 165759 & 91.6699 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 15185500 & 161473 & 94.0436 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 15181100 & 157726 & 96.2498 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 15176200 & 152790 & 99.327 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 15177400 & 148296 & 102.345 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 15171900 & 144288 & 105.15 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 15165800 & 138790 & 109.271 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 15166600 & 133850 & 113.31 \tabularnewline
Median & 15014900 &  &  \tabularnewline
Midrange & 15287900 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 15209900 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 15209900 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 15209900 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 15209900 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 15209900 &  &  \tabularnewline
Midmean - Closest Observation & 15209900 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 15209900 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 15209900 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307169&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]15325800[/C][C]319611[/C][C]47.9515[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]14957600[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]14573400[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]15678400[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]15330900[/C][C]316278[/C][C]48.4727[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]15341000[/C][C]314300[/C][C]48.81[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]15333400[/C][C]309691[/C][C]49.5119[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]15353600[/C][C]302408[/C][C]50.7712[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]15353600[/C][C]302408[/C][C]50.7712[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]15338500[/C][C]288889[/C][C]53.0946[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]15320800[/C][C]285692[/C][C]53.6269[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]15239900[/C][C]272357[/C][C]55.9554[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]15217100[/C][C]268987[/C][C]56.572[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]15217100[/C][C]268987[/C][C]56.572[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]15244900[/C][C]264655[/C][C]57.603[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]15244900[/C][C]255732[/C][C]59.6129[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]15244900[/C][C]255732[/C][C]59.6129[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]15315700[/C][C]235918[/C][C]64.9196[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]15315700[/C][C]235918[/C][C]64.9196[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]15315700[/C][C]235918[/C][C]64.9196[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]15358700[/C][C]230426[/C][C]66.6535[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]15358700[/C][C]230426[/C][C]66.6535[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]15358700[/C][C]217852[/C][C]70.5007[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]15308100[/C][C]211035[/C][C]72.5385[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]15308100[/C][C]211035[/C][C]72.5385[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]15308100[/C][C]211035[/C][C]72.5385[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]15308100[/C][C]211035[/C][C]72.5385[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]15247500[/C][C]188127[/C][C]81.0487[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]15247500[/C][C]188127[/C][C]81.0487[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]15247500[/C][C]172309[/C][C]88.4888[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]15247500[/C][C]172309[/C][C]88.4888[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]15318200[/C][C]164282[/C][C]93.2437[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]15318200[/C][C]164282[/C][C]93.2437[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]15242400[/C][C]155163[/C][C]98.2348[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]15242400[/C][C]155163[/C][C]98.2348[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]15161500[/C][C]145817[/C][C]103.976[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]15244900[/C][C]136484[/C][C]111.698[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]15244900[/C][C]136484[/C][C]111.698[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]15156500[/C][C]126494[/C][C]119.82[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]15247500[/C][C]116589[/C][C]130.78[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]15326500[/C][C]307892[/C][C]49.7789[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]15322000[/C][C]298462[/C][C]51.3365[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]15312000[/C][C]289016[/C][C]52.9798[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]15304300[/C][C]280315[/C][C]54.5967[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]15290700[/C][C]272928[/C][C]56.0246[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]15276500[/C][C]264545[/C][C]57.7464[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]15264700[/C][C]258422[/C][C]59.0687[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]15255300[/C][C]252179[/C][C]60.4937[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]15257600[/C][C]247789[/C][C]61.5749[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]15263100[/C][C]243389[/C][C]62.7105[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]15268900[/C][C]238338[/C][C]64.0639[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]15271600[/C][C]233277[/C][C]65.4656[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]15274600[/C][C]228909[/C][C]66.7278[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]15277700[/C][C]223842[/C][C]68.252[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]15273900[/C][C]220997[/C][C]69.1136[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]15269900[/C][C]217640[/C][C]70.1613[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]15265800[/C][C]213682[/C][C]71.4416[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]15257600[/C][C]209801[/C][C]72.7241[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]15248900[/C][C]205190[/C][C]74.3159[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]15239700[/C][C]201575[/C][C]75.6033[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]15234100[/C][C]198254[/C][C]76.8414[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]15228200[/C][C]194230[/C][C]78.4027[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]15221900[/C][C]189349[/C][C]80.3905[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]15215100[/C][C]183406[/C][C]82.9586[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]15212600[/C][C]179898[/C][C]84.5624[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]15209900[/C][C]175539[/C][C]86.6466[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]15207000[/C][C]172695[/C][C]88.057[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]15203900[/C][C]169065[/C][C]89.9295[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]15195100[/C][C]165759[/C][C]91.6699[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]15185500[/C][C]161473[/C][C]94.0436[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]15181100[/C][C]157726[/C][C]96.2498[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]15176200[/C][C]152790[/C][C]99.327[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]15177400[/C][C]148296[/C][C]102.345[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]15171900[/C][C]144288[/C][C]105.15[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]15165800[/C][C]138790[/C][C]109.271[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]15166600[/C][C]133850[/C][C]113.31[/C][/ROW]
[ROW][C]Median[/C][C]15014900[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]15287900[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]15209900[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]15209900[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]15209900[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]15209900[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]15209900[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]15209900[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]15209900[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]15209900[/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=307169&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307169&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 Mean1532580031961147.9515
Geometric Mean14957600
Harmonic Mean14573400
Quadratic Mean15678400
Winsorized Mean ( 1 / 36 )1533090031627848.4727
Winsorized Mean ( 2 / 36 )1534100031430048.81
Winsorized Mean ( 3 / 36 )1533340030969149.5119
Winsorized Mean ( 4 / 36 )1535360030240850.7712
Winsorized Mean ( 5 / 36 )1535360030240850.7712
Winsorized Mean ( 6 / 36 )1533850028888953.0946
Winsorized Mean ( 7 / 36 )1532080028569253.6269
Winsorized Mean ( 8 / 36 )1523990027235755.9554
Winsorized Mean ( 9 / 36 )1521710026898756.572
Winsorized Mean ( 10 / 36 )1521710026898756.572
Winsorized Mean ( 11 / 36 )1524490026465557.603
Winsorized Mean ( 12 / 36 )1524490025573259.6129
Winsorized Mean ( 13 / 36 )1524490025573259.6129
Winsorized Mean ( 14 / 36 )1531570023591864.9196
Winsorized Mean ( 15 / 36 )1531570023591864.9196
Winsorized Mean ( 16 / 36 )1531570023591864.9196
Winsorized Mean ( 17 / 36 )1535870023042666.6535
Winsorized Mean ( 18 / 36 )1535870023042666.6535
Winsorized Mean ( 19 / 36 )1535870021785270.5007
Winsorized Mean ( 20 / 36 )1530810021103572.5385
Winsorized Mean ( 21 / 36 )1530810021103572.5385
Winsorized Mean ( 22 / 36 )1530810021103572.5385
Winsorized Mean ( 23 / 36 )1530810021103572.5385
Winsorized Mean ( 24 / 36 )1524750018812781.0487
Winsorized Mean ( 25 / 36 )1524750018812781.0487
Winsorized Mean ( 26 / 36 )1524750017230988.4888
Winsorized Mean ( 27 / 36 )1524750017230988.4888
Winsorized Mean ( 28 / 36 )1531820016428293.2437
Winsorized Mean ( 29 / 36 )1531820016428293.2437
Winsorized Mean ( 30 / 36 )1524240015516398.2348
Winsorized Mean ( 31 / 36 )1524240015516398.2348
Winsorized Mean ( 32 / 36 )15161500145817103.976
Winsorized Mean ( 33 / 36 )15244900136484111.698
Winsorized Mean ( 34 / 36 )15244900136484111.698
Winsorized Mean ( 35 / 36 )15156500126494119.82
Winsorized Mean ( 36 / 36 )15247500116589130.78
Trimmed Mean ( 1 / 36 )1532650030789249.7789
Trimmed Mean ( 2 / 36 )1532200029846251.3365
Trimmed Mean ( 3 / 36 )1531200028901652.9798
Trimmed Mean ( 4 / 36 )1530430028031554.5967
Trimmed Mean ( 5 / 36 )1529070027292856.0246
Trimmed Mean ( 6 / 36 )1527650026454557.7464
Trimmed Mean ( 7 / 36 )1526470025842259.0687
Trimmed Mean ( 8 / 36 )1525530025217960.4937
Trimmed Mean ( 9 / 36 )1525760024778961.5749
Trimmed Mean ( 10 / 36 )1526310024338962.7105
Trimmed Mean ( 11 / 36 )1526890023833864.0639
Trimmed Mean ( 12 / 36 )1527160023327765.4656
Trimmed Mean ( 13 / 36 )1527460022890966.7278
Trimmed Mean ( 14 / 36 )1527770022384268.252
Trimmed Mean ( 15 / 36 )1527390022099769.1136
Trimmed Mean ( 16 / 36 )1526990021764070.1613
Trimmed Mean ( 17 / 36 )1526580021368271.4416
Trimmed Mean ( 18 / 36 )1525760020980172.7241
Trimmed Mean ( 19 / 36 )1524890020519074.3159
Trimmed Mean ( 20 / 36 )1523970020157575.6033
Trimmed Mean ( 21 / 36 )1523410019825476.8414
Trimmed Mean ( 22 / 36 )1522820019423078.4027
Trimmed Mean ( 23 / 36 )1522190018934980.3905
Trimmed Mean ( 24 / 36 )1521510018340682.9586
Trimmed Mean ( 25 / 36 )1521260017989884.5624
Trimmed Mean ( 26 / 36 )1520990017553986.6466
Trimmed Mean ( 27 / 36 )1520700017269588.057
Trimmed Mean ( 28 / 36 )1520390016906589.9295
Trimmed Mean ( 29 / 36 )1519510016575991.6699
Trimmed Mean ( 30 / 36 )1518550016147394.0436
Trimmed Mean ( 31 / 36 )1518110015772696.2498
Trimmed Mean ( 32 / 36 )1517620015279099.327
Trimmed Mean ( 33 / 36 )15177400148296102.345
Trimmed Mean ( 34 / 36 )15171900144288105.15
Trimmed Mean ( 35 / 36 )15165800138790109.271
Trimmed Mean ( 36 / 36 )15166600133850113.31
Median15014900
Midrange15287900
Midmean - Weighted Average at Xnp15209900
Midmean - Weighted Average at X(n+1)p15209900
Midmean - Empirical Distribution Function15209900
Midmean - Empirical Distribution Function - Averaging15209900
Midmean - Empirical Distribution Function - Interpolation15209900
Midmean - Closest Observation15209900
Midmean - True Basic - Statistics Graphics Toolkit15209900
Midmean - MS Excel (old versions)15209900
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,'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')