Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 20 Oct 2009 12:46:56 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Oct/20/t1256064503ljsfnci3wzc35ah.htm/, Retrieved Thu, 02 May 2024 15:03:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=48985, Retrieved Thu, 02 May 2024 15:03:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
F RMPD  [Univariate Explorative Data Analysis] [Colombia Coffee] [2008-01-07 14:21:11] [74be16979710d4c4e7c6647856088456]
F RMPD    [Univariate Data Series] [] [2009-10-14 08:30:28] [74be16979710d4c4e7c6647856088456]
- RMPD        [Central Tendency] [E[t] bij Y[t]=C+e[t]] [2009-10-20 18:46:56] [9a3898f49d4e2f0208d1968305d88f0a] [Current]
Feedback Forum

Post a new message
Dataseries X:
-402.63
-1216.13
-474.53
-466.63
-745.83
-628.33
-877.53
-709.33
-143.63
-292.23
-162.03
177.77
82.77
-810.53
377.07
-228.23
-2.63
-199.23
-370.83
-191.03
543.37
-449.43
338.77
-49.93
61.57
-814.63
74.17
120.87
174.37
-121.33
-151.43
35.17
789.57
-156.63
323.67
525.47
930.07
146.37
252.67
745.17
227.77
170.47
145.27
246.07
436.57
1032.27
855.07
1056.17
1631.47
-117.03
1318.77
805.37
-396.53
-347.83
-1048.53
-521.53
-213.53
-562.13
-509.23
-73.83
-169.23




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=48985&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=48985&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=48985&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean0.0011475409836097174.07510306213941.54915880798313e-05
Geometric MeanNaN
Harmonic Mean-164.059768941246
Quadratic Mean573.783281057676
Winsorized Mean ( 1 / 20 )-2.3775409836065571.6328308589465-0.0331906606942313
Winsorized Mean ( 2 / 20 )-5.3808196721311467.8977217248558-0.0792488987176332
Winsorized Mean ( 3 / 20 )-3.462786885245966.9494369488402-0.0517224198299384
Winsorized Mean ( 4 / 20 )-9.895573770491865.2252343506272-0.151713886029091
Winsorized Mean ( 5 / 20 )-10.739836065573862.7182081398003-0.171239523323664
Winsorized Mean ( 6 / 20 )-12.038196721311560.9157176095439-0.197620535285714
Winsorized Mean ( 7 / 20 )-4.5562295081967158.7994004328768-0.0774876865181293
Winsorized Mean ( 8 / 20 )-1.6972131147540956.0041364456552-0.0303051385570604
Winsorized Mean ( 9 / 20 )-25.480819672131148.7656660339216-0.522515567703035
Winsorized Mean ( 10 / 20 )-26.398852459016447.8579380298022-0.551608647296447
Winsorized Mean ( 11 / 20 )-36.172622950819743.8240824740699-0.825405140477785
Winsorized Mean ( 12 / 20 )-46.323442622950841.5149300202216-1.11582610401576
Winsorized Mean ( 13 / 20 )-50.820163934426239.5330567014242-1.28551061250458
Winsorized Mean ( 14 / 20 )-43.544754098360637.1955643865387-1.17069749623479
Winsorized Mean ( 15 / 20 )-59.503770491803334.1821049674966-1.74078719108682
Winsorized Mean ( 16 / 20 )-54.493934426229532.8227396046071-1.66024942106236
Winsorized Mean ( 17 / 20 )-53.184098360655731.0263054769764-1.71416150079879
Winsorized Mean ( 18 / 20 )-51.531639344262326.2825601854265-1.96067806867751
Winsorized Mean ( 19 / 20 )-32.656229508196723.1975089228895-1.40774725496383
Winsorized Mean ( 20 / 20 )-29.115245901639322.3368588077927-1.30346196625829
Trimmed Mean ( 1 / 20 )-7.0384745762711868.2486794878123-0.103129827992175
Trimmed Mean ( 2 / 20 )-12.026491228070264.051255564424-0.187763551582119
Trimmed Mean ( 3 / 20 )-15.711818181818261.421146847592-0.255804702260035
Trimmed Mean ( 4 / 20 )-20.411132075471758.6086518487529-0.348261415876707
Trimmed Mean ( 5 / 20 )-23.555490196078455.7957834405979-0.422173303134213
Trimmed Mean ( 6 / 20 )-26.746326530612253.1508090046437-0.503215793540893
Trimmed Mean ( 7 / 20 )-29.927872340425550.3714518255482-0.594143532810508
Trimmed Mean ( 8 / 20 )-34.841111111111147.433409061272-0.7345268198224
Trimmed Mean ( 9 / 20 )-40.718372093023344.4414194044870-0.916225733530737
Trimmed Mean ( 10 / 20 )-43.237317073170742.7294566800668-1.01188548679443
Trimmed Mean ( 11 / 20 )-45.871025641025640.6880341507087-1.12738367921928
Trimmed Mean ( 12 / 20 )-47.324594594594639.1050296961494-1.21019201269791
Trimmed Mean ( 13 / 20 )-47.4737.5843066212705-1.26302715860494
Trimmed Mean ( 14 / 20 )-46.993636363636436.0214800233364-1.30460037547573
Trimmed Mean ( 15 / 20 )-47.478387096774234.4906659871314-1.37655756239930
Trimmed Mean ( 16 / 20 )-45.792068965517233.187129313393-1.37981410001128
Trimmed Mean ( 17 / 20 )-44.563333333333331.6554451552526-1.40776201739620
Trimmed Mean ( 18 / 20 )-43.32629.9242596566732-1.44785536875724
Trimmed Mean ( 19 / 20 )-42.116956521739129.029306647604-1.45084266162504
Trimmed Mean ( 20 / 20 )-43.563333333333328.6546732940249-1.52028721061766
Median-73.83
Midrange207.67
Midmean - Weighted Average at Xnp-57.4833333333334
Midmean - Weighted Average at X(n+1)p-47.4783870967742
Midmean - Empirical Distribution Function-47.4783870967742
Midmean - Empirical Distribution Function - Averaging-47.4783870967742
Midmean - Empirical Distribution Function - Interpolation-47.4783870967742
Midmean - Closest Observation-58.576875
Midmean - True Basic - Statistics Graphics Toolkit-47.4783870967742
Midmean - MS Excel (old versions)-47.4783870967742
Number of observations61

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 0.00114754098360971 & 74.0751030621394 & 1.54915880798313e-05 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & -164.059768941246 &  &  \tabularnewline
Quadratic Mean & 573.783281057676 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & -2.37754098360655 & 71.6328308589465 & -0.0331906606942313 \tabularnewline
Winsorized Mean ( 2 / 20 ) & -5.38081967213114 & 67.8977217248558 & -0.0792488987176332 \tabularnewline
Winsorized Mean ( 3 / 20 ) & -3.4627868852459 & 66.9494369488402 & -0.0517224198299384 \tabularnewline
Winsorized Mean ( 4 / 20 ) & -9.8955737704918 & 65.2252343506272 & -0.151713886029091 \tabularnewline
Winsorized Mean ( 5 / 20 ) & -10.7398360655738 & 62.7182081398003 & -0.171239523323664 \tabularnewline
Winsorized Mean ( 6 / 20 ) & -12.0381967213115 & 60.9157176095439 & -0.197620535285714 \tabularnewline
Winsorized Mean ( 7 / 20 ) & -4.55622950819671 & 58.7994004328768 & -0.0774876865181293 \tabularnewline
Winsorized Mean ( 8 / 20 ) & -1.69721311475409 & 56.0041364456552 & -0.0303051385570604 \tabularnewline
Winsorized Mean ( 9 / 20 ) & -25.4808196721311 & 48.7656660339216 & -0.522515567703035 \tabularnewline
Winsorized Mean ( 10 / 20 ) & -26.3988524590164 & 47.8579380298022 & -0.551608647296447 \tabularnewline
Winsorized Mean ( 11 / 20 ) & -36.1726229508197 & 43.8240824740699 & -0.825405140477785 \tabularnewline
Winsorized Mean ( 12 / 20 ) & -46.3234426229508 & 41.5149300202216 & -1.11582610401576 \tabularnewline
Winsorized Mean ( 13 / 20 ) & -50.8201639344262 & 39.5330567014242 & -1.28551061250458 \tabularnewline
Winsorized Mean ( 14 / 20 ) & -43.5447540983606 & 37.1955643865387 & -1.17069749623479 \tabularnewline
Winsorized Mean ( 15 / 20 ) & -59.5037704918033 & 34.1821049674966 & -1.74078719108682 \tabularnewline
Winsorized Mean ( 16 / 20 ) & -54.4939344262295 & 32.8227396046071 & -1.66024942106236 \tabularnewline
Winsorized Mean ( 17 / 20 ) & -53.1840983606557 & 31.0263054769764 & -1.71416150079879 \tabularnewline
Winsorized Mean ( 18 / 20 ) & -51.5316393442623 & 26.2825601854265 & -1.96067806867751 \tabularnewline
Winsorized Mean ( 19 / 20 ) & -32.6562295081967 & 23.1975089228895 & -1.40774725496383 \tabularnewline
Winsorized Mean ( 20 / 20 ) & -29.1152459016393 & 22.3368588077927 & -1.30346196625829 \tabularnewline
Trimmed Mean ( 1 / 20 ) & -7.03847457627118 & 68.2486794878123 & -0.103129827992175 \tabularnewline
Trimmed Mean ( 2 / 20 ) & -12.0264912280702 & 64.051255564424 & -0.187763551582119 \tabularnewline
Trimmed Mean ( 3 / 20 ) & -15.7118181818182 & 61.421146847592 & -0.255804702260035 \tabularnewline
Trimmed Mean ( 4 / 20 ) & -20.4111320754717 & 58.6086518487529 & -0.348261415876707 \tabularnewline
Trimmed Mean ( 5 / 20 ) & -23.5554901960784 & 55.7957834405979 & -0.422173303134213 \tabularnewline
Trimmed Mean ( 6 / 20 ) & -26.7463265306122 & 53.1508090046437 & -0.503215793540893 \tabularnewline
Trimmed Mean ( 7 / 20 ) & -29.9278723404255 & 50.3714518255482 & -0.594143532810508 \tabularnewline
Trimmed Mean ( 8 / 20 ) & -34.8411111111111 & 47.433409061272 & -0.7345268198224 \tabularnewline
Trimmed Mean ( 9 / 20 ) & -40.7183720930233 & 44.4414194044870 & -0.916225733530737 \tabularnewline
Trimmed Mean ( 10 / 20 ) & -43.2373170731707 & 42.7294566800668 & -1.01188548679443 \tabularnewline
Trimmed Mean ( 11 / 20 ) & -45.8710256410256 & 40.6880341507087 & -1.12738367921928 \tabularnewline
Trimmed Mean ( 12 / 20 ) & -47.3245945945946 & 39.1050296961494 & -1.21019201269791 \tabularnewline
Trimmed Mean ( 13 / 20 ) & -47.47 & 37.5843066212705 & -1.26302715860494 \tabularnewline
Trimmed Mean ( 14 / 20 ) & -46.9936363636364 & 36.0214800233364 & -1.30460037547573 \tabularnewline
Trimmed Mean ( 15 / 20 ) & -47.4783870967742 & 34.4906659871314 & -1.37655756239930 \tabularnewline
Trimmed Mean ( 16 / 20 ) & -45.7920689655172 & 33.187129313393 & -1.37981410001128 \tabularnewline
Trimmed Mean ( 17 / 20 ) & -44.5633333333333 & 31.6554451552526 & -1.40776201739620 \tabularnewline
Trimmed Mean ( 18 / 20 ) & -43.326 & 29.9242596566732 & -1.44785536875724 \tabularnewline
Trimmed Mean ( 19 / 20 ) & -42.1169565217391 & 29.029306647604 & -1.45084266162504 \tabularnewline
Trimmed Mean ( 20 / 20 ) & -43.5633333333333 & 28.6546732940249 & -1.52028721061766 \tabularnewline
Median & -73.83 &  &  \tabularnewline
Midrange & 207.67 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -57.4833333333334 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -47.4783870967742 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -47.4783870967742 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -47.4783870967742 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -47.4783870967742 &  &  \tabularnewline
Midmean - Closest Observation & -58.576875 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -47.4783870967742 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -47.4783870967742 &  &  \tabularnewline
Number of observations & 61 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=48985&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]0.00114754098360971[/C][C]74.0751030621394[/C][C]1.54915880798313e-05[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]-164.059768941246[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]573.783281057676[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]-2.37754098360655[/C][C]71.6328308589465[/C][C]-0.0331906606942313[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]-5.38081967213114[/C][C]67.8977217248558[/C][C]-0.0792488987176332[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]-3.4627868852459[/C][C]66.9494369488402[/C][C]-0.0517224198299384[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]-9.8955737704918[/C][C]65.2252343506272[/C][C]-0.151713886029091[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]-10.7398360655738[/C][C]62.7182081398003[/C][C]-0.171239523323664[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]-12.0381967213115[/C][C]60.9157176095439[/C][C]-0.197620535285714[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]-4.55622950819671[/C][C]58.7994004328768[/C][C]-0.0774876865181293[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]-1.69721311475409[/C][C]56.0041364456552[/C][C]-0.0303051385570604[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]-25.4808196721311[/C][C]48.7656660339216[/C][C]-0.522515567703035[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]-26.3988524590164[/C][C]47.8579380298022[/C][C]-0.551608647296447[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]-36.1726229508197[/C][C]43.8240824740699[/C][C]-0.825405140477785[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]-46.3234426229508[/C][C]41.5149300202216[/C][C]-1.11582610401576[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]-50.8201639344262[/C][C]39.5330567014242[/C][C]-1.28551061250458[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]-43.5447540983606[/C][C]37.1955643865387[/C][C]-1.17069749623479[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]-59.5037704918033[/C][C]34.1821049674966[/C][C]-1.74078719108682[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]-54.4939344262295[/C][C]32.8227396046071[/C][C]-1.66024942106236[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]-53.1840983606557[/C][C]31.0263054769764[/C][C]-1.71416150079879[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]-51.5316393442623[/C][C]26.2825601854265[/C][C]-1.96067806867751[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]-32.6562295081967[/C][C]23.1975089228895[/C][C]-1.40774725496383[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]-29.1152459016393[/C][C]22.3368588077927[/C][C]-1.30346196625829[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]-7.03847457627118[/C][C]68.2486794878123[/C][C]-0.103129827992175[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]-12.0264912280702[/C][C]64.051255564424[/C][C]-0.187763551582119[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]-15.7118181818182[/C][C]61.421146847592[/C][C]-0.255804702260035[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]-20.4111320754717[/C][C]58.6086518487529[/C][C]-0.348261415876707[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]-23.5554901960784[/C][C]55.7957834405979[/C][C]-0.422173303134213[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]-26.7463265306122[/C][C]53.1508090046437[/C][C]-0.503215793540893[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]-29.9278723404255[/C][C]50.3714518255482[/C][C]-0.594143532810508[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]-34.8411111111111[/C][C]47.433409061272[/C][C]-0.7345268198224[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]-40.7183720930233[/C][C]44.4414194044870[/C][C]-0.916225733530737[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]-43.2373170731707[/C][C]42.7294566800668[/C][C]-1.01188548679443[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]-45.8710256410256[/C][C]40.6880341507087[/C][C]-1.12738367921928[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]-47.3245945945946[/C][C]39.1050296961494[/C][C]-1.21019201269791[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]-47.47[/C][C]37.5843066212705[/C][C]-1.26302715860494[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]-46.9936363636364[/C][C]36.0214800233364[/C][C]-1.30460037547573[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]-47.4783870967742[/C][C]34.4906659871314[/C][C]-1.37655756239930[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]-45.7920689655172[/C][C]33.187129313393[/C][C]-1.37981410001128[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]-44.5633333333333[/C][C]31.6554451552526[/C][C]-1.40776201739620[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]-43.326[/C][C]29.9242596566732[/C][C]-1.44785536875724[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]-42.1169565217391[/C][C]29.029306647604[/C][C]-1.45084266162504[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]-43.5633333333333[/C][C]28.6546732940249[/C][C]-1.52028721061766[/C][/ROW]
[ROW][C]Median[/C][C]-73.83[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]207.67[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-57.4833333333334[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-47.4783870967742[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-47.4783870967742[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-47.4783870967742[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-47.4783870967742[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-58.576875[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-47.4783870967742[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-47.4783870967742[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]61[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=48985&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=48985&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 Mean0.0011475409836097174.07510306213941.54915880798313e-05
Geometric MeanNaN
Harmonic Mean-164.059768941246
Quadratic Mean573.783281057676
Winsorized Mean ( 1 / 20 )-2.3775409836065571.6328308589465-0.0331906606942313
Winsorized Mean ( 2 / 20 )-5.3808196721311467.8977217248558-0.0792488987176332
Winsorized Mean ( 3 / 20 )-3.462786885245966.9494369488402-0.0517224198299384
Winsorized Mean ( 4 / 20 )-9.895573770491865.2252343506272-0.151713886029091
Winsorized Mean ( 5 / 20 )-10.739836065573862.7182081398003-0.171239523323664
Winsorized Mean ( 6 / 20 )-12.038196721311560.9157176095439-0.197620535285714
Winsorized Mean ( 7 / 20 )-4.5562295081967158.7994004328768-0.0774876865181293
Winsorized Mean ( 8 / 20 )-1.6972131147540956.0041364456552-0.0303051385570604
Winsorized Mean ( 9 / 20 )-25.480819672131148.7656660339216-0.522515567703035
Winsorized Mean ( 10 / 20 )-26.398852459016447.8579380298022-0.551608647296447
Winsorized Mean ( 11 / 20 )-36.172622950819743.8240824740699-0.825405140477785
Winsorized Mean ( 12 / 20 )-46.323442622950841.5149300202216-1.11582610401576
Winsorized Mean ( 13 / 20 )-50.820163934426239.5330567014242-1.28551061250458
Winsorized Mean ( 14 / 20 )-43.544754098360637.1955643865387-1.17069749623479
Winsorized Mean ( 15 / 20 )-59.503770491803334.1821049674966-1.74078719108682
Winsorized Mean ( 16 / 20 )-54.493934426229532.8227396046071-1.66024942106236
Winsorized Mean ( 17 / 20 )-53.184098360655731.0263054769764-1.71416150079879
Winsorized Mean ( 18 / 20 )-51.531639344262326.2825601854265-1.96067806867751
Winsorized Mean ( 19 / 20 )-32.656229508196723.1975089228895-1.40774725496383
Winsorized Mean ( 20 / 20 )-29.115245901639322.3368588077927-1.30346196625829
Trimmed Mean ( 1 / 20 )-7.0384745762711868.2486794878123-0.103129827992175
Trimmed Mean ( 2 / 20 )-12.026491228070264.051255564424-0.187763551582119
Trimmed Mean ( 3 / 20 )-15.711818181818261.421146847592-0.255804702260035
Trimmed Mean ( 4 / 20 )-20.411132075471758.6086518487529-0.348261415876707
Trimmed Mean ( 5 / 20 )-23.555490196078455.7957834405979-0.422173303134213
Trimmed Mean ( 6 / 20 )-26.746326530612253.1508090046437-0.503215793540893
Trimmed Mean ( 7 / 20 )-29.927872340425550.3714518255482-0.594143532810508
Trimmed Mean ( 8 / 20 )-34.841111111111147.433409061272-0.7345268198224
Trimmed Mean ( 9 / 20 )-40.718372093023344.4414194044870-0.916225733530737
Trimmed Mean ( 10 / 20 )-43.237317073170742.7294566800668-1.01188548679443
Trimmed Mean ( 11 / 20 )-45.871025641025640.6880341507087-1.12738367921928
Trimmed Mean ( 12 / 20 )-47.324594594594639.1050296961494-1.21019201269791
Trimmed Mean ( 13 / 20 )-47.4737.5843066212705-1.26302715860494
Trimmed Mean ( 14 / 20 )-46.993636363636436.0214800233364-1.30460037547573
Trimmed Mean ( 15 / 20 )-47.478387096774234.4906659871314-1.37655756239930
Trimmed Mean ( 16 / 20 )-45.792068965517233.187129313393-1.37981410001128
Trimmed Mean ( 17 / 20 )-44.563333333333331.6554451552526-1.40776201739620
Trimmed Mean ( 18 / 20 )-43.32629.9242596566732-1.44785536875724
Trimmed Mean ( 19 / 20 )-42.116956521739129.029306647604-1.45084266162504
Trimmed Mean ( 20 / 20 )-43.563333333333328.6546732940249-1.52028721061766
Median-73.83
Midrange207.67
Midmean - Weighted Average at Xnp-57.4833333333334
Midmean - Weighted Average at X(n+1)p-47.4783870967742
Midmean - Empirical Distribution Function-47.4783870967742
Midmean - Empirical Distribution Function - Averaging-47.4783870967742
Midmean - Empirical Distribution Function - Interpolation-47.4783870967742
Midmean - Closest Observation-58.576875
Midmean - True Basic - Statistics Graphics Toolkit-47.4783870967742
Midmean - MS Excel (old versions)-47.4783870967742
Number of observations61



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')