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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 27 Oct 2008 03:27:41 -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/2008/Oct/27/t12250998016q78be0o5ny57vf.htm/, Retrieved Fri, 17 May 2024 02:09:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19137, Retrieved Fri, 17 May 2024 02:09:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Central Tendency] [Q6 Distributions] [2007-10-22 19:20:42] [b731da8b544846036771bbf9bf2f34ce]
F    D    [Central Tendency] [Q6 Afwijking tov ...] [2008-10-27 09:27:41] [e4cb5a8878d0401c2e8d19a1768b515b] [Current]
Feedback Forum
2008-10-31 20:18:01 [Jan Van Riet] [reply
Deze berekening klopt.

We gaan in feite de central tendency onderzoeken van de residus (dus tijdreeks - gemiddelde).

Dit doen we door dit ofwel in een Excel-file te berekenen of door dit rechtstreeks in de R-code aan te passen (x <- x - gemiddelde).

Het resultaat is dat het gemiddelde inderdaad dicht bij 0 ligt.
2008-11-03 08:30:43 [Glenn De Maeyer] [reply
We gebruiken hier een nieuwe tijdreeks nl. de tijdreeks (clothing production/total production) - het gemiddelde van de reeks. Het gemiddelde van de random component van deze reeks is inderdaad zeer dichtbij 0. We kunnen dus stellen dat we met een robuust zitten en dat deze reeks niet gevoelig is aan outliers.

Post a new message
Dataseries X:
0,13
0,06
0,06
0,06
0,20
-0,01
0,17
0,13
0,05
-0,07
0,12
0,13
0,05
0,02
-0,03
-0,04
0,16
-0,05
0,16
0,05
-0,05
-0,12
0,13
0,11
-0,01
-0,01
-0,09
-0,07
0,07
-0,12
0,02
-0,02
-0,04
-0,13
0,06
0,06
0,02
-0,04
-0,09
-0,04
0,06
-0,11
0,01
-0,05
-0,06
-0,15
-0,03
0,05
0,01
-0,08
-0,11
-0,10
0,06
-0,12
-0,05
-0,09
-0,08
-0,18
-0,01
0,04
0,01




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19137&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19137&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19137&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean0.0001639344262295090.01140532854874630.0143734944178815
Geometric MeanNaN
Harmonic Mean-0.526741926658227
Quadratic Mean0.0883454471536982
Winsorized Mean ( 1 / 20 )0.0001639344262295090.01115095576113610.0147013789437550
Winsorized Mean ( 2 / 20 )0.0004918032786885250.01093054633321340.0449934764188447
Winsorized Mean ( 3 / 20 )0.000983606557377050.01083584649630150.0907733934504126
Winsorized Mean ( 4 / 20 )-0.0009836065573770480.0103878473501538-0.0946881990292709
Winsorized Mean ( 5 / 20 )-0.0009836065573770480.0103878473501538-0.0946881990292709
Winsorized Mean ( 6 / 20 )00.01020553798015960
Winsorized Mean ( 7 / 20 )00.01020553798015960
Winsorized Mean ( 8 / 20 )-1.82003774528714e-180.00970043095206279-1.87624421459349e-16
Winsorized Mean ( 9 / 20 )00.009152622127198230
Winsorized Mean ( 10 / 20 )-0.006557377049180320.00796126292910359-0.823660405085837
Winsorized Mean ( 11 / 20 )-0.008360655737704920.00768285411969585-1.08822263281968
Winsorized Mean ( 12 / 20 )-0.006393442622950820.00734412812133488-0.87055161856146
Winsorized Mean ( 13 / 20 )-0.006393442622950820.00734412812133488-0.870551618561461
Winsorized Mean ( 14 / 20 )-0.004098360655737710.006971358458222-0.58788551475274
Winsorized Mean ( 15 / 20 )-0.004098360655737710.006971358458222-0.58788551475274
Winsorized Mean ( 16 / 20 )-0.001475409836065580.00656966062607012-0.224579307827678
Winsorized Mean ( 17 / 20 )0.001311475409836060.00616917867830170.212585090856389
Winsorized Mean ( 18 / 20 )-0.001639344262295080.00571251300231139-0.286974272379209
Winsorized Mean ( 19 / 20 )-0.001639344262295080.00571251300231139-0.286974272379209
Winsorized Mean ( 20 / 20 )-0.001639344262295080.00571251300231139-0.286974272379210
Trimmed Mean ( 1 / 20 )-0.0001694915254237280.0108614663342786-0.0156048474678613
Trimmed Mean ( 2 / 20 )-0.0005263157894736840.0105054617989165-0.0500992530883282
Trimmed Mean ( 3 / 20 )-0.001090909090909090.0102121361987721-0.106824769046878
Trimmed Mean ( 4 / 20 )-0.001886792452830190.00989075525230874-0.190763233413320
Trimmed Mean ( 5 / 20 )-0.002156862745098040.00966624904638206-0.22313337208142
Trimmed Mean ( 6 / 20 )-0.002448979591836740.00937924784600978-0.26110618165172
Trimmed Mean ( 7 / 20 )-0.002978723404255320.00906811970417226-0.328483026407868
Trimmed Mean ( 8 / 20 )-0.003555555555555560.00866407627695442-0.410379068916207
Trimmed Mean ( 9 / 20 )-0.004186046511627910.0082876882238165-0.505092179939682
Trimmed Mean ( 10 / 20 )-0.00487804878048780.00794893727533798-0.613673074968426
Trimmed Mean ( 11 / 20 )-0.004615384615384620.00782609698644965-0.589742833928053
Trimmed Mean ( 12 / 20 )-0.004054054054054060.00771546805879496-0.525444992210523
Trimmed Mean ( 13 / 20 )-0.003714285714285720.00763765235484029-0.48631248736162
Trimmed Mean ( 14 / 20 )-0.003333333333333330.00750841279008171-0.443946467319501
Trimmed Mean ( 15 / 20 )-0.003225806451612900.00741093491372887-0.435276586444856
Trimmed Mean ( 16 / 20 )-0.003103448275862070.00724489710472786-0.42836333366789
Trimmed Mean ( 17 / 20 )-0.003333333333333330.00710122175596217-0.469402794038177
Trimmed Mean ( 18 / 20 )-0.0040.00697614984548545-0.573382179080996
Trimmed Mean ( 19 / 20 )-0.004347826086956520.00691066904309063-0.629146911803501
Trimmed Mean ( 20 / 20 )-0.004761904761904760.00674780555577842-0.705696796172046
Median-0.01
Midrange0.01
Midmean - Weighted Average at Xnp0.00194444444444444
Midmean - Weighted Average at X(n+1)p0.00194444444444444
Midmean - Empirical Distribution Function0.00194444444444444
Midmean - Empirical Distribution Function - Averaging0.00194444444444444
Midmean - Empirical Distribution Function - Interpolation0.00194444444444444
Midmean - Closest Observation0.00194444444444444
Midmean - True Basic - Statistics Graphics Toolkit0.00194444444444444
Midmean - MS Excel (old versions)0.00194444444444444
Number of observations61

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 0.000163934426229509 & 0.0114053285487463 & 0.0143734944178815 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & -0.526741926658227 &  &  \tabularnewline
Quadratic Mean & 0.0883454471536982 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & 0.000163934426229509 & 0.0111509557611361 & 0.0147013789437550 \tabularnewline
Winsorized Mean ( 2 / 20 ) & 0.000491803278688525 & 0.0109305463332134 & 0.0449934764188447 \tabularnewline
Winsorized Mean ( 3 / 20 ) & 0.00098360655737705 & 0.0108358464963015 & 0.0907733934504126 \tabularnewline
Winsorized Mean ( 4 / 20 ) & -0.000983606557377048 & 0.0103878473501538 & -0.0946881990292709 \tabularnewline
Winsorized Mean ( 5 / 20 ) & -0.000983606557377048 & 0.0103878473501538 & -0.0946881990292709 \tabularnewline
Winsorized Mean ( 6 / 20 ) & 0 & 0.0102055379801596 & 0 \tabularnewline
Winsorized Mean ( 7 / 20 ) & 0 & 0.0102055379801596 & 0 \tabularnewline
Winsorized Mean ( 8 / 20 ) & -1.82003774528714e-18 & 0.00970043095206279 & -1.87624421459349e-16 \tabularnewline
Winsorized Mean ( 9 / 20 ) & 0 & 0.00915262212719823 & 0 \tabularnewline
Winsorized Mean ( 10 / 20 ) & -0.00655737704918032 & 0.00796126292910359 & -0.823660405085837 \tabularnewline
Winsorized Mean ( 11 / 20 ) & -0.00836065573770492 & 0.00768285411969585 & -1.08822263281968 \tabularnewline
Winsorized Mean ( 12 / 20 ) & -0.00639344262295082 & 0.00734412812133488 & -0.87055161856146 \tabularnewline
Winsorized Mean ( 13 / 20 ) & -0.00639344262295082 & 0.00734412812133488 & -0.870551618561461 \tabularnewline
Winsorized Mean ( 14 / 20 ) & -0.00409836065573771 & 0.006971358458222 & -0.58788551475274 \tabularnewline
Winsorized Mean ( 15 / 20 ) & -0.00409836065573771 & 0.006971358458222 & -0.58788551475274 \tabularnewline
Winsorized Mean ( 16 / 20 ) & -0.00147540983606558 & 0.00656966062607012 & -0.224579307827678 \tabularnewline
Winsorized Mean ( 17 / 20 ) & 0.00131147540983606 & 0.0061691786783017 & 0.212585090856389 \tabularnewline
Winsorized Mean ( 18 / 20 ) & -0.00163934426229508 & 0.00571251300231139 & -0.286974272379209 \tabularnewline
Winsorized Mean ( 19 / 20 ) & -0.00163934426229508 & 0.00571251300231139 & -0.286974272379209 \tabularnewline
Winsorized Mean ( 20 / 20 ) & -0.00163934426229508 & 0.00571251300231139 & -0.286974272379210 \tabularnewline
Trimmed Mean ( 1 / 20 ) & -0.000169491525423728 & 0.0108614663342786 & -0.0156048474678613 \tabularnewline
Trimmed Mean ( 2 / 20 ) & -0.000526315789473684 & 0.0105054617989165 & -0.0500992530883282 \tabularnewline
Trimmed Mean ( 3 / 20 ) & -0.00109090909090909 & 0.0102121361987721 & -0.106824769046878 \tabularnewline
Trimmed Mean ( 4 / 20 ) & -0.00188679245283019 & 0.00989075525230874 & -0.190763233413320 \tabularnewline
Trimmed Mean ( 5 / 20 ) & -0.00215686274509804 & 0.00966624904638206 & -0.22313337208142 \tabularnewline
Trimmed Mean ( 6 / 20 ) & -0.00244897959183674 & 0.00937924784600978 & -0.26110618165172 \tabularnewline
Trimmed Mean ( 7 / 20 ) & -0.00297872340425532 & 0.00906811970417226 & -0.328483026407868 \tabularnewline
Trimmed Mean ( 8 / 20 ) & -0.00355555555555556 & 0.00866407627695442 & -0.410379068916207 \tabularnewline
Trimmed Mean ( 9 / 20 ) & -0.00418604651162791 & 0.0082876882238165 & -0.505092179939682 \tabularnewline
Trimmed Mean ( 10 / 20 ) & -0.0048780487804878 & 0.00794893727533798 & -0.613673074968426 \tabularnewline
Trimmed Mean ( 11 / 20 ) & -0.00461538461538462 & 0.00782609698644965 & -0.589742833928053 \tabularnewline
Trimmed Mean ( 12 / 20 ) & -0.00405405405405406 & 0.00771546805879496 & -0.525444992210523 \tabularnewline
Trimmed Mean ( 13 / 20 ) & -0.00371428571428572 & 0.00763765235484029 & -0.48631248736162 \tabularnewline
Trimmed Mean ( 14 / 20 ) & -0.00333333333333333 & 0.00750841279008171 & -0.443946467319501 \tabularnewline
Trimmed Mean ( 15 / 20 ) & -0.00322580645161290 & 0.00741093491372887 & -0.435276586444856 \tabularnewline
Trimmed Mean ( 16 / 20 ) & -0.00310344827586207 & 0.00724489710472786 & -0.42836333366789 \tabularnewline
Trimmed Mean ( 17 / 20 ) & -0.00333333333333333 & 0.00710122175596217 & -0.469402794038177 \tabularnewline
Trimmed Mean ( 18 / 20 ) & -0.004 & 0.00697614984548545 & -0.573382179080996 \tabularnewline
Trimmed Mean ( 19 / 20 ) & -0.00434782608695652 & 0.00691066904309063 & -0.629146911803501 \tabularnewline
Trimmed Mean ( 20 / 20 ) & -0.00476190476190476 & 0.00674780555577842 & -0.705696796172046 \tabularnewline
Median & -0.01 &  &  \tabularnewline
Midrange & 0.01 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 0.00194444444444444 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 0.00194444444444444 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 0.00194444444444444 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 0.00194444444444444 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 0.00194444444444444 &  &  \tabularnewline
Midmean - Closest Observation & 0.00194444444444444 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 0.00194444444444444 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 0.00194444444444444 &  &  \tabularnewline
Number of observations & 61 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19137&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]0.000163934426229509[/C][C]0.0114053285487463[/C][C]0.0143734944178815[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]-0.526741926658227[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]0.0883454471536982[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]0.000163934426229509[/C][C]0.0111509557611361[/C][C]0.0147013789437550[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]0.000491803278688525[/C][C]0.0109305463332134[/C][C]0.0449934764188447[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]0.00098360655737705[/C][C]0.0108358464963015[/C][C]0.0907733934504126[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]-0.000983606557377048[/C][C]0.0103878473501538[/C][C]-0.0946881990292709[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]-0.000983606557377048[/C][C]0.0103878473501538[/C][C]-0.0946881990292709[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]0[/C][C]0.0102055379801596[/C][C]0[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]0[/C][C]0.0102055379801596[/C][C]0[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]-1.82003774528714e-18[/C][C]0.00970043095206279[/C][C]-1.87624421459349e-16[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]0[/C][C]0.00915262212719823[/C][C]0[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]-0.00655737704918032[/C][C]0.00796126292910359[/C][C]-0.823660405085837[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]-0.00836065573770492[/C][C]0.00768285411969585[/C][C]-1.08822263281968[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]-0.00639344262295082[/C][C]0.00734412812133488[/C][C]-0.87055161856146[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]-0.00639344262295082[/C][C]0.00734412812133488[/C][C]-0.870551618561461[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]-0.00409836065573771[/C][C]0.006971358458222[/C][C]-0.58788551475274[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]-0.00409836065573771[/C][C]0.006971358458222[/C][C]-0.58788551475274[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]-0.00147540983606558[/C][C]0.00656966062607012[/C][C]-0.224579307827678[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]0.00131147540983606[/C][C]0.0061691786783017[/C][C]0.212585090856389[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]-0.00163934426229508[/C][C]0.00571251300231139[/C][C]-0.286974272379209[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]-0.00163934426229508[/C][C]0.00571251300231139[/C][C]-0.286974272379209[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]-0.00163934426229508[/C][C]0.00571251300231139[/C][C]-0.286974272379210[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]-0.000169491525423728[/C][C]0.0108614663342786[/C][C]-0.0156048474678613[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]-0.000526315789473684[/C][C]0.0105054617989165[/C][C]-0.0500992530883282[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]-0.00109090909090909[/C][C]0.0102121361987721[/C][C]-0.106824769046878[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]-0.00188679245283019[/C][C]0.00989075525230874[/C][C]-0.190763233413320[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]-0.00215686274509804[/C][C]0.00966624904638206[/C][C]-0.22313337208142[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]-0.00244897959183674[/C][C]0.00937924784600978[/C][C]-0.26110618165172[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]-0.00297872340425532[/C][C]0.00906811970417226[/C][C]-0.328483026407868[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]-0.00355555555555556[/C][C]0.00866407627695442[/C][C]-0.410379068916207[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]-0.00418604651162791[/C][C]0.0082876882238165[/C][C]-0.505092179939682[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]-0.0048780487804878[/C][C]0.00794893727533798[/C][C]-0.613673074968426[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]-0.00461538461538462[/C][C]0.00782609698644965[/C][C]-0.589742833928053[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]-0.00405405405405406[/C][C]0.00771546805879496[/C][C]-0.525444992210523[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]-0.00371428571428572[/C][C]0.00763765235484029[/C][C]-0.48631248736162[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]-0.00333333333333333[/C][C]0.00750841279008171[/C][C]-0.443946467319501[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]-0.00322580645161290[/C][C]0.00741093491372887[/C][C]-0.435276586444856[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]-0.00310344827586207[/C][C]0.00724489710472786[/C][C]-0.42836333366789[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]-0.00333333333333333[/C][C]0.00710122175596217[/C][C]-0.469402794038177[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]-0.004[/C][C]0.00697614984548545[/C][C]-0.573382179080996[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]-0.00434782608695652[/C][C]0.00691066904309063[/C][C]-0.629146911803501[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]-0.00476190476190476[/C][C]0.00674780555577842[/C][C]-0.705696796172046[/C][/ROW]
[ROW][C]Median[/C][C]-0.01[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]0.01[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]0.00194444444444444[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]0.00194444444444444[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]0.00194444444444444[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]0.00194444444444444[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]0.00194444444444444[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]0.00194444444444444[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]0.00194444444444444[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]0.00194444444444444[/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=19137&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19137&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 Mean0.0001639344262295090.01140532854874630.0143734944178815
Geometric MeanNaN
Harmonic Mean-0.526741926658227
Quadratic Mean0.0883454471536982
Winsorized Mean ( 1 / 20 )0.0001639344262295090.01115095576113610.0147013789437550
Winsorized Mean ( 2 / 20 )0.0004918032786885250.01093054633321340.0449934764188447
Winsorized Mean ( 3 / 20 )0.000983606557377050.01083584649630150.0907733934504126
Winsorized Mean ( 4 / 20 )-0.0009836065573770480.0103878473501538-0.0946881990292709
Winsorized Mean ( 5 / 20 )-0.0009836065573770480.0103878473501538-0.0946881990292709
Winsorized Mean ( 6 / 20 )00.01020553798015960
Winsorized Mean ( 7 / 20 )00.01020553798015960
Winsorized Mean ( 8 / 20 )-1.82003774528714e-180.00970043095206279-1.87624421459349e-16
Winsorized Mean ( 9 / 20 )00.009152622127198230
Winsorized Mean ( 10 / 20 )-0.006557377049180320.00796126292910359-0.823660405085837
Winsorized Mean ( 11 / 20 )-0.008360655737704920.00768285411969585-1.08822263281968
Winsorized Mean ( 12 / 20 )-0.006393442622950820.00734412812133488-0.87055161856146
Winsorized Mean ( 13 / 20 )-0.006393442622950820.00734412812133488-0.870551618561461
Winsorized Mean ( 14 / 20 )-0.004098360655737710.006971358458222-0.58788551475274
Winsorized Mean ( 15 / 20 )-0.004098360655737710.006971358458222-0.58788551475274
Winsorized Mean ( 16 / 20 )-0.001475409836065580.00656966062607012-0.224579307827678
Winsorized Mean ( 17 / 20 )0.001311475409836060.00616917867830170.212585090856389
Winsorized Mean ( 18 / 20 )-0.001639344262295080.00571251300231139-0.286974272379209
Winsorized Mean ( 19 / 20 )-0.001639344262295080.00571251300231139-0.286974272379209
Winsorized Mean ( 20 / 20 )-0.001639344262295080.00571251300231139-0.286974272379210
Trimmed Mean ( 1 / 20 )-0.0001694915254237280.0108614663342786-0.0156048474678613
Trimmed Mean ( 2 / 20 )-0.0005263157894736840.0105054617989165-0.0500992530883282
Trimmed Mean ( 3 / 20 )-0.001090909090909090.0102121361987721-0.106824769046878
Trimmed Mean ( 4 / 20 )-0.001886792452830190.00989075525230874-0.190763233413320
Trimmed Mean ( 5 / 20 )-0.002156862745098040.00966624904638206-0.22313337208142
Trimmed Mean ( 6 / 20 )-0.002448979591836740.00937924784600978-0.26110618165172
Trimmed Mean ( 7 / 20 )-0.002978723404255320.00906811970417226-0.328483026407868
Trimmed Mean ( 8 / 20 )-0.003555555555555560.00866407627695442-0.410379068916207
Trimmed Mean ( 9 / 20 )-0.004186046511627910.0082876882238165-0.505092179939682
Trimmed Mean ( 10 / 20 )-0.00487804878048780.00794893727533798-0.613673074968426
Trimmed Mean ( 11 / 20 )-0.004615384615384620.00782609698644965-0.589742833928053
Trimmed Mean ( 12 / 20 )-0.004054054054054060.00771546805879496-0.525444992210523
Trimmed Mean ( 13 / 20 )-0.003714285714285720.00763765235484029-0.48631248736162
Trimmed Mean ( 14 / 20 )-0.003333333333333330.00750841279008171-0.443946467319501
Trimmed Mean ( 15 / 20 )-0.003225806451612900.00741093491372887-0.435276586444856
Trimmed Mean ( 16 / 20 )-0.003103448275862070.00724489710472786-0.42836333366789
Trimmed Mean ( 17 / 20 )-0.003333333333333330.00710122175596217-0.469402794038177
Trimmed Mean ( 18 / 20 )-0.0040.00697614984548545-0.573382179080996
Trimmed Mean ( 19 / 20 )-0.004347826086956520.00691066904309063-0.629146911803501
Trimmed Mean ( 20 / 20 )-0.004761904761904760.00674780555577842-0.705696796172046
Median-0.01
Midrange0.01
Midmean - Weighted Average at Xnp0.00194444444444444
Midmean - Weighted Average at X(n+1)p0.00194444444444444
Midmean - Empirical Distribution Function0.00194444444444444
Midmean - Empirical Distribution Function - Averaging0.00194444444444444
Midmean - Empirical Distribution Function - Interpolation0.00194444444444444
Midmean - Closest Observation0.00194444444444444
Midmean - True Basic - Statistics Graphics Toolkit0.00194444444444444
Midmean - MS Excel (old versions)0.00194444444444444
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')