Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationWed, 26 Dec 2007 12:53:11 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Dec/26/t11986976522s6u8howv41djvo.htm/, Retrieved Mon, 29 Apr 2024 18:47:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4896, Retrieved Mon, 29 Apr 2024 18:47:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsmet voorspellingsfouten van Backward Selection...
Estimated Impact288
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Central Tendency] [2007-12-26 19:53:11] [bebbf4ab6ac77d61a56e6916ab0650f9] [Current]
Feedback Forum

Post a new message
Dataseries X:
0.00432941450518916
0.0233604344343087
0.111529718090494
0.0426566422442822
0.00329114082772466
-0.0165654712348738
0.0328601051615075
0.0170922301110487
0.0455461538266676
-0.0173515146503020
-0.0593934315521763
0.0624774966484597
0.0770081993209697
0.053709101252903
-0.0657049095682227
-0.111187584404637
0.0176352266485562
0.037238930258372
0.0152746372627233
0.0268816086175372
-0.0529994426109983
0.0640631754196459
0.0208622686822659
0.0279464743413715
0.049900535299785
0.0090330617930574
0.0682587886333925
0.0166606038985879
0.0527302708157107
-0.0239493642811439
0.0291680288906129
0.0465178661058054
-0.00301251154084081
0.0742259190265377
-0.0576205628450657
-0.0543536659883159
0.0695743048603195
0.0248509795595009
0.101874908803837
-0.00537615556147397
-0.0499250288828526
0.079319657170796
0.0252566541924892
0.0588076942476148
-0.00257916999892505
-0.0516904353435663
-0.0335694314655619
0.0363027887384009
0.080406744001655
-0.0174791308159552
0.00764175000849487
0.093848814552608
0.0270171922041724
-0.0222662842247345
0.0504733484129973
-0.0151864590183735
-0.107353439071580
-0.0342395391363599
0.0142417646291220
0.0402140631821242
-0.0914835921955728
0.0568373013868300
0.0418639678369921
0.0523004479841136
-0.0005599725773342
0.0338304081769785
0.0495823756713341




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4896&T=0

[TABLE]
[ROW][C]Summary of compuational 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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4896&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4896&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean0.01612919553386610.005987367663154742.6938709030886
Geometric MeanNaN
Harmonic Mean-0.0512080281006703
Quadratic Mean0.0512460405280242
Winsorized Mean ( 1 / 22 )0.01604231995246910.005935949090629642.7025703400646
Winsorized Mean ( 2 / 22 )0.01627646182186550.005743096503645262.83409164577584
Winsorized Mean ( 3 / 22 )0.01682884743722650.005326153356214493.15966257666818
Winsorized Mean ( 4 / 22 )0.0171407513885810.005228393904156163.27839709532127
Winsorized Mean ( 5 / 22 )0.01710055816897540.005168540638791843.30858541396178
Winsorized Mean ( 6 / 22 )0.01714395666709340.005062017053123343.38678366492569
Winsorized Mean ( 7 / 22 )0.01679945315183510.004950978405707373.39315823564674
Winsorized Mean ( 8 / 22 )0.01679867596264170.004892506877821153.4335518338858
Winsorized Mean ( 9 / 22 )0.01647223027939840.004754591833334813.46448882613022
Winsorized Mean ( 10 / 22 )0.01857667967869790.004248456852642714.37257110593991
Winsorized Mean ( 11 / 22 )0.01808419248421260.00413554319788244.37286992757629
Winsorized Mean ( 12 / 22 )0.01945428340784840.003768754475986245.1619927835064
Winsorized Mean ( 13 / 22 )0.01917388697489720.003622473268257775.29303753402684
Winsorized Mean ( 14 / 22 )0.01996965595403480.003423173737422935.83366708377138
Winsorized Mean ( 15 / 22 )0.01990199774524140.003404523110921825.84575198840482
Winsorized Mean ( 16 / 22 )0.01965338732000250.003311175030103785.93547219380501
Winsorized Mean ( 17 / 22 )0.01985794530143370.003232963190992686.1423357236976
Winsorized Mean ( 18 / 22 )0.02240807349415130.002805171950883717.98812831673014
Winsorized Mean ( 19 / 22 )0.02220932057843460.002579298071066068.61060643884994
Winsorized Mean ( 20 / 22 )0.02204861289568180.002518923104884118.75319014420497
Winsorized Mean ( 21 / 22 )0.02177582786020890.002299057011607039.47163456594217
Winsorized Mean ( 22 / 22 )0.02278009141171500.0020800730047755610.9515826412896
Trimmed Mean ( 1 / 22 )0.01662021487820270.005658466462554312.93722954588301
Trimmed Mean ( 2 / 22 )0.01723480154525260.005319641213615033.23984284901434
Trimmed Mean ( 3 / 22 )0.01776110286875220.005036152661710333.52672050706269
Trimmed Mean ( 4 / 22 )0.01811399051797370.004893057745601953.70197767117202
Trimmed Mean ( 5 / 22 )0.01839998622704960.00475500580175993.86960331788439
Trimmed Mean ( 6 / 22 )0.01871657415392590.00460390029566244.06537347725794
Trimmed Mean ( 7 / 22 )0.01904791180052270.00444795132759554.28240113203302
Trimmed Mean ( 8 / 22 )0.01946989143487020.004282780470774114.54608672280395
Trimmed Mean ( 9 / 22 )0.01992645122221540.004088636844858234.87361729063183
Trimmed Mean ( 10 / 22 )0.02047357368833540.003875784097300965.28243399899207
Trimmed Mean ( 11 / 22 )0.02075600012977030.003741352106050475.54772700922855
Trimmed Mean ( 12 / 22 )0.02113445914087470.003592638434654705.8827125315509
Trimmed Mean ( 13 / 22 )0.02136326355980300.003492216386574676.11739399709911
Trimmed Mean ( 14 / 22 )0.02165258945958350.003391631376615486.38412228665919
Trimmed Mean ( 15 / 22 )0.02187026618713510.003304926385187036.61747453291534
Trimmed Mean ( 16 / 22 )0.02212145473114820.00318640346225816.94245251524786
Trimmed Mean ( 17 / 22 )0.02243463752763830.003043019192109557.37249294575948
Trimmed Mean ( 18 / 22 )0.02276222458485980.002859707995302547.95963245976505
Trimmed Mean ( 19 / 22 )0.02280768075933770.002739585264875008.32523121355681
Trimmed Mean ( 20 / 22 )0.02288582916503070.002632609917575208.69320935556983
Trimmed Mean ( 21 / 22 )0.02299801614512340.002484295544174569.25735917332849
Trimmed Mean ( 22 / 22 )0.02316755365048430.002335891595194749.91807740485183
Median0.0248509795595009
Midrange0.000171066842928502
Midmean - Weighted Average at Xnp0.0212875755052115
Midmean - Weighted Average at X(n+1)p0.0221214547311482
Midmean - Empirical Distribution Function0.0221214547311482
Midmean - Empirical Distribution Function - Averaging0.0221214547311482
Midmean - Empirical Distribution Function - Interpolation0.0224346375276383
Midmean - Closest Observation0.0212875755052115
Midmean - True Basic - Statistics Graphics Toolkit0.0221214547311482
Midmean - MS Excel (old versions)0.0221214547311482
Number of observations67

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 0.0161291955338661 & 0.00598736766315474 & 2.6938709030886 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & -0.0512080281006703 &  &  \tabularnewline
Quadratic Mean & 0.0512460405280242 &  &  \tabularnewline
Winsorized Mean ( 1 / 22 ) & 0.0160423199524691 & 0.00593594909062964 & 2.7025703400646 \tabularnewline
Winsorized Mean ( 2 / 22 ) & 0.0162764618218655 & 0.00574309650364526 & 2.83409164577584 \tabularnewline
Winsorized Mean ( 3 / 22 ) & 0.0168288474372265 & 0.00532615335621449 & 3.15966257666818 \tabularnewline
Winsorized Mean ( 4 / 22 ) & 0.017140751388581 & 0.00522839390415616 & 3.27839709532127 \tabularnewline
Winsorized Mean ( 5 / 22 ) & 0.0171005581689754 & 0.00516854063879184 & 3.30858541396178 \tabularnewline
Winsorized Mean ( 6 / 22 ) & 0.0171439566670934 & 0.00506201705312334 & 3.38678366492569 \tabularnewline
Winsorized Mean ( 7 / 22 ) & 0.0167994531518351 & 0.00495097840570737 & 3.39315823564674 \tabularnewline
Winsorized Mean ( 8 / 22 ) & 0.0167986759626417 & 0.00489250687782115 & 3.4335518338858 \tabularnewline
Winsorized Mean ( 9 / 22 ) & 0.0164722302793984 & 0.00475459183333481 & 3.46448882613022 \tabularnewline
Winsorized Mean ( 10 / 22 ) & 0.0185766796786979 & 0.00424845685264271 & 4.37257110593991 \tabularnewline
Winsorized Mean ( 11 / 22 ) & 0.0180841924842126 & 0.0041355431978824 & 4.37286992757629 \tabularnewline
Winsorized Mean ( 12 / 22 ) & 0.0194542834078484 & 0.00376875447598624 & 5.1619927835064 \tabularnewline
Winsorized Mean ( 13 / 22 ) & 0.0191738869748972 & 0.00362247326825777 & 5.29303753402684 \tabularnewline
Winsorized Mean ( 14 / 22 ) & 0.0199696559540348 & 0.00342317373742293 & 5.83366708377138 \tabularnewline
Winsorized Mean ( 15 / 22 ) & 0.0199019977452414 & 0.00340452311092182 & 5.84575198840482 \tabularnewline
Winsorized Mean ( 16 / 22 ) & 0.0196533873200025 & 0.00331117503010378 & 5.93547219380501 \tabularnewline
Winsorized Mean ( 17 / 22 ) & 0.0198579453014337 & 0.00323296319099268 & 6.1423357236976 \tabularnewline
Winsorized Mean ( 18 / 22 ) & 0.0224080734941513 & 0.00280517195088371 & 7.98812831673014 \tabularnewline
Winsorized Mean ( 19 / 22 ) & 0.0222093205784346 & 0.00257929807106606 & 8.61060643884994 \tabularnewline
Winsorized Mean ( 20 / 22 ) & 0.0220486128956818 & 0.00251892310488411 & 8.75319014420497 \tabularnewline
Winsorized Mean ( 21 / 22 ) & 0.0217758278602089 & 0.00229905701160703 & 9.47163456594217 \tabularnewline
Winsorized Mean ( 22 / 22 ) & 0.0227800914117150 & 0.00208007300477556 & 10.9515826412896 \tabularnewline
Trimmed Mean ( 1 / 22 ) & 0.0166202148782027 & 0.00565846646255431 & 2.93722954588301 \tabularnewline
Trimmed Mean ( 2 / 22 ) & 0.0172348015452526 & 0.00531964121361503 & 3.23984284901434 \tabularnewline
Trimmed Mean ( 3 / 22 ) & 0.0177611028687522 & 0.00503615266171033 & 3.52672050706269 \tabularnewline
Trimmed Mean ( 4 / 22 ) & 0.0181139905179737 & 0.00489305774560195 & 3.70197767117202 \tabularnewline
Trimmed Mean ( 5 / 22 ) & 0.0183999862270496 & 0.0047550058017599 & 3.86960331788439 \tabularnewline
Trimmed Mean ( 6 / 22 ) & 0.0187165741539259 & 0.0046039002956624 & 4.06537347725794 \tabularnewline
Trimmed Mean ( 7 / 22 ) & 0.0190479118005227 & 0.0044479513275955 & 4.28240113203302 \tabularnewline
Trimmed Mean ( 8 / 22 ) & 0.0194698914348702 & 0.00428278047077411 & 4.54608672280395 \tabularnewline
Trimmed Mean ( 9 / 22 ) & 0.0199264512222154 & 0.00408863684485823 & 4.87361729063183 \tabularnewline
Trimmed Mean ( 10 / 22 ) & 0.0204735736883354 & 0.00387578409730096 & 5.28243399899207 \tabularnewline
Trimmed Mean ( 11 / 22 ) & 0.0207560001297703 & 0.00374135210605047 & 5.54772700922855 \tabularnewline
Trimmed Mean ( 12 / 22 ) & 0.0211344591408747 & 0.00359263843465470 & 5.8827125315509 \tabularnewline
Trimmed Mean ( 13 / 22 ) & 0.0213632635598030 & 0.00349221638657467 & 6.11739399709911 \tabularnewline
Trimmed Mean ( 14 / 22 ) & 0.0216525894595835 & 0.00339163137661548 & 6.38412228665919 \tabularnewline
Trimmed Mean ( 15 / 22 ) & 0.0218702661871351 & 0.00330492638518703 & 6.61747453291534 \tabularnewline
Trimmed Mean ( 16 / 22 ) & 0.0221214547311482 & 0.0031864034622581 & 6.94245251524786 \tabularnewline
Trimmed Mean ( 17 / 22 ) & 0.0224346375276383 & 0.00304301919210955 & 7.37249294575948 \tabularnewline
Trimmed Mean ( 18 / 22 ) & 0.0227622245848598 & 0.00285970799530254 & 7.95963245976505 \tabularnewline
Trimmed Mean ( 19 / 22 ) & 0.0228076807593377 & 0.00273958526487500 & 8.32523121355681 \tabularnewline
Trimmed Mean ( 20 / 22 ) & 0.0228858291650307 & 0.00263260991757520 & 8.69320935556983 \tabularnewline
Trimmed Mean ( 21 / 22 ) & 0.0229980161451234 & 0.00248429554417456 & 9.25735917332849 \tabularnewline
Trimmed Mean ( 22 / 22 ) & 0.0231675536504843 & 0.00233589159519474 & 9.91807740485183 \tabularnewline
Median & 0.0248509795595009 &  &  \tabularnewline
Midrange & 0.000171066842928502 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 0.0212875755052115 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 0.0221214547311482 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 0.0221214547311482 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 0.0221214547311482 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 0.0224346375276383 &  &  \tabularnewline
Midmean - Closest Observation & 0.0212875755052115 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 0.0221214547311482 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 0.0221214547311482 &  &  \tabularnewline
Number of observations & 67 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4896&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]0.0161291955338661[/C][C]0.00598736766315474[/C][C]2.6938709030886[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]-0.0512080281006703[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]0.0512460405280242[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 22 )[/C][C]0.0160423199524691[/C][C]0.00593594909062964[/C][C]2.7025703400646[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 22 )[/C][C]0.0162764618218655[/C][C]0.00574309650364526[/C][C]2.83409164577584[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 22 )[/C][C]0.0168288474372265[/C][C]0.00532615335621449[/C][C]3.15966257666818[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 22 )[/C][C]0.017140751388581[/C][C]0.00522839390415616[/C][C]3.27839709532127[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 22 )[/C][C]0.0171005581689754[/C][C]0.00516854063879184[/C][C]3.30858541396178[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 22 )[/C][C]0.0171439566670934[/C][C]0.00506201705312334[/C][C]3.38678366492569[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 22 )[/C][C]0.0167994531518351[/C][C]0.00495097840570737[/C][C]3.39315823564674[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 22 )[/C][C]0.0167986759626417[/C][C]0.00489250687782115[/C][C]3.4335518338858[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 22 )[/C][C]0.0164722302793984[/C][C]0.00475459183333481[/C][C]3.46448882613022[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 22 )[/C][C]0.0185766796786979[/C][C]0.00424845685264271[/C][C]4.37257110593991[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 22 )[/C][C]0.0180841924842126[/C][C]0.0041355431978824[/C][C]4.37286992757629[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 22 )[/C][C]0.0194542834078484[/C][C]0.00376875447598624[/C][C]5.1619927835064[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 22 )[/C][C]0.0191738869748972[/C][C]0.00362247326825777[/C][C]5.29303753402684[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 22 )[/C][C]0.0199696559540348[/C][C]0.00342317373742293[/C][C]5.83366708377138[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 22 )[/C][C]0.0199019977452414[/C][C]0.00340452311092182[/C][C]5.84575198840482[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 22 )[/C][C]0.0196533873200025[/C][C]0.00331117503010378[/C][C]5.93547219380501[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 22 )[/C][C]0.0198579453014337[/C][C]0.00323296319099268[/C][C]6.1423357236976[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 22 )[/C][C]0.0224080734941513[/C][C]0.00280517195088371[/C][C]7.98812831673014[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 22 )[/C][C]0.0222093205784346[/C][C]0.00257929807106606[/C][C]8.61060643884994[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 22 )[/C][C]0.0220486128956818[/C][C]0.00251892310488411[/C][C]8.75319014420497[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 22 )[/C][C]0.0217758278602089[/C][C]0.00229905701160703[/C][C]9.47163456594217[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 22 )[/C][C]0.0227800914117150[/C][C]0.00208007300477556[/C][C]10.9515826412896[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 22 )[/C][C]0.0166202148782027[/C][C]0.00565846646255431[/C][C]2.93722954588301[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 22 )[/C][C]0.0172348015452526[/C][C]0.00531964121361503[/C][C]3.23984284901434[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 22 )[/C][C]0.0177611028687522[/C][C]0.00503615266171033[/C][C]3.52672050706269[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 22 )[/C][C]0.0181139905179737[/C][C]0.00489305774560195[/C][C]3.70197767117202[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 22 )[/C][C]0.0183999862270496[/C][C]0.0047550058017599[/C][C]3.86960331788439[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 22 )[/C][C]0.0187165741539259[/C][C]0.0046039002956624[/C][C]4.06537347725794[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 22 )[/C][C]0.0190479118005227[/C][C]0.0044479513275955[/C][C]4.28240113203302[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 22 )[/C][C]0.0194698914348702[/C][C]0.00428278047077411[/C][C]4.54608672280395[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 22 )[/C][C]0.0199264512222154[/C][C]0.00408863684485823[/C][C]4.87361729063183[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 22 )[/C][C]0.0204735736883354[/C][C]0.00387578409730096[/C][C]5.28243399899207[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 22 )[/C][C]0.0207560001297703[/C][C]0.00374135210605047[/C][C]5.54772700922855[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 22 )[/C][C]0.0211344591408747[/C][C]0.00359263843465470[/C][C]5.8827125315509[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 22 )[/C][C]0.0213632635598030[/C][C]0.00349221638657467[/C][C]6.11739399709911[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 22 )[/C][C]0.0216525894595835[/C][C]0.00339163137661548[/C][C]6.38412228665919[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 22 )[/C][C]0.0218702661871351[/C][C]0.00330492638518703[/C][C]6.61747453291534[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 22 )[/C][C]0.0221214547311482[/C][C]0.0031864034622581[/C][C]6.94245251524786[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 22 )[/C][C]0.0224346375276383[/C][C]0.00304301919210955[/C][C]7.37249294575948[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 22 )[/C][C]0.0227622245848598[/C][C]0.00285970799530254[/C][C]7.95963245976505[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 22 )[/C][C]0.0228076807593377[/C][C]0.00273958526487500[/C][C]8.32523121355681[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 22 )[/C][C]0.0228858291650307[/C][C]0.00263260991757520[/C][C]8.69320935556983[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 22 )[/C][C]0.0229980161451234[/C][C]0.00248429554417456[/C][C]9.25735917332849[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 22 )[/C][C]0.0231675536504843[/C][C]0.00233589159519474[/C][C]9.91807740485183[/C][/ROW]
[ROW][C]Median[/C][C]0.0248509795595009[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]0.000171066842928502[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]0.0212875755052115[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]0.0221214547311482[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]0.0221214547311482[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]0.0221214547311482[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]0.0224346375276383[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]0.0212875755052115[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]0.0221214547311482[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]0.0221214547311482[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]67[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4896&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4896&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 Mean0.01612919553386610.005987367663154742.6938709030886
Geometric MeanNaN
Harmonic Mean-0.0512080281006703
Quadratic Mean0.0512460405280242
Winsorized Mean ( 1 / 22 )0.01604231995246910.005935949090629642.7025703400646
Winsorized Mean ( 2 / 22 )0.01627646182186550.005743096503645262.83409164577584
Winsorized Mean ( 3 / 22 )0.01682884743722650.005326153356214493.15966257666818
Winsorized Mean ( 4 / 22 )0.0171407513885810.005228393904156163.27839709532127
Winsorized Mean ( 5 / 22 )0.01710055816897540.005168540638791843.30858541396178
Winsorized Mean ( 6 / 22 )0.01714395666709340.005062017053123343.38678366492569
Winsorized Mean ( 7 / 22 )0.01679945315183510.004950978405707373.39315823564674
Winsorized Mean ( 8 / 22 )0.01679867596264170.004892506877821153.4335518338858
Winsorized Mean ( 9 / 22 )0.01647223027939840.004754591833334813.46448882613022
Winsorized Mean ( 10 / 22 )0.01857667967869790.004248456852642714.37257110593991
Winsorized Mean ( 11 / 22 )0.01808419248421260.00413554319788244.37286992757629
Winsorized Mean ( 12 / 22 )0.01945428340784840.003768754475986245.1619927835064
Winsorized Mean ( 13 / 22 )0.01917388697489720.003622473268257775.29303753402684
Winsorized Mean ( 14 / 22 )0.01996965595403480.003423173737422935.83366708377138
Winsorized Mean ( 15 / 22 )0.01990199774524140.003404523110921825.84575198840482
Winsorized Mean ( 16 / 22 )0.01965338732000250.003311175030103785.93547219380501
Winsorized Mean ( 17 / 22 )0.01985794530143370.003232963190992686.1423357236976
Winsorized Mean ( 18 / 22 )0.02240807349415130.002805171950883717.98812831673014
Winsorized Mean ( 19 / 22 )0.02220932057843460.002579298071066068.61060643884994
Winsorized Mean ( 20 / 22 )0.02204861289568180.002518923104884118.75319014420497
Winsorized Mean ( 21 / 22 )0.02177582786020890.002299057011607039.47163456594217
Winsorized Mean ( 22 / 22 )0.02278009141171500.0020800730047755610.9515826412896
Trimmed Mean ( 1 / 22 )0.01662021487820270.005658466462554312.93722954588301
Trimmed Mean ( 2 / 22 )0.01723480154525260.005319641213615033.23984284901434
Trimmed Mean ( 3 / 22 )0.01776110286875220.005036152661710333.52672050706269
Trimmed Mean ( 4 / 22 )0.01811399051797370.004893057745601953.70197767117202
Trimmed Mean ( 5 / 22 )0.01839998622704960.00475500580175993.86960331788439
Trimmed Mean ( 6 / 22 )0.01871657415392590.00460390029566244.06537347725794
Trimmed Mean ( 7 / 22 )0.01904791180052270.00444795132759554.28240113203302
Trimmed Mean ( 8 / 22 )0.01946989143487020.004282780470774114.54608672280395
Trimmed Mean ( 9 / 22 )0.01992645122221540.004088636844858234.87361729063183
Trimmed Mean ( 10 / 22 )0.02047357368833540.003875784097300965.28243399899207
Trimmed Mean ( 11 / 22 )0.02075600012977030.003741352106050475.54772700922855
Trimmed Mean ( 12 / 22 )0.02113445914087470.003592638434654705.8827125315509
Trimmed Mean ( 13 / 22 )0.02136326355980300.003492216386574676.11739399709911
Trimmed Mean ( 14 / 22 )0.02165258945958350.003391631376615486.38412228665919
Trimmed Mean ( 15 / 22 )0.02187026618713510.003304926385187036.61747453291534
Trimmed Mean ( 16 / 22 )0.02212145473114820.00318640346225816.94245251524786
Trimmed Mean ( 17 / 22 )0.02243463752763830.003043019192109557.37249294575948
Trimmed Mean ( 18 / 22 )0.02276222458485980.002859707995302547.95963245976505
Trimmed Mean ( 19 / 22 )0.02280768075933770.002739585264875008.32523121355681
Trimmed Mean ( 20 / 22 )0.02288582916503070.002632609917575208.69320935556983
Trimmed Mean ( 21 / 22 )0.02299801614512340.002484295544174569.25735917332849
Trimmed Mean ( 22 / 22 )0.02316755365048430.002335891595194749.91807740485183
Median0.0248509795595009
Midrange0.000171066842928502
Midmean - Weighted Average at Xnp0.0212875755052115
Midmean - Weighted Average at X(n+1)p0.0221214547311482
Midmean - Empirical Distribution Function0.0221214547311482
Midmean - Empirical Distribution Function - Averaging0.0221214547311482
Midmean - Empirical Distribution Function - Interpolation0.0224346375276383
Midmean - Closest Observation0.0212875755052115
Midmean - True Basic - Statistics Graphics Toolkit0.0221214547311482
Midmean - MS Excel (old versions)0.0221214547311482
Number of observations67



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')