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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, 20 Oct 2008 11:01:48 -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/20/t12245221622sgz5vkpfnp1xiw.htm/, Retrieved Tue, 28 May 2024 20:12:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17677, Retrieved Tue, 28 May 2024 20:12:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact158
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Harrell-Davis Quantiles] [Q7 95% confidence...] [2007-10-20 15:02:46] [b731da8b544846036771bbf9bf2f34ce]
F    D  [Harrell-Davis Quantiles] [total industrial ...] [2008-10-20 06:02:18] [a4ee3bef49b119f4bd2e925060c84f5e]
- RMPD    [Central Tendency] [central tendency ...] [2008-10-20 16:39:47] [a4ee3bef49b119f4bd2e925060c84f5e]
F    D        [Central Tendency] [central tendency ...] [2008-10-20 17:01:48] [19ef54504342c1b076371d395a2ab19f] [Current]
Feedback Forum
2008-10-24 17:07:41 [Kenny Simons] [reply
Deze tijdreeks is inderdaag robuust. De midrange, median en gemiddelde liggen niet dicht bij elkaar, we hebben hier zelf te maken met een negatieve midrange. En als we naar de 2 plots gaan kijken van de trimmed en winsorized mean, zien we dat de curves niet binnen het betrouwbaarheidinterval liggen. We kunnen dus concluderen dat deze tijdreeks robuust is.
2008-10-24 17:13:28 [Kenny Simons] [reply
Om van deze tijdreeks een voorspelling te maken, moeten we zien naar de curves van de winsorized mean en de trimmed mean. We kunnen zien dat deze allebei stijgen, hierdoor kunnen we voorspellen dat de volgende observatie ook lichtjes boven de laatste observatie zal liggen.

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Dataseries X:
1.1
0.9
0
0.4
0.7
0.7
1
1.1
0.3
1.4
-0.5
1.2
1.2
0.8
-0.2
0.3
0.2
0.7
0.9
0.7
0.3
1.2
-0.6
1.1
1
0.2
-1
-0.6
0
-0.4
0.1
0.7
0.8
1.2
-0.7
0.9
0.7
0.5
-0.2
0.3
0.5
0.9
0.5
0.3
0.9
0.4
-0.1
0.6
0.2
-0.5
-1.7
-2
-1
-1.7
-1.6
-1.7
-0.9




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=17677&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=17677&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17677&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 Mean0.2017543859649120.1137614801298841.77348594387630
Geometric MeanNaN
Harmonic Mean0
Quadratic Mean0.874893477225215
Winsorized Mean ( 1 / 19 )0.2035087719298250.1114375453698151.82621369893301
Winsorized Mean ( 2 / 19 )0.2035087719298250.1114375453698151.82621369893301
Winsorized Mean ( 3 / 19 )0.2035087719298250.1114375453698151.82621369893301
Winsorized Mean ( 4 / 19 )0.2105263157894740.1093293583044261.92561558079638
Winsorized Mean ( 5 / 19 )0.2543859649122810.09372780189790412.71409293465965
Winsorized Mean ( 6 / 19 )0.2543859649122810.09372780189790412.71409293465965
Winsorized Mean ( 7 / 19 )0.2666666666666670.09085135251589962.93519754282137
Winsorized Mean ( 8 / 19 )0.2807017543859650.08239212574045083.40690025731613
Winsorized Mean ( 9 / 19 )0.2964912280701750.07911497107612013.74759952556777
Winsorized Mean ( 10 / 19 )0.2789473684210530.07644747087160283.64887634921969
Winsorized Mean ( 11 / 19 )0.2982456140350880.07256883466647874.10983055475265
Winsorized Mean ( 12 / 19 )0.2982456140350880.07256883466647874.10983055475265
Winsorized Mean ( 13 / 19 )0.3210526315789470.06817238405709434.70942355940004
Winsorized Mean ( 14 / 19 )0.3701754385964910.0592858983749066.24390367260042
Winsorized Mean ( 15 / 19 )0.3438596491228070.05524027851167966.2247993382239
Winsorized Mean ( 16 / 19 )0.3719298245614040.05042143109894717.37642340677574
Winsorized Mean ( 17 / 19 )0.3719298245614030.0411119251343379.04676254751118
Winsorized Mean ( 18 / 19 )0.3719298245614030.0411119251343379.04676254751118
Winsorized Mean ( 19 / 19 )0.4052631578947370.035876166563131211.2961666955581
Trimmed Mean ( 1 / 19 )0.220.1085688969604342.02636303913242
Trimmed Mean ( 2 / 19 )0.2377358490566040.1049302213054472.26565660587493
Trimmed Mean ( 3 / 19 )0.2568627450980390.1002841023884112.56135059277075
Trimmed Mean ( 4 / 19 )0.2775510204081630.09427783634667962.94396892380463
Trimmed Mean ( 5 / 19 )0.2978723404255320.08738620784737043.408688255998
Trimmed Mean ( 6 / 19 )0.3088888888888890.08461572209989763.65049049069408
Trimmed Mean ( 7 / 19 )0.3209302325581400.0809384423223543.96511501024407
Trimmed Mean ( 8 / 19 )0.3317073170731710.07702066751379964.3067312681202
Trimmed Mean ( 9 / 19 )0.3410256410256410.07444966315821574.58062033539245
Trimmed Mean ( 10 / 19 )0.3486486486486490.07193398934542334.84678594668865
Trimmed Mean ( 11 / 19 )0.360.06911201478929185.2089351048087
Trimmed Mean ( 12 / 19 )0.369696969696970.0663560255771465.57141520278603
Trimmed Mean ( 13 / 19 )0.3806451612903230.06228953463916436.1109007074038
Trimmed Mean ( 14 / 19 )0.3896551724137930.05795038381997096.72394463554027
Trimmed Mean ( 15 / 19 )0.3925925925925930.0549348036081167.14651854211037
Trimmed Mean ( 16 / 19 )0.40.05163977794943227.74596669241483
Trimmed Mean ( 17 / 19 )0.4043478260869570.04848628055397838.33942759615904
Trimmed Mean ( 18 / 19 )0.4095238095238100.04726055533637918.6652348159899
Trimmed Mean ( 19 / 19 )0.4157894736842110.04476263446376529.288762349785
Median0.4
Midrange-0.3
Midmean - Weighted Average at Xnp0.371428571428571
Midmean - Weighted Average at X(n+1)p0.451515151515152
Midmean - Empirical Distribution Function0.451515151515152
Midmean - Empirical Distribution Function - Averaging0.451515151515152
Midmean - Empirical Distribution Function - Interpolation0.451515151515152
Midmean - Closest Observation0.426470588235294
Midmean - True Basic - Statistics Graphics Toolkit0.451515151515152
Midmean - MS Excel (old versions)0.451515151515152
Number of observations57

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 0.201754385964912 & 0.113761480129884 & 1.77348594387630 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 0 &  &  \tabularnewline
Quadratic Mean & 0.874893477225215 &  &  \tabularnewline
Winsorized Mean ( 1 / 19 ) & 0.203508771929825 & 0.111437545369815 & 1.82621369893301 \tabularnewline
Winsorized Mean ( 2 / 19 ) & 0.203508771929825 & 0.111437545369815 & 1.82621369893301 \tabularnewline
Winsorized Mean ( 3 / 19 ) & 0.203508771929825 & 0.111437545369815 & 1.82621369893301 \tabularnewline
Winsorized Mean ( 4 / 19 ) & 0.210526315789474 & 0.109329358304426 & 1.92561558079638 \tabularnewline
Winsorized Mean ( 5 / 19 ) & 0.254385964912281 & 0.0937278018979041 & 2.71409293465965 \tabularnewline
Winsorized Mean ( 6 / 19 ) & 0.254385964912281 & 0.0937278018979041 & 2.71409293465965 \tabularnewline
Winsorized Mean ( 7 / 19 ) & 0.266666666666667 & 0.0908513525158996 & 2.93519754282137 \tabularnewline
Winsorized Mean ( 8 / 19 ) & 0.280701754385965 & 0.0823921257404508 & 3.40690025731613 \tabularnewline
Winsorized Mean ( 9 / 19 ) & 0.296491228070175 & 0.0791149710761201 & 3.74759952556777 \tabularnewline
Winsorized Mean ( 10 / 19 ) & 0.278947368421053 & 0.0764474708716028 & 3.64887634921969 \tabularnewline
Winsorized Mean ( 11 / 19 ) & 0.298245614035088 & 0.0725688346664787 & 4.10983055475265 \tabularnewline
Winsorized Mean ( 12 / 19 ) & 0.298245614035088 & 0.0725688346664787 & 4.10983055475265 \tabularnewline
Winsorized Mean ( 13 / 19 ) & 0.321052631578947 & 0.0681723840570943 & 4.70942355940004 \tabularnewline
Winsorized Mean ( 14 / 19 ) & 0.370175438596491 & 0.059285898374906 & 6.24390367260042 \tabularnewline
Winsorized Mean ( 15 / 19 ) & 0.343859649122807 & 0.0552402785116796 & 6.2247993382239 \tabularnewline
Winsorized Mean ( 16 / 19 ) & 0.371929824561404 & 0.0504214310989471 & 7.37642340677574 \tabularnewline
Winsorized Mean ( 17 / 19 ) & 0.371929824561403 & 0.041111925134337 & 9.04676254751118 \tabularnewline
Winsorized Mean ( 18 / 19 ) & 0.371929824561403 & 0.041111925134337 & 9.04676254751118 \tabularnewline
Winsorized Mean ( 19 / 19 ) & 0.405263157894737 & 0.0358761665631312 & 11.2961666955581 \tabularnewline
Trimmed Mean ( 1 / 19 ) & 0.22 & 0.108568896960434 & 2.02636303913242 \tabularnewline
Trimmed Mean ( 2 / 19 ) & 0.237735849056604 & 0.104930221305447 & 2.26565660587493 \tabularnewline
Trimmed Mean ( 3 / 19 ) & 0.256862745098039 & 0.100284102388411 & 2.56135059277075 \tabularnewline
Trimmed Mean ( 4 / 19 ) & 0.277551020408163 & 0.0942778363466796 & 2.94396892380463 \tabularnewline
Trimmed Mean ( 5 / 19 ) & 0.297872340425532 & 0.0873862078473704 & 3.408688255998 \tabularnewline
Trimmed Mean ( 6 / 19 ) & 0.308888888888889 & 0.0846157220998976 & 3.65049049069408 \tabularnewline
Trimmed Mean ( 7 / 19 ) & 0.320930232558140 & 0.080938442322354 & 3.96511501024407 \tabularnewline
Trimmed Mean ( 8 / 19 ) & 0.331707317073171 & 0.0770206675137996 & 4.3067312681202 \tabularnewline
Trimmed Mean ( 9 / 19 ) & 0.341025641025641 & 0.0744496631582157 & 4.58062033539245 \tabularnewline
Trimmed Mean ( 10 / 19 ) & 0.348648648648649 & 0.0719339893454233 & 4.84678594668865 \tabularnewline
Trimmed Mean ( 11 / 19 ) & 0.36 & 0.0691120147892918 & 5.2089351048087 \tabularnewline
Trimmed Mean ( 12 / 19 ) & 0.36969696969697 & 0.066356025577146 & 5.57141520278603 \tabularnewline
Trimmed Mean ( 13 / 19 ) & 0.380645161290323 & 0.0622895346391643 & 6.1109007074038 \tabularnewline
Trimmed Mean ( 14 / 19 ) & 0.389655172413793 & 0.0579503838199709 & 6.72394463554027 \tabularnewline
Trimmed Mean ( 15 / 19 ) & 0.392592592592593 & 0.054934803608116 & 7.14651854211037 \tabularnewline
Trimmed Mean ( 16 / 19 ) & 0.4 & 0.0516397779494322 & 7.74596669241483 \tabularnewline
Trimmed Mean ( 17 / 19 ) & 0.404347826086957 & 0.0484862805539783 & 8.33942759615904 \tabularnewline
Trimmed Mean ( 18 / 19 ) & 0.409523809523810 & 0.0472605553363791 & 8.6652348159899 \tabularnewline
Trimmed Mean ( 19 / 19 ) & 0.415789473684211 & 0.0447626344637652 & 9.288762349785 \tabularnewline
Median & 0.4 &  &  \tabularnewline
Midrange & -0.3 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 0.371428571428571 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 0.451515151515152 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 0.451515151515152 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 0.451515151515152 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 0.451515151515152 &  &  \tabularnewline
Midmean - Closest Observation & 0.426470588235294 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 0.451515151515152 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 0.451515151515152 &  &  \tabularnewline
Number of observations & 57 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17677&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]0.201754385964912[/C][C]0.113761480129884[/C][C]1.77348594387630[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]0[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]0.874893477225215[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 19 )[/C][C]0.203508771929825[/C][C]0.111437545369815[/C][C]1.82621369893301[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 19 )[/C][C]0.203508771929825[/C][C]0.111437545369815[/C][C]1.82621369893301[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 19 )[/C][C]0.203508771929825[/C][C]0.111437545369815[/C][C]1.82621369893301[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 19 )[/C][C]0.210526315789474[/C][C]0.109329358304426[/C][C]1.92561558079638[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 19 )[/C][C]0.254385964912281[/C][C]0.0937278018979041[/C][C]2.71409293465965[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 19 )[/C][C]0.254385964912281[/C][C]0.0937278018979041[/C][C]2.71409293465965[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 19 )[/C][C]0.266666666666667[/C][C]0.0908513525158996[/C][C]2.93519754282137[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 19 )[/C][C]0.280701754385965[/C][C]0.0823921257404508[/C][C]3.40690025731613[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 19 )[/C][C]0.296491228070175[/C][C]0.0791149710761201[/C][C]3.74759952556777[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 19 )[/C][C]0.278947368421053[/C][C]0.0764474708716028[/C][C]3.64887634921969[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 19 )[/C][C]0.298245614035088[/C][C]0.0725688346664787[/C][C]4.10983055475265[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 19 )[/C][C]0.298245614035088[/C][C]0.0725688346664787[/C][C]4.10983055475265[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 19 )[/C][C]0.321052631578947[/C][C]0.0681723840570943[/C][C]4.70942355940004[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 19 )[/C][C]0.370175438596491[/C][C]0.059285898374906[/C][C]6.24390367260042[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 19 )[/C][C]0.343859649122807[/C][C]0.0552402785116796[/C][C]6.2247993382239[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 19 )[/C][C]0.371929824561404[/C][C]0.0504214310989471[/C][C]7.37642340677574[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 19 )[/C][C]0.371929824561403[/C][C]0.041111925134337[/C][C]9.04676254751118[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 19 )[/C][C]0.371929824561403[/C][C]0.041111925134337[/C][C]9.04676254751118[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 19 )[/C][C]0.405263157894737[/C][C]0.0358761665631312[/C][C]11.2961666955581[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 19 )[/C][C]0.22[/C][C]0.108568896960434[/C][C]2.02636303913242[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 19 )[/C][C]0.237735849056604[/C][C]0.104930221305447[/C][C]2.26565660587493[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 19 )[/C][C]0.256862745098039[/C][C]0.100284102388411[/C][C]2.56135059277075[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 19 )[/C][C]0.277551020408163[/C][C]0.0942778363466796[/C][C]2.94396892380463[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 19 )[/C][C]0.297872340425532[/C][C]0.0873862078473704[/C][C]3.408688255998[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 19 )[/C][C]0.308888888888889[/C][C]0.0846157220998976[/C][C]3.65049049069408[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 19 )[/C][C]0.320930232558140[/C][C]0.080938442322354[/C][C]3.96511501024407[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 19 )[/C][C]0.331707317073171[/C][C]0.0770206675137996[/C][C]4.3067312681202[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 19 )[/C][C]0.341025641025641[/C][C]0.0744496631582157[/C][C]4.58062033539245[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 19 )[/C][C]0.348648648648649[/C][C]0.0719339893454233[/C][C]4.84678594668865[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 19 )[/C][C]0.36[/C][C]0.0691120147892918[/C][C]5.2089351048087[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 19 )[/C][C]0.36969696969697[/C][C]0.066356025577146[/C][C]5.57141520278603[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 19 )[/C][C]0.380645161290323[/C][C]0.0622895346391643[/C][C]6.1109007074038[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 19 )[/C][C]0.389655172413793[/C][C]0.0579503838199709[/C][C]6.72394463554027[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 19 )[/C][C]0.392592592592593[/C][C]0.054934803608116[/C][C]7.14651854211037[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 19 )[/C][C]0.4[/C][C]0.0516397779494322[/C][C]7.74596669241483[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 19 )[/C][C]0.404347826086957[/C][C]0.0484862805539783[/C][C]8.33942759615904[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 19 )[/C][C]0.409523809523810[/C][C]0.0472605553363791[/C][C]8.6652348159899[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 19 )[/C][C]0.415789473684211[/C][C]0.0447626344637652[/C][C]9.288762349785[/C][/ROW]
[ROW][C]Median[/C][C]0.4[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-0.3[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]0.371428571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]0.451515151515152[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]0.451515151515152[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]0.451515151515152[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]0.451515151515152[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]0.426470588235294[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]0.451515151515152[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]0.451515151515152[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]57[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17677&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17677&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 Mean0.2017543859649120.1137614801298841.77348594387630
Geometric MeanNaN
Harmonic Mean0
Quadratic Mean0.874893477225215
Winsorized Mean ( 1 / 19 )0.2035087719298250.1114375453698151.82621369893301
Winsorized Mean ( 2 / 19 )0.2035087719298250.1114375453698151.82621369893301
Winsorized Mean ( 3 / 19 )0.2035087719298250.1114375453698151.82621369893301
Winsorized Mean ( 4 / 19 )0.2105263157894740.1093293583044261.92561558079638
Winsorized Mean ( 5 / 19 )0.2543859649122810.09372780189790412.71409293465965
Winsorized Mean ( 6 / 19 )0.2543859649122810.09372780189790412.71409293465965
Winsorized Mean ( 7 / 19 )0.2666666666666670.09085135251589962.93519754282137
Winsorized Mean ( 8 / 19 )0.2807017543859650.08239212574045083.40690025731613
Winsorized Mean ( 9 / 19 )0.2964912280701750.07911497107612013.74759952556777
Winsorized Mean ( 10 / 19 )0.2789473684210530.07644747087160283.64887634921969
Winsorized Mean ( 11 / 19 )0.2982456140350880.07256883466647874.10983055475265
Winsorized Mean ( 12 / 19 )0.2982456140350880.07256883466647874.10983055475265
Winsorized Mean ( 13 / 19 )0.3210526315789470.06817238405709434.70942355940004
Winsorized Mean ( 14 / 19 )0.3701754385964910.0592858983749066.24390367260042
Winsorized Mean ( 15 / 19 )0.3438596491228070.05524027851167966.2247993382239
Winsorized Mean ( 16 / 19 )0.3719298245614040.05042143109894717.37642340677574
Winsorized Mean ( 17 / 19 )0.3719298245614030.0411119251343379.04676254751118
Winsorized Mean ( 18 / 19 )0.3719298245614030.0411119251343379.04676254751118
Winsorized Mean ( 19 / 19 )0.4052631578947370.035876166563131211.2961666955581
Trimmed Mean ( 1 / 19 )0.220.1085688969604342.02636303913242
Trimmed Mean ( 2 / 19 )0.2377358490566040.1049302213054472.26565660587493
Trimmed Mean ( 3 / 19 )0.2568627450980390.1002841023884112.56135059277075
Trimmed Mean ( 4 / 19 )0.2775510204081630.09427783634667962.94396892380463
Trimmed Mean ( 5 / 19 )0.2978723404255320.08738620784737043.408688255998
Trimmed Mean ( 6 / 19 )0.3088888888888890.08461572209989763.65049049069408
Trimmed Mean ( 7 / 19 )0.3209302325581400.0809384423223543.96511501024407
Trimmed Mean ( 8 / 19 )0.3317073170731710.07702066751379964.3067312681202
Trimmed Mean ( 9 / 19 )0.3410256410256410.07444966315821574.58062033539245
Trimmed Mean ( 10 / 19 )0.3486486486486490.07193398934542334.84678594668865
Trimmed Mean ( 11 / 19 )0.360.06911201478929185.2089351048087
Trimmed Mean ( 12 / 19 )0.369696969696970.0663560255771465.57141520278603
Trimmed Mean ( 13 / 19 )0.3806451612903230.06228953463916436.1109007074038
Trimmed Mean ( 14 / 19 )0.3896551724137930.05795038381997096.72394463554027
Trimmed Mean ( 15 / 19 )0.3925925925925930.0549348036081167.14651854211037
Trimmed Mean ( 16 / 19 )0.40.05163977794943227.74596669241483
Trimmed Mean ( 17 / 19 )0.4043478260869570.04848628055397838.33942759615904
Trimmed Mean ( 18 / 19 )0.4095238095238100.04726055533637918.6652348159899
Trimmed Mean ( 19 / 19 )0.4157894736842110.04476263446376529.288762349785
Median0.4
Midrange-0.3
Midmean - Weighted Average at Xnp0.371428571428571
Midmean - Weighted Average at X(n+1)p0.451515151515152
Midmean - Empirical Distribution Function0.451515151515152
Midmean - Empirical Distribution Function - Averaging0.451515151515152
Midmean - Empirical Distribution Function - Interpolation0.451515151515152
Midmean - Closest Observation0.426470588235294
Midmean - True Basic - Statistics Graphics Toolkit0.451515151515152
Midmean - MS Excel (old versions)0.451515151515152
Number of observations57



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')