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Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSat, 15 Dec 2007 05:29:46 -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/15/t1197720859zvku15d2alw4y3w.htm/, Retrieved Thu, 02 May 2024 22:29:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4028, Retrieved Thu, 02 May 2024 22:29:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact202
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Totale uitvoer] [2007-12-15 12:29:46] [89d26cd0a44959d9c8b169f34617598a] [Current]
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Dataseries X:
-52.3790054485179
-289.481355589424
494.54194663302
-161.125204916602
-45.2267527881661
1005.83628177171
-36.925832079854
342.83495958438
1314.25091544284
886.810954721906
-316.233471096358
973.745937230418
-92.417005828337
1076.25126575013
-75.5456237596632
-214.411641621588
626.287476189197
379.357831457496
-137.635148298157
-812.262311443738
-609.835033108426
-44.651415815144
472.685585828795
-562.929480961792
-1192.81827342019
-237.703233795914
566.534266798622
-793.652665734495
460.448716456503
423.638176953718
957.424373075894
-106.311946635185
570.668466212301
-2032.19598908302
693.606967808613
92.597484465634
809.012710462503
-494.504523392054
-1073.88309892307
881.714920620533
36.6734655900618
-1601.5256027092
-224.158321349372
183.388509822322
118.159975774703
709.77497795103
197.046298972702
609.162452013902
973.491760730554




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=4028&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=4028&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4028&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 Mean94.8598722555351101.0324576167470.938904927121273
Geometric MeanNaN
Harmonic Mean-626.506924338517
Quadratic Mean706.371824879905
Winsorized Mean ( 1 / 16 )98.7919281061796.3557688637761.02528296199720
Winsorized Mean ( 2 / 16 )112.59977893517490.15436229014581.24896650672090
Winsorized Mean ( 3 / 16 )117.91680934063387.6206683599671.34576477842193
Winsorized Mean ( 4 / 16 )139.25285921650781.99401610074481.69832953474812
Winsorized Mean ( 5 / 16 )139.51227330371081.19129231226651.71831571256604
Winsorized Mean ( 6 / 16 )153.37401382682274.27720868860882.06488661239021
Winsorized Mean ( 7 / 16 )159.34680211900272.71623155970382.19135121143028
Winsorized Mean ( 8 / 16 )158.64847516581168.0299761701482.33203778829820
Winsorized Mean ( 9 / 16 )173.16479920781258.2918357740942.97065269789924
Winsorized Mean ( 10 / 16 )175.32482071077456.71763468946023.09118710028566
Winsorized Mean ( 11 / 16 )171.83594177026551.95092944021533.30765866216142
Winsorized Mean ( 12 / 16 )170.95917971424450.64877450226393.37538630291246
Winsorized Mean ( 13 / 16 )163.33234340894548.41241717838063.37376964275777
Winsorized Mean ( 14 / 16 )177.3758397778945.79281929844553.87344222293628
Winsorized Mean ( 15 / 16 )162.52820807978140.86795125442923.97691107802146
Winsorized Mean ( 16 / 16 )165.61942142141238.12172129542544.34448959263775
Trimmed Mean ( 1 / 16 )94.859872255535191.19254423738891.04021521768928
Trimmed Mean ( 2 / 16 )114.17188966300984.37988212029421.35307003036864
Trimmed Mean ( 3 / 16 )141.35663122718580.05771902417841.76568397089222
Trimmed Mean ( 4 / 16 )141.35663122718575.71540891312841.86694667910160
Trimmed Mean ( 5 / 16 )154.28827833781572.5338820425482.12712009881548
Trimmed Mean ( 6 / 16 )158.20192291441668.51524226319222.30900333544329
Trimmed Mean ( 7 / 16 )159.32843503485465.67082717968742.42616762841898
Trimmed Mean ( 8 / 16 )159.32843503485462.22335549447262.56058892627557
Trimmed Mean ( 9 / 16 )159.45811611260459.01499743012362.70199310440383
Trimmed Mean ( 10 / 16 )156.88483078055357.76686690404242.71582724126544
Trimmed Mean ( 11 / 16 )153.53831408951356.26095408456572.7290385772472
Trimmed Mean ( 12 / 16 )150.27800952094355.45583226553972.70986843730638
Trimmed Mean ( 13 / 16 )146.60635249387154.33976767183082.69795692501407
Trimmed Mean ( 14 / 16 )143.60425156039753.08954933123312.70494388009267
Trimmed Mean ( 15 / 16 )137.38316952033251.62009585994742.66142802006939
Trimmed Mean ( 16 / 16 )137.38316952033251.00859849077552.69333354738568
Median92.597484465634
Midrange-358.97253682009
Midmean - Weighted Average at Xnp131.157824417070
Midmean - Weighted Average at X(n+1)p150.278009520943
Midmean - Empirical Distribution Function150.278009520943
Midmean - Empirical Distribution Function - Averaging150.278009520943
Midmean - Empirical Distribution Function - Interpolation150.278009520943
Midmean - Closest Observation135.355654008756
Midmean - True Basic - Statistics Graphics Toolkit150.278009520943
Midmean - MS Excel (old versions)150.278009520943
Number of observations49

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 94.8598722555351 & 101.032457616747 & 0.938904927121273 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & -626.506924338517 &  &  \tabularnewline
Quadratic Mean & 706.371824879905 &  &  \tabularnewline
Winsorized Mean ( 1 / 16 ) & 98.79192810617 & 96.355768863776 & 1.02528296199720 \tabularnewline
Winsorized Mean ( 2 / 16 ) & 112.599778935174 & 90.1543622901458 & 1.24896650672090 \tabularnewline
Winsorized Mean ( 3 / 16 ) & 117.916809340633 & 87.620668359967 & 1.34576477842193 \tabularnewline
Winsorized Mean ( 4 / 16 ) & 139.252859216507 & 81.9940161007448 & 1.69832953474812 \tabularnewline
Winsorized Mean ( 5 / 16 ) & 139.512273303710 & 81.1912923122665 & 1.71831571256604 \tabularnewline
Winsorized Mean ( 6 / 16 ) & 153.374013826822 & 74.2772086886088 & 2.06488661239021 \tabularnewline
Winsorized Mean ( 7 / 16 ) & 159.346802119002 & 72.7162315597038 & 2.19135121143028 \tabularnewline
Winsorized Mean ( 8 / 16 ) & 158.648475165811 & 68.029976170148 & 2.33203778829820 \tabularnewline
Winsorized Mean ( 9 / 16 ) & 173.164799207812 & 58.291835774094 & 2.97065269789924 \tabularnewline
Winsorized Mean ( 10 / 16 ) & 175.324820710774 & 56.7176346894602 & 3.09118710028566 \tabularnewline
Winsorized Mean ( 11 / 16 ) & 171.835941770265 & 51.9509294402153 & 3.30765866216142 \tabularnewline
Winsorized Mean ( 12 / 16 ) & 170.959179714244 & 50.6487745022639 & 3.37538630291246 \tabularnewline
Winsorized Mean ( 13 / 16 ) & 163.332343408945 & 48.4124171783806 & 3.37376964275777 \tabularnewline
Winsorized Mean ( 14 / 16 ) & 177.37583977789 & 45.7928192984455 & 3.87344222293628 \tabularnewline
Winsorized Mean ( 15 / 16 ) & 162.528208079781 & 40.8679512544292 & 3.97691107802146 \tabularnewline
Winsorized Mean ( 16 / 16 ) & 165.619421421412 & 38.1217212954254 & 4.34448959263775 \tabularnewline
Trimmed Mean ( 1 / 16 ) & 94.8598722555351 & 91.1925442373889 & 1.04021521768928 \tabularnewline
Trimmed Mean ( 2 / 16 ) & 114.171889663009 & 84.3798821202942 & 1.35307003036864 \tabularnewline
Trimmed Mean ( 3 / 16 ) & 141.356631227185 & 80.0577190241784 & 1.76568397089222 \tabularnewline
Trimmed Mean ( 4 / 16 ) & 141.356631227185 & 75.7154089131284 & 1.86694667910160 \tabularnewline
Trimmed Mean ( 5 / 16 ) & 154.288278337815 & 72.533882042548 & 2.12712009881548 \tabularnewline
Trimmed Mean ( 6 / 16 ) & 158.201922914416 & 68.5152422631922 & 2.30900333544329 \tabularnewline
Trimmed Mean ( 7 / 16 ) & 159.328435034854 & 65.6708271796874 & 2.42616762841898 \tabularnewline
Trimmed Mean ( 8 / 16 ) & 159.328435034854 & 62.2233554944726 & 2.56058892627557 \tabularnewline
Trimmed Mean ( 9 / 16 ) & 159.458116112604 & 59.0149974301236 & 2.70199310440383 \tabularnewline
Trimmed Mean ( 10 / 16 ) & 156.884830780553 & 57.7668669040424 & 2.71582724126544 \tabularnewline
Trimmed Mean ( 11 / 16 ) & 153.538314089513 & 56.2609540845657 & 2.7290385772472 \tabularnewline
Trimmed Mean ( 12 / 16 ) & 150.278009520943 & 55.4558322655397 & 2.70986843730638 \tabularnewline
Trimmed Mean ( 13 / 16 ) & 146.606352493871 & 54.3397676718308 & 2.69795692501407 \tabularnewline
Trimmed Mean ( 14 / 16 ) & 143.604251560397 & 53.0895493312331 & 2.70494388009267 \tabularnewline
Trimmed Mean ( 15 / 16 ) & 137.383169520332 & 51.6200958599474 & 2.66142802006939 \tabularnewline
Trimmed Mean ( 16 / 16 ) & 137.383169520332 & 51.0085984907755 & 2.69333354738568 \tabularnewline
Median & 92.597484465634 &  &  \tabularnewline
Midrange & -358.97253682009 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 131.157824417070 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 150.278009520943 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 150.278009520943 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 150.278009520943 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 150.278009520943 &  &  \tabularnewline
Midmean - Closest Observation & 135.355654008756 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 150.278009520943 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 150.278009520943 &  &  \tabularnewline
Number of observations & 49 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4028&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]94.8598722555351[/C][C]101.032457616747[/C][C]0.938904927121273[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]-626.506924338517[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]706.371824879905[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 16 )[/C][C]98.79192810617[/C][C]96.355768863776[/C][C]1.02528296199720[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 16 )[/C][C]112.599778935174[/C][C]90.1543622901458[/C][C]1.24896650672090[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 16 )[/C][C]117.916809340633[/C][C]87.620668359967[/C][C]1.34576477842193[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 16 )[/C][C]139.252859216507[/C][C]81.9940161007448[/C][C]1.69832953474812[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 16 )[/C][C]139.512273303710[/C][C]81.1912923122665[/C][C]1.71831571256604[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 16 )[/C][C]153.374013826822[/C][C]74.2772086886088[/C][C]2.06488661239021[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 16 )[/C][C]159.346802119002[/C][C]72.7162315597038[/C][C]2.19135121143028[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 16 )[/C][C]158.648475165811[/C][C]68.029976170148[/C][C]2.33203778829820[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 16 )[/C][C]173.164799207812[/C][C]58.291835774094[/C][C]2.97065269789924[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 16 )[/C][C]175.324820710774[/C][C]56.7176346894602[/C][C]3.09118710028566[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 16 )[/C][C]171.835941770265[/C][C]51.9509294402153[/C][C]3.30765866216142[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 16 )[/C][C]170.959179714244[/C][C]50.6487745022639[/C][C]3.37538630291246[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 16 )[/C][C]163.332343408945[/C][C]48.4124171783806[/C][C]3.37376964275777[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 16 )[/C][C]177.37583977789[/C][C]45.7928192984455[/C][C]3.87344222293628[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 16 )[/C][C]162.528208079781[/C][C]40.8679512544292[/C][C]3.97691107802146[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 16 )[/C][C]165.619421421412[/C][C]38.1217212954254[/C][C]4.34448959263775[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 16 )[/C][C]94.8598722555351[/C][C]91.1925442373889[/C][C]1.04021521768928[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 16 )[/C][C]114.171889663009[/C][C]84.3798821202942[/C][C]1.35307003036864[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 16 )[/C][C]141.356631227185[/C][C]80.0577190241784[/C][C]1.76568397089222[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 16 )[/C][C]141.356631227185[/C][C]75.7154089131284[/C][C]1.86694667910160[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 16 )[/C][C]154.288278337815[/C][C]72.533882042548[/C][C]2.12712009881548[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 16 )[/C][C]158.201922914416[/C][C]68.5152422631922[/C][C]2.30900333544329[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 16 )[/C][C]159.328435034854[/C][C]65.6708271796874[/C][C]2.42616762841898[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 16 )[/C][C]159.328435034854[/C][C]62.2233554944726[/C][C]2.56058892627557[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 16 )[/C][C]159.458116112604[/C][C]59.0149974301236[/C][C]2.70199310440383[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 16 )[/C][C]156.884830780553[/C][C]57.7668669040424[/C][C]2.71582724126544[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 16 )[/C][C]153.538314089513[/C][C]56.2609540845657[/C][C]2.7290385772472[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 16 )[/C][C]150.278009520943[/C][C]55.4558322655397[/C][C]2.70986843730638[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 16 )[/C][C]146.606352493871[/C][C]54.3397676718308[/C][C]2.69795692501407[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 16 )[/C][C]143.604251560397[/C][C]53.0895493312331[/C][C]2.70494388009267[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 16 )[/C][C]137.383169520332[/C][C]51.6200958599474[/C][C]2.66142802006939[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 16 )[/C][C]137.383169520332[/C][C]51.0085984907755[/C][C]2.69333354738568[/C][/ROW]
[ROW][C]Median[/C][C]92.597484465634[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-358.97253682009[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]131.157824417070[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]150.278009520943[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]150.278009520943[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]150.278009520943[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]150.278009520943[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]135.355654008756[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]150.278009520943[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]150.278009520943[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]49[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4028&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4028&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 Mean94.8598722555351101.0324576167470.938904927121273
Geometric MeanNaN
Harmonic Mean-626.506924338517
Quadratic Mean706.371824879905
Winsorized Mean ( 1 / 16 )98.7919281061796.3557688637761.02528296199720
Winsorized Mean ( 2 / 16 )112.59977893517490.15436229014581.24896650672090
Winsorized Mean ( 3 / 16 )117.91680934063387.6206683599671.34576477842193
Winsorized Mean ( 4 / 16 )139.25285921650781.99401610074481.69832953474812
Winsorized Mean ( 5 / 16 )139.51227330371081.19129231226651.71831571256604
Winsorized Mean ( 6 / 16 )153.37401382682274.27720868860882.06488661239021
Winsorized Mean ( 7 / 16 )159.34680211900272.71623155970382.19135121143028
Winsorized Mean ( 8 / 16 )158.64847516581168.0299761701482.33203778829820
Winsorized Mean ( 9 / 16 )173.16479920781258.2918357740942.97065269789924
Winsorized Mean ( 10 / 16 )175.32482071077456.71763468946023.09118710028566
Winsorized Mean ( 11 / 16 )171.83594177026551.95092944021533.30765866216142
Winsorized Mean ( 12 / 16 )170.95917971424450.64877450226393.37538630291246
Winsorized Mean ( 13 / 16 )163.33234340894548.41241717838063.37376964275777
Winsorized Mean ( 14 / 16 )177.3758397778945.79281929844553.87344222293628
Winsorized Mean ( 15 / 16 )162.52820807978140.86795125442923.97691107802146
Winsorized Mean ( 16 / 16 )165.61942142141238.12172129542544.34448959263775
Trimmed Mean ( 1 / 16 )94.859872255535191.19254423738891.04021521768928
Trimmed Mean ( 2 / 16 )114.17188966300984.37988212029421.35307003036864
Trimmed Mean ( 3 / 16 )141.35663122718580.05771902417841.76568397089222
Trimmed Mean ( 4 / 16 )141.35663122718575.71540891312841.86694667910160
Trimmed Mean ( 5 / 16 )154.28827833781572.5338820425482.12712009881548
Trimmed Mean ( 6 / 16 )158.20192291441668.51524226319222.30900333544329
Trimmed Mean ( 7 / 16 )159.32843503485465.67082717968742.42616762841898
Trimmed Mean ( 8 / 16 )159.32843503485462.22335549447262.56058892627557
Trimmed Mean ( 9 / 16 )159.45811611260459.01499743012362.70199310440383
Trimmed Mean ( 10 / 16 )156.88483078055357.76686690404242.71582724126544
Trimmed Mean ( 11 / 16 )153.53831408951356.26095408456572.7290385772472
Trimmed Mean ( 12 / 16 )150.27800952094355.45583226553972.70986843730638
Trimmed Mean ( 13 / 16 )146.60635249387154.33976767183082.69795692501407
Trimmed Mean ( 14 / 16 )143.60425156039753.08954933123312.70494388009267
Trimmed Mean ( 15 / 16 )137.38316952033251.62009585994742.66142802006939
Trimmed Mean ( 16 / 16 )137.38316952033251.00859849077552.69333354738568
Median92.597484465634
Midrange-358.97253682009
Midmean - Weighted Average at Xnp131.157824417070
Midmean - Weighted Average at X(n+1)p150.278009520943
Midmean - Empirical Distribution Function150.278009520943
Midmean - Empirical Distribution Function - Averaging150.278009520943
Midmean - Empirical Distribution Function - Interpolation150.278009520943
Midmean - Closest Observation135.355654008756
Midmean - True Basic - Statistics Graphics Toolkit150.278009520943
Midmean - MS Excel (old versions)150.278009520943
Number of observations49



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')