Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationWed, 30 Dec 2009 07:34:46 -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/2009/Dec/30/t1262183769sdybvjhyjl2o37l.htm/, Retrieved Sun, 28 Apr 2024 23:16:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71298, Retrieved Sun, 28 Apr 2024 23:16:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact85
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [ct residuals: gou...] [2009-12-30 14:34:46] [47a6e19efaace1829ce1b2ce66897f57] [Current]
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Dataseries X:
10.0699947754242 
65.7731821094984 
-150.198460641018 
-247.385699879324 
-617.482560413075 
51.0478428322415 
150.198460641018 
84.4252785302456 
543.855864020419 
224.806846318910 
-171.795624916197 
-268.982864154503 
268.980915214612 
48.2372215011231 
-15.8551476059929 
-9.99671370398755 
395.817726508698 
647.094559970665 
-166.144852394007 
167.617926105329 
-48.5310341586937 
-213.622033975345 
-627.664384516658 
72.1940493853472 
218.805950614653 
-100.619843111337 
-115.427984589998 
278.048375417337 
248.424972151986 
-199.151424986032 
-540.902975307326 
-485.050018565342 
165.142113813998 
-36.6168306733252 
221.913381911367 
443.190215373332 
423.377418308653 
-416.046458411329 
319.620664685339 
-97.8606247660136 
-149.337258631349 
-258.90379688133 
446.007394166028 
322.720154100021 
-609.526104714676 
100.143756962003 
29.7130337919953 
57.8513135939775 
-11.4823848833566 
234.481837167355 
10.6151875253181 
-238.047006127332 
-200.474990717328 
108.003560154013 
28.6146398093169 
44.8540521739887 
165.721797248028 
634.427436873995 
-16.1434831040024 
77.760039919327 
497.951350724663 
581.045636837325 
444.237221500664 
828.050840139345 
773.526652430677 
376.33260304533 
-62.7154985140041 
1101.85596917999 
1048.33260304533 
-2020.00848959803 
883.333424619334 
-231.001369290005 
-799.720975674025 
-299.198431113364 
606.946421280643 
-491.772089671373 
134.561882663964 
695.28066747398 
-411.427984589998 
29.8425501379443 
-435.728095982053 
137.167582608094 
-287.011502036044 
129.193227811344 
888.723440396036 
628.859529334008 
531.800473454634 
114.337806347350 
1596.80595061465 
607.51378110463 
40.0054771600226 
-1570.28888321401 
-98.4255198679894 
-7.33041218132348 
809.668218528674 
-1115.95354158867 
260.180630343297 
1047.84939658797 
-575.484849605367 
445.666027664665 
865.883257531252 
2621.37111957463 
-650.380430746663 
-832.694411447923 
141.239960080675 
-141.475538433329 
-543.915025059374 
293.347665235389 
508.042350541313 
406.842002421941 
1725.52966486869 




Summary of computational 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 computational 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=71298&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]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=71298&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71298&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean112.82071115785256.0655399590312.01230044765990
Geometric MeanNaN
Harmonic Mean-4566.78513243971
Quadratic Mean598.74572037294
Winsorized Mean ( 1 / 37 )108.80159540720451.96416358085652.09378132754717
Winsorized Mean ( 2 / 37 )114.66847157605749.17716368529142.33174227594491
Winsorized Mean ( 3 / 37 )108.94709721676244.342102142912.45696735047961
Winsorized Mean ( 4 / 37 )108.20655918574343.73040608868182.47440096866031
Winsorized Mean ( 5 / 37 )114.91184470241042.54000477295982.70126543980674
Winsorized Mean ( 6 / 37 )107.53833605581940.72919563279392.64032555480257
Winsorized Mean ( 7 / 37 )107.84052216652340.56515302227112.65845224612654
Winsorized Mean ( 8 / 37 )107.15629071501540.25509989494982.66193081111836
Winsorized Mean ( 9 / 37 )106.84889917858839.29503073936932.71914532621900
Winsorized Mean ( 10 / 37 )108.03693547906738.57692620777872.80055841922632
Winsorized Mean ( 11 / 37 )104.75383025559537.94782975015292.76046959589758
Winsorized Mean ( 12 / 37 )101.60625195065035.82076761997622.83651799505231
Winsorized Mean ( 13 / 37 )96.750103543760434.87153752920012.77447197338934
Winsorized Mean ( 14 / 37 )101.37323140693833.71960768207213.00635856629006
Winsorized Mean ( 15 / 37 )103.28049222190233.22991737046493.10805744927006
Winsorized Mean ( 16 / 37 )100.86935356849032.69726483077643.08494774992758
Winsorized Mean ( 17 / 37 )117.97077061439130.38237417246823.88286872989976
Winsorized Mean ( 18 / 37 )115.74690217666129.52830532786833.9198626840065
Winsorized Mean ( 19 / 37 )112.46706826880628.24939055967813.98122104727230
Winsorized Mean ( 20 / 37 )112.11097398184927.72722848539294.0433530542337
Winsorized Mean ( 21 / 37 )109.79529340403326.85053852205674.08912816828013
Winsorized Mean ( 22 / 37 )109.64618769752426.35886554540184.15974608272362
Winsorized Mean ( 23 / 37 )100.34293225977524.77823673027574.04963974442821
Winsorized Mean ( 24 / 37 )104.02681740859624.31727122220194.27789847216159
Winsorized Mean ( 25 / 37 )106.66605999733923.92747777607714.45788983676266
Winsorized Mean ( 26 / 37 )106.73083972439323.85987628719124.47323525234245
Winsorized Mean ( 27 / 37 )108.56562423916122.47881541388994.82968618408945
Winsorized Mean ( 28 / 37 )105.81994843549821.78963201657724.8564357743624
Winsorized Mean ( 29 / 37 )107.10590662786420.95950602966995.11013506121025
Winsorized Mean ( 30 / 37 )102.07241434308020.27984674005795.03319456263253
Winsorized Mean ( 31 / 37 )89.295183792035618.23577046506154.89670474648269
Winsorized Mean ( 32 / 37 )95.910842005700217.28146758014195.54992459760254
Winsorized Mean ( 33 / 37 )92.502370716938615.88442398447505.82346396742795
Winsorized Mean ( 34 / 37 )88.488236811173315.27614344165635.79257697789588
Winsorized Mean ( 35 / 37 )85.807247815441514.93560930812845.74514544704532
Winsorized Mean ( 36 / 37 )94.351520695666813.36821963530537.05789725705028
Winsorized Mean ( 37 / 37 )95.161122750333212.42636641847367.65800070154557
Trimmed Mean ( 1 / 37 )109.37372760133048.36536163029872.26140617819370
Trimmed Mean ( 2 / 37 )109.96724791486344.14581927642672.49100027403011
Trimmed Mean ( 3 / 37 )107.48231540823241.03701015518702.61915561103923
Trimmed Mean ( 4 / 37 )106.95613165177039.65025996885222.6974887866004
Trimmed Mean ( 5 / 37 )106.61257359169338.29105654360712.78426826562696
Trimmed Mean ( 6 / 37 )104.75152491838037.09365505889292.82397420130393
Trimmed Mean ( 7 / 37 )104.75152491838036.19328441852562.89422545097242
Trimmed Mean ( 8 / 37 )103.61569522983235.20915449572562.94286235252854
Trimmed Mean ( 9 / 37 )103.08746122599434.15433666773523.01828321916667
Trimmed Mean ( 10 / 37 )102.57766926904933.13987483178313.09529440861591
Trimmed Mean ( 11 / 37 )101.89679449454132.11299610279053.17307030986395
Trimmed Mean ( 12 / 37 )101.56541417115931.04785715934733.27125358925395
Trimmed Mean ( 13 / 37 )101.56097005986130.19050648787373.36400351880994
Trimmed Mean ( 14 / 37 )101.56097005986129.35823612774663.45936893544757
Trimmed Mean ( 15 / 37 )102.12269842951828.58143279816973.57304335127865
Trimmed Mean ( 16 / 37 )102.01424685909227.75708691564163.67525047455916
Trimmed Mean ( 17 / 37 )102.11739877082626.88039498183153.79895454809528
Trimmed Mean ( 18 / 37 )100.73722286915126.20895235501973.84361883316017
Trimmed Mean ( 19 / 37 )99.469281923083125.55019890442163.89309227279125
Trimmed Mean ( 20 / 37 )98.399782824213424.96623769375333.94131402701631
Trimmed Mean ( 21 / 37 )97.296926144142724.35125787012723.99556058512695
Trimmed Mean ( 22 / 37 )96.310914228117323.75196317054194.05486121448545
Trimmed Mean ( 23 / 37 )95.275798595177423.10883968541174.12291572801571
Trimmed Mean ( 24 / 37 )94.887633076357222.58305435178764.20171831490305
Trimmed Mean ( 25 / 37 )94.194703116740822.01455629382234.27874638305445
Trimmed Mean ( 26 / 37 )93.256180666743221.38110506481854.36161650130009
Trimmed Mean ( 27 / 37 )92.24694506930820.61369584706654.47503183095793
Trimmed Mean ( 28 / 37 )92.24694506930819.90644079237604.63402503900333
Trimmed Mean ( 29 / 37 )89.920696708116219.15267718067584.6949413839044
Trimmed Mean ( 30 / 37 )88.63093450318618.36081482496194.82717871445935
Trimmed Mean ( 31 / 37 )88.63093450318617.49882393627675.06496521285901
Trimmed Mean ( 32 / 37 )87.48803616131516.83084372701535.19807786111681
Trimmed Mean ( 33 / 37 )86.838778210810416.16465288925755.3721399899976
Trimmed Mean ( 34 / 37 )86.395748775870115.60111502963405.53779320335521
Trimmed Mean ( 35 / 37 )86.229130288123614.99349904188035.75110119707653
Trimmed Mean ( 36 / 37 )86.263437214473614.26075187953856.04901045492876
Trimmed Mean ( 37 / 37 )85.589430257707413.6706817202626.26080191237655
Median72.1940493853472
Midrange300.6813149883
Midmean - Weighted Average at Xnp86.3339009043196
Midmean - Weighted Average at X(n+1)p92.246945069308
Midmean - Empirical Distribution Function92.246945069308
Midmean - Empirical Distribution Function - Averaging92.246945069308
Midmean - Empirical Distribution Function - Interpolation91.0271650101472
Midmean - Closest Observation86.3339009043196
Midmean - True Basic - Statistics Graphics Toolkit92.246945069308
Midmean - MS Excel (old versions)92.246945069308
Number of observations111

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 112.820711157852 & 56.065539959031 & 2.01230044765990 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & -4566.78513243971 &  &  \tabularnewline
Quadratic Mean & 598.74572037294 &  &  \tabularnewline
Winsorized Mean ( 1 / 37 ) & 108.801595407204 & 51.9641635808565 & 2.09378132754717 \tabularnewline
Winsorized Mean ( 2 / 37 ) & 114.668471576057 & 49.1771636852914 & 2.33174227594491 \tabularnewline
Winsorized Mean ( 3 / 37 ) & 108.947097216762 & 44.34210214291 & 2.45696735047961 \tabularnewline
Winsorized Mean ( 4 / 37 ) & 108.206559185743 & 43.7304060886818 & 2.47440096866031 \tabularnewline
Winsorized Mean ( 5 / 37 ) & 114.911844702410 & 42.5400047729598 & 2.70126543980674 \tabularnewline
Winsorized Mean ( 6 / 37 ) & 107.538336055819 & 40.7291956327939 & 2.64032555480257 \tabularnewline
Winsorized Mean ( 7 / 37 ) & 107.840522166523 & 40.5651530222711 & 2.65845224612654 \tabularnewline
Winsorized Mean ( 8 / 37 ) & 107.156290715015 & 40.2550998949498 & 2.66193081111836 \tabularnewline
Winsorized Mean ( 9 / 37 ) & 106.848899178588 & 39.2950307393693 & 2.71914532621900 \tabularnewline
Winsorized Mean ( 10 / 37 ) & 108.036935479067 & 38.5769262077787 & 2.80055841922632 \tabularnewline
Winsorized Mean ( 11 / 37 ) & 104.753830255595 & 37.9478297501529 & 2.76046959589758 \tabularnewline
Winsorized Mean ( 12 / 37 ) & 101.606251950650 & 35.8207676199762 & 2.83651799505231 \tabularnewline
Winsorized Mean ( 13 / 37 ) & 96.7501035437604 & 34.8715375292001 & 2.77447197338934 \tabularnewline
Winsorized Mean ( 14 / 37 ) & 101.373231406938 & 33.7196076820721 & 3.00635856629006 \tabularnewline
Winsorized Mean ( 15 / 37 ) & 103.280492221902 & 33.2299173704649 & 3.10805744927006 \tabularnewline
Winsorized Mean ( 16 / 37 ) & 100.869353568490 & 32.6972648307764 & 3.08494774992758 \tabularnewline
Winsorized Mean ( 17 / 37 ) & 117.970770614391 & 30.3823741724682 & 3.88286872989976 \tabularnewline
Winsorized Mean ( 18 / 37 ) & 115.746902176661 & 29.5283053278683 & 3.9198626840065 \tabularnewline
Winsorized Mean ( 19 / 37 ) & 112.467068268806 & 28.2493905596781 & 3.98122104727230 \tabularnewline
Winsorized Mean ( 20 / 37 ) & 112.110973981849 & 27.7272284853929 & 4.0433530542337 \tabularnewline
Winsorized Mean ( 21 / 37 ) & 109.795293404033 & 26.8505385220567 & 4.08912816828013 \tabularnewline
Winsorized Mean ( 22 / 37 ) & 109.646187697524 & 26.3588655454018 & 4.15974608272362 \tabularnewline
Winsorized Mean ( 23 / 37 ) & 100.342932259775 & 24.7782367302757 & 4.04963974442821 \tabularnewline
Winsorized Mean ( 24 / 37 ) & 104.026817408596 & 24.3172712222019 & 4.27789847216159 \tabularnewline
Winsorized Mean ( 25 / 37 ) & 106.666059997339 & 23.9274777760771 & 4.45788983676266 \tabularnewline
Winsorized Mean ( 26 / 37 ) & 106.730839724393 & 23.8598762871912 & 4.47323525234245 \tabularnewline
Winsorized Mean ( 27 / 37 ) & 108.565624239161 & 22.4788154138899 & 4.82968618408945 \tabularnewline
Winsorized Mean ( 28 / 37 ) & 105.819948435498 & 21.7896320165772 & 4.8564357743624 \tabularnewline
Winsorized Mean ( 29 / 37 ) & 107.105906627864 & 20.9595060296699 & 5.11013506121025 \tabularnewline
Winsorized Mean ( 30 / 37 ) & 102.072414343080 & 20.2798467400579 & 5.03319456263253 \tabularnewline
Winsorized Mean ( 31 / 37 ) & 89.2951837920356 & 18.2357704650615 & 4.89670474648269 \tabularnewline
Winsorized Mean ( 32 / 37 ) & 95.9108420057002 & 17.2814675801419 & 5.54992459760254 \tabularnewline
Winsorized Mean ( 33 / 37 ) & 92.5023707169386 & 15.8844239844750 & 5.82346396742795 \tabularnewline
Winsorized Mean ( 34 / 37 ) & 88.4882368111733 & 15.2761434416563 & 5.79257697789588 \tabularnewline
Winsorized Mean ( 35 / 37 ) & 85.8072478154415 & 14.9356093081284 & 5.74514544704532 \tabularnewline
Winsorized Mean ( 36 / 37 ) & 94.3515206956668 & 13.3682196353053 & 7.05789725705028 \tabularnewline
Winsorized Mean ( 37 / 37 ) & 95.1611227503332 & 12.4263664184736 & 7.65800070154557 \tabularnewline
Trimmed Mean ( 1 / 37 ) & 109.373727601330 & 48.3653616302987 & 2.26140617819370 \tabularnewline
Trimmed Mean ( 2 / 37 ) & 109.967247914863 & 44.1458192764267 & 2.49100027403011 \tabularnewline
Trimmed Mean ( 3 / 37 ) & 107.482315408232 & 41.0370101551870 & 2.61915561103923 \tabularnewline
Trimmed Mean ( 4 / 37 ) & 106.956131651770 & 39.6502599688522 & 2.6974887866004 \tabularnewline
Trimmed Mean ( 5 / 37 ) & 106.612573591693 & 38.2910565436071 & 2.78426826562696 \tabularnewline
Trimmed Mean ( 6 / 37 ) & 104.751524918380 & 37.0936550588929 & 2.82397420130393 \tabularnewline
Trimmed Mean ( 7 / 37 ) & 104.751524918380 & 36.1932844185256 & 2.89422545097242 \tabularnewline
Trimmed Mean ( 8 / 37 ) & 103.615695229832 & 35.2091544957256 & 2.94286235252854 \tabularnewline
Trimmed Mean ( 9 / 37 ) & 103.087461225994 & 34.1543366677352 & 3.01828321916667 \tabularnewline
Trimmed Mean ( 10 / 37 ) & 102.577669269049 & 33.1398748317831 & 3.09529440861591 \tabularnewline
Trimmed Mean ( 11 / 37 ) & 101.896794494541 & 32.1129961027905 & 3.17307030986395 \tabularnewline
Trimmed Mean ( 12 / 37 ) & 101.565414171159 & 31.0478571593473 & 3.27125358925395 \tabularnewline
Trimmed Mean ( 13 / 37 ) & 101.560970059861 & 30.1905064878737 & 3.36400351880994 \tabularnewline
Trimmed Mean ( 14 / 37 ) & 101.560970059861 & 29.3582361277466 & 3.45936893544757 \tabularnewline
Trimmed Mean ( 15 / 37 ) & 102.122698429518 & 28.5814327981697 & 3.57304335127865 \tabularnewline
Trimmed Mean ( 16 / 37 ) & 102.014246859092 & 27.7570869156416 & 3.67525047455916 \tabularnewline
Trimmed Mean ( 17 / 37 ) & 102.117398770826 & 26.8803949818315 & 3.79895454809528 \tabularnewline
Trimmed Mean ( 18 / 37 ) & 100.737222869151 & 26.2089523550197 & 3.84361883316017 \tabularnewline
Trimmed Mean ( 19 / 37 ) & 99.4692819230831 & 25.5501989044216 & 3.89309227279125 \tabularnewline
Trimmed Mean ( 20 / 37 ) & 98.3997828242134 & 24.9662376937533 & 3.94131402701631 \tabularnewline
Trimmed Mean ( 21 / 37 ) & 97.2969261441427 & 24.3512578701272 & 3.99556058512695 \tabularnewline
Trimmed Mean ( 22 / 37 ) & 96.3109142281173 & 23.7519631705419 & 4.05486121448545 \tabularnewline
Trimmed Mean ( 23 / 37 ) & 95.2757985951774 & 23.1088396854117 & 4.12291572801571 \tabularnewline
Trimmed Mean ( 24 / 37 ) & 94.8876330763572 & 22.5830543517876 & 4.20171831490305 \tabularnewline
Trimmed Mean ( 25 / 37 ) & 94.1947031167408 & 22.0145562938223 & 4.27874638305445 \tabularnewline
Trimmed Mean ( 26 / 37 ) & 93.2561806667432 & 21.3811050648185 & 4.36161650130009 \tabularnewline
Trimmed Mean ( 27 / 37 ) & 92.246945069308 & 20.6136958470665 & 4.47503183095793 \tabularnewline
Trimmed Mean ( 28 / 37 ) & 92.246945069308 & 19.9064407923760 & 4.63402503900333 \tabularnewline
Trimmed Mean ( 29 / 37 ) & 89.9206967081162 & 19.1526771806758 & 4.6949413839044 \tabularnewline
Trimmed Mean ( 30 / 37 ) & 88.630934503186 & 18.3608148249619 & 4.82717871445935 \tabularnewline
Trimmed Mean ( 31 / 37 ) & 88.630934503186 & 17.4988239362767 & 5.06496521285901 \tabularnewline
Trimmed Mean ( 32 / 37 ) & 87.488036161315 & 16.8308437270153 & 5.19807786111681 \tabularnewline
Trimmed Mean ( 33 / 37 ) & 86.8387782108104 & 16.1646528892575 & 5.3721399899976 \tabularnewline
Trimmed Mean ( 34 / 37 ) & 86.3957487758701 & 15.6011150296340 & 5.53779320335521 \tabularnewline
Trimmed Mean ( 35 / 37 ) & 86.2291302881236 & 14.9934990418803 & 5.75110119707653 \tabularnewline
Trimmed Mean ( 36 / 37 ) & 86.2634372144736 & 14.2607518795385 & 6.04901045492876 \tabularnewline
Trimmed Mean ( 37 / 37 ) & 85.5894302577074 & 13.670681720262 & 6.26080191237655 \tabularnewline
Median & 72.1940493853472 &  &  \tabularnewline
Midrange & 300.6813149883 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 86.3339009043196 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 92.246945069308 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 92.246945069308 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 92.246945069308 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 91.0271650101472 &  &  \tabularnewline
Midmean - Closest Observation & 86.3339009043196 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 92.246945069308 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 92.246945069308 &  &  \tabularnewline
Number of observations & 111 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71298&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]112.820711157852[/C][C]56.065539959031[/C][C]2.01230044765990[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]-4566.78513243971[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]598.74572037294[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 37 )[/C][C]108.801595407204[/C][C]51.9641635808565[/C][C]2.09378132754717[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 37 )[/C][C]114.668471576057[/C][C]49.1771636852914[/C][C]2.33174227594491[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 37 )[/C][C]108.947097216762[/C][C]44.34210214291[/C][C]2.45696735047961[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 37 )[/C][C]108.206559185743[/C][C]43.7304060886818[/C][C]2.47440096866031[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 37 )[/C][C]114.911844702410[/C][C]42.5400047729598[/C][C]2.70126543980674[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 37 )[/C][C]107.538336055819[/C][C]40.7291956327939[/C][C]2.64032555480257[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 37 )[/C][C]107.840522166523[/C][C]40.5651530222711[/C][C]2.65845224612654[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 37 )[/C][C]107.156290715015[/C][C]40.2550998949498[/C][C]2.66193081111836[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 37 )[/C][C]106.848899178588[/C][C]39.2950307393693[/C][C]2.71914532621900[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 37 )[/C][C]108.036935479067[/C][C]38.5769262077787[/C][C]2.80055841922632[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 37 )[/C][C]104.753830255595[/C][C]37.9478297501529[/C][C]2.76046959589758[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 37 )[/C][C]101.606251950650[/C][C]35.8207676199762[/C][C]2.83651799505231[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 37 )[/C][C]96.7501035437604[/C][C]34.8715375292001[/C][C]2.77447197338934[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 37 )[/C][C]101.373231406938[/C][C]33.7196076820721[/C][C]3.00635856629006[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 37 )[/C][C]103.280492221902[/C][C]33.2299173704649[/C][C]3.10805744927006[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 37 )[/C][C]100.869353568490[/C][C]32.6972648307764[/C][C]3.08494774992758[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 37 )[/C][C]117.970770614391[/C][C]30.3823741724682[/C][C]3.88286872989976[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 37 )[/C][C]115.746902176661[/C][C]29.5283053278683[/C][C]3.9198626840065[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 37 )[/C][C]112.467068268806[/C][C]28.2493905596781[/C][C]3.98122104727230[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 37 )[/C][C]112.110973981849[/C][C]27.7272284853929[/C][C]4.0433530542337[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 37 )[/C][C]109.795293404033[/C][C]26.8505385220567[/C][C]4.08912816828013[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 37 )[/C][C]109.646187697524[/C][C]26.3588655454018[/C][C]4.15974608272362[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 37 )[/C][C]100.342932259775[/C][C]24.7782367302757[/C][C]4.04963974442821[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 37 )[/C][C]104.026817408596[/C][C]24.3172712222019[/C][C]4.27789847216159[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 37 )[/C][C]106.666059997339[/C][C]23.9274777760771[/C][C]4.45788983676266[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 37 )[/C][C]106.730839724393[/C][C]23.8598762871912[/C][C]4.47323525234245[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 37 )[/C][C]108.565624239161[/C][C]22.4788154138899[/C][C]4.82968618408945[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 37 )[/C][C]105.819948435498[/C][C]21.7896320165772[/C][C]4.8564357743624[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 37 )[/C][C]107.105906627864[/C][C]20.9595060296699[/C][C]5.11013506121025[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 37 )[/C][C]102.072414343080[/C][C]20.2798467400579[/C][C]5.03319456263253[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 37 )[/C][C]89.2951837920356[/C][C]18.2357704650615[/C][C]4.89670474648269[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 37 )[/C][C]95.9108420057002[/C][C]17.2814675801419[/C][C]5.54992459760254[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 37 )[/C][C]92.5023707169386[/C][C]15.8844239844750[/C][C]5.82346396742795[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 37 )[/C][C]88.4882368111733[/C][C]15.2761434416563[/C][C]5.79257697789588[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 37 )[/C][C]85.8072478154415[/C][C]14.9356093081284[/C][C]5.74514544704532[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 37 )[/C][C]94.3515206956668[/C][C]13.3682196353053[/C][C]7.05789725705028[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 37 )[/C][C]95.1611227503332[/C][C]12.4263664184736[/C][C]7.65800070154557[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 37 )[/C][C]109.373727601330[/C][C]48.3653616302987[/C][C]2.26140617819370[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 37 )[/C][C]109.967247914863[/C][C]44.1458192764267[/C][C]2.49100027403011[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 37 )[/C][C]107.482315408232[/C][C]41.0370101551870[/C][C]2.61915561103923[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 37 )[/C][C]106.956131651770[/C][C]39.6502599688522[/C][C]2.6974887866004[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 37 )[/C][C]106.612573591693[/C][C]38.2910565436071[/C][C]2.78426826562696[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 37 )[/C][C]104.751524918380[/C][C]37.0936550588929[/C][C]2.82397420130393[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 37 )[/C][C]104.751524918380[/C][C]36.1932844185256[/C][C]2.89422545097242[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 37 )[/C][C]103.615695229832[/C][C]35.2091544957256[/C][C]2.94286235252854[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 37 )[/C][C]103.087461225994[/C][C]34.1543366677352[/C][C]3.01828321916667[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 37 )[/C][C]102.577669269049[/C][C]33.1398748317831[/C][C]3.09529440861591[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 37 )[/C][C]101.896794494541[/C][C]32.1129961027905[/C][C]3.17307030986395[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 37 )[/C][C]101.565414171159[/C][C]31.0478571593473[/C][C]3.27125358925395[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 37 )[/C][C]101.560970059861[/C][C]30.1905064878737[/C][C]3.36400351880994[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 37 )[/C][C]101.560970059861[/C][C]29.3582361277466[/C][C]3.45936893544757[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 37 )[/C][C]102.122698429518[/C][C]28.5814327981697[/C][C]3.57304335127865[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 37 )[/C][C]102.014246859092[/C][C]27.7570869156416[/C][C]3.67525047455916[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 37 )[/C][C]102.117398770826[/C][C]26.8803949818315[/C][C]3.79895454809528[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 37 )[/C][C]100.737222869151[/C][C]26.2089523550197[/C][C]3.84361883316017[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 37 )[/C][C]99.4692819230831[/C][C]25.5501989044216[/C][C]3.89309227279125[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 37 )[/C][C]98.3997828242134[/C][C]24.9662376937533[/C][C]3.94131402701631[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 37 )[/C][C]97.2969261441427[/C][C]24.3512578701272[/C][C]3.99556058512695[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 37 )[/C][C]96.3109142281173[/C][C]23.7519631705419[/C][C]4.05486121448545[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 37 )[/C][C]95.2757985951774[/C][C]23.1088396854117[/C][C]4.12291572801571[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 37 )[/C][C]94.8876330763572[/C][C]22.5830543517876[/C][C]4.20171831490305[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 37 )[/C][C]94.1947031167408[/C][C]22.0145562938223[/C][C]4.27874638305445[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 37 )[/C][C]93.2561806667432[/C][C]21.3811050648185[/C][C]4.36161650130009[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 37 )[/C][C]92.246945069308[/C][C]20.6136958470665[/C][C]4.47503183095793[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 37 )[/C][C]92.246945069308[/C][C]19.9064407923760[/C][C]4.63402503900333[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 37 )[/C][C]89.9206967081162[/C][C]19.1526771806758[/C][C]4.6949413839044[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 37 )[/C][C]88.630934503186[/C][C]18.3608148249619[/C][C]4.82717871445935[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 37 )[/C][C]88.630934503186[/C][C]17.4988239362767[/C][C]5.06496521285901[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 37 )[/C][C]87.488036161315[/C][C]16.8308437270153[/C][C]5.19807786111681[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 37 )[/C][C]86.8387782108104[/C][C]16.1646528892575[/C][C]5.3721399899976[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 37 )[/C][C]86.3957487758701[/C][C]15.6011150296340[/C][C]5.53779320335521[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 37 )[/C][C]86.2291302881236[/C][C]14.9934990418803[/C][C]5.75110119707653[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 37 )[/C][C]86.2634372144736[/C][C]14.2607518795385[/C][C]6.04901045492876[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 37 )[/C][C]85.5894302577074[/C][C]13.670681720262[/C][C]6.26080191237655[/C][/ROW]
[ROW][C]Median[/C][C]72.1940493853472[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]300.6813149883[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]86.3339009043196[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]92.246945069308[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]92.246945069308[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]92.246945069308[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]91.0271650101472[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]86.3339009043196[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]92.246945069308[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]92.246945069308[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]111[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71298&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71298&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 Mean112.82071115785256.0655399590312.01230044765990
Geometric MeanNaN
Harmonic Mean-4566.78513243971
Quadratic Mean598.74572037294
Winsorized Mean ( 1 / 37 )108.80159540720451.96416358085652.09378132754717
Winsorized Mean ( 2 / 37 )114.66847157605749.17716368529142.33174227594491
Winsorized Mean ( 3 / 37 )108.94709721676244.342102142912.45696735047961
Winsorized Mean ( 4 / 37 )108.20655918574343.73040608868182.47440096866031
Winsorized Mean ( 5 / 37 )114.91184470241042.54000477295982.70126543980674
Winsorized Mean ( 6 / 37 )107.53833605581940.72919563279392.64032555480257
Winsorized Mean ( 7 / 37 )107.84052216652340.56515302227112.65845224612654
Winsorized Mean ( 8 / 37 )107.15629071501540.25509989494982.66193081111836
Winsorized Mean ( 9 / 37 )106.84889917858839.29503073936932.71914532621900
Winsorized Mean ( 10 / 37 )108.03693547906738.57692620777872.80055841922632
Winsorized Mean ( 11 / 37 )104.75383025559537.94782975015292.76046959589758
Winsorized Mean ( 12 / 37 )101.60625195065035.82076761997622.83651799505231
Winsorized Mean ( 13 / 37 )96.750103543760434.87153752920012.77447197338934
Winsorized Mean ( 14 / 37 )101.37323140693833.71960768207213.00635856629006
Winsorized Mean ( 15 / 37 )103.28049222190233.22991737046493.10805744927006
Winsorized Mean ( 16 / 37 )100.86935356849032.69726483077643.08494774992758
Winsorized Mean ( 17 / 37 )117.97077061439130.38237417246823.88286872989976
Winsorized Mean ( 18 / 37 )115.74690217666129.52830532786833.9198626840065
Winsorized Mean ( 19 / 37 )112.46706826880628.24939055967813.98122104727230
Winsorized Mean ( 20 / 37 )112.11097398184927.72722848539294.0433530542337
Winsorized Mean ( 21 / 37 )109.79529340403326.85053852205674.08912816828013
Winsorized Mean ( 22 / 37 )109.64618769752426.35886554540184.15974608272362
Winsorized Mean ( 23 / 37 )100.34293225977524.77823673027574.04963974442821
Winsorized Mean ( 24 / 37 )104.02681740859624.31727122220194.27789847216159
Winsorized Mean ( 25 / 37 )106.66605999733923.92747777607714.45788983676266
Winsorized Mean ( 26 / 37 )106.73083972439323.85987628719124.47323525234245
Winsorized Mean ( 27 / 37 )108.56562423916122.47881541388994.82968618408945
Winsorized Mean ( 28 / 37 )105.81994843549821.78963201657724.8564357743624
Winsorized Mean ( 29 / 37 )107.10590662786420.95950602966995.11013506121025
Winsorized Mean ( 30 / 37 )102.07241434308020.27984674005795.03319456263253
Winsorized Mean ( 31 / 37 )89.295183792035618.23577046506154.89670474648269
Winsorized Mean ( 32 / 37 )95.910842005700217.28146758014195.54992459760254
Winsorized Mean ( 33 / 37 )92.502370716938615.88442398447505.82346396742795
Winsorized Mean ( 34 / 37 )88.488236811173315.27614344165635.79257697789588
Winsorized Mean ( 35 / 37 )85.807247815441514.93560930812845.74514544704532
Winsorized Mean ( 36 / 37 )94.351520695666813.36821963530537.05789725705028
Winsorized Mean ( 37 / 37 )95.161122750333212.42636641847367.65800070154557
Trimmed Mean ( 1 / 37 )109.37372760133048.36536163029872.26140617819370
Trimmed Mean ( 2 / 37 )109.96724791486344.14581927642672.49100027403011
Trimmed Mean ( 3 / 37 )107.48231540823241.03701015518702.61915561103923
Trimmed Mean ( 4 / 37 )106.95613165177039.65025996885222.6974887866004
Trimmed Mean ( 5 / 37 )106.61257359169338.29105654360712.78426826562696
Trimmed Mean ( 6 / 37 )104.75152491838037.09365505889292.82397420130393
Trimmed Mean ( 7 / 37 )104.75152491838036.19328441852562.89422545097242
Trimmed Mean ( 8 / 37 )103.61569522983235.20915449572562.94286235252854
Trimmed Mean ( 9 / 37 )103.08746122599434.15433666773523.01828321916667
Trimmed Mean ( 10 / 37 )102.57766926904933.13987483178313.09529440861591
Trimmed Mean ( 11 / 37 )101.89679449454132.11299610279053.17307030986395
Trimmed Mean ( 12 / 37 )101.56541417115931.04785715934733.27125358925395
Trimmed Mean ( 13 / 37 )101.56097005986130.19050648787373.36400351880994
Trimmed Mean ( 14 / 37 )101.56097005986129.35823612774663.45936893544757
Trimmed Mean ( 15 / 37 )102.12269842951828.58143279816973.57304335127865
Trimmed Mean ( 16 / 37 )102.01424685909227.75708691564163.67525047455916
Trimmed Mean ( 17 / 37 )102.11739877082626.88039498183153.79895454809528
Trimmed Mean ( 18 / 37 )100.73722286915126.20895235501973.84361883316017
Trimmed Mean ( 19 / 37 )99.469281923083125.55019890442163.89309227279125
Trimmed Mean ( 20 / 37 )98.399782824213424.96623769375333.94131402701631
Trimmed Mean ( 21 / 37 )97.296926144142724.35125787012723.99556058512695
Trimmed Mean ( 22 / 37 )96.310914228117323.75196317054194.05486121448545
Trimmed Mean ( 23 / 37 )95.275798595177423.10883968541174.12291572801571
Trimmed Mean ( 24 / 37 )94.887633076357222.58305435178764.20171831490305
Trimmed Mean ( 25 / 37 )94.194703116740822.01455629382234.27874638305445
Trimmed Mean ( 26 / 37 )93.256180666743221.38110506481854.36161650130009
Trimmed Mean ( 27 / 37 )92.24694506930820.61369584706654.47503183095793
Trimmed Mean ( 28 / 37 )92.24694506930819.90644079237604.63402503900333
Trimmed Mean ( 29 / 37 )89.920696708116219.15267718067584.6949413839044
Trimmed Mean ( 30 / 37 )88.63093450318618.36081482496194.82717871445935
Trimmed Mean ( 31 / 37 )88.63093450318617.49882393627675.06496521285901
Trimmed Mean ( 32 / 37 )87.48803616131516.83084372701535.19807786111681
Trimmed Mean ( 33 / 37 )86.838778210810416.16465288925755.3721399899976
Trimmed Mean ( 34 / 37 )86.395748775870115.60111502963405.53779320335521
Trimmed Mean ( 35 / 37 )86.229130288123614.99349904188035.75110119707653
Trimmed Mean ( 36 / 37 )86.263437214473614.26075187953856.04901045492876
Trimmed Mean ( 37 / 37 )85.589430257707413.6706817202626.26080191237655
Median72.1940493853472
Midrange300.6813149883
Midmean - Weighted Average at Xnp86.3339009043196
Midmean - Weighted Average at X(n+1)p92.246945069308
Midmean - Empirical Distribution Function92.246945069308
Midmean - Empirical Distribution Function - Averaging92.246945069308
Midmean - Empirical Distribution Function - Interpolation91.0271650101472
Midmean - Closest Observation86.3339009043196
Midmean - True Basic - Statistics Graphics Toolkit92.246945069308
Midmean - MS Excel (old versions)92.246945069308
Number of observations111



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')