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Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 13 Oct 2014 19:24:55 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Oct/13/t1413224712j2c0raf1pjkovyx.htm/, Retrieved Fri, 10 May 2024 07:53:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=240818, Retrieved Fri, 10 May 2024 07:53:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact60
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2014-10-13 18:24:55] [11722998b98bb8551244d4a68b29baca] [Current]
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Dataseries X:
15.579
16.348
15.928
16.171
15.937
15.713
15.594
15.683
16.438
17.032
17.696
17.745
19.394
20.148
20.108
18.584
18.441
18.391
19.178
18.079
18.483
19.644
19.195
19.650
20.830
23.595
22.937
21.814
21.928
21.777
21.383
21.467
22.052
22.680
24.320
24.977
25.204
25.739
26.434
27.525
30.695
32.436
30.160
30.236
31.293
31.077
32.226
33.865
32.810
32.242
32.700
32.819
33.947
34.148
35.261
39.506
41.591
39.148
41.216
40.225
41.126
42.362
40.740
40.256
39.804
41.002
41.702
42.254
43.605
43.271
43.221
41.373
40.435
39.217
39.457
36.710
34.977
32.729
31.584
32.510
32.565
30.988
30.383
28.673




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ yule.wessa.net

\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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=240818&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=240818&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=240818&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'George Udny Yule' @ yule.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean28.55197619047620.99934497393517128.5706907375995
Geometric Mean27.0515477453354
Harmonic Mean25.5753362643866
Quadratic Mean29.9684274807115
Winsorized Mean ( 1 / 28 )28.54817857142860.99860310267523628.58811323032
Winsorized Mean ( 2 / 28 )28.54910714285710.99806178963038728.6045487759127
Winsorized Mean ( 3 / 28 )28.51950.99260082901734528.732093673782
Winsorized Mean ( 4 / 28 )28.52459523809520.99015882870287428.8081006917476
Winsorized Mean ( 5 / 28 )28.49227380952380.98467649212013728.9356697733041
Winsorized Mean ( 6 / 28 )28.50105952380950.98084870771258829.0575491405561
Winsorized Mean ( 7 / 28 )28.49764285714290.97572061129948829.206765263664
Winsorized Mean ( 8 / 28 )28.49126190476190.97206966626059529.3098971129955
Winsorized Mean ( 9 / 28 )28.54526190476190.96120190319962829.6974671083579
Winsorized Mean ( 10 / 28 )28.60954761904760.94768594156178130.1888488204217
Winsorized Mean ( 11 / 28 )28.58165476190480.94142373251703930.3600321244158
Winsorized Mean ( 12 / 28 )28.58579761904760.92811959613680730.7996919125862
Winsorized Mean ( 13 / 28 )28.6063809523810.91733728234945631.1841473172388
Winsorized Mean ( 14 / 28 )28.60954761904760.91543043595705531.2525632700176
Winsorized Mean ( 15 / 28 )28.5418690476190.9030301042201631.6067746958085
Winsorized Mean ( 16 / 28 )28.50434523809520.89196792533807731.9566930921775
Winsorized Mean ( 17 / 28 )28.61464285714290.87462044397016832.7166407490457
Winsorized Mean ( 18 / 28 )28.56685714285710.86649766713774332.9681870203073
Winsorized Mean ( 19 / 28 )28.59626190476190.85834636429664933.3155275005963
Winsorized Mean ( 20 / 28 )28.07530952380950.76806807882936736.5531523801898
Winsorized Mean ( 21 / 28 )27.71455952380950.7204225092933338.4698689536992
Winsorized Mean ( 22 / 28 )27.76013095238090.69502838341472339.9410032954244
Winsorized Mean ( 23 / 28 )27.54409523809520.66579406919538241.3702922757821
Winsorized Mean ( 24 / 28 )27.68152380952380.63318913722411643.7176227167744
Winsorized Mean ( 25 / 28 )27.82170238095240.60906131320374445.6796414052413
Winsorized Mean ( 26 / 28 )27.52394047619050.56816664458223248.4434289457957
Winsorized Mean ( 27 / 28 )27.62069047619050.55512252243084149.7560256702277
Winsorized Mean ( 28 / 28 )27.60602380952380.55052467176459250.1449348692011
Trimmed Mean ( 1 / 28 )28.52660975609760.99440810122021228.6870246944824
Trimmed Mean ( 2 / 28 )28.50396250.98912076070333928.8174747032218
Trimmed Mean ( 3 / 28 )28.47965384615380.98288890945720528.9754554885369
Trimmed Mean ( 4 / 28 )28.46497368421050.97750996853600329.1198807177813
Trimmed Mean ( 5 / 28 )28.44805405405410.97156562179669529.2806305779384
Trimmed Mean ( 6 / 28 )28.43773611111110.9656625580675829.4489372851101
Trimmed Mean ( 7 / 28 )28.42507142857140.9591521612633129.6356225597537
Trimmed Mean ( 8 / 28 )28.41226470588240.95209593814109929.8418085485748
Trimmed Mean ( 9 / 28 )28.3996969696970.94395688237867530.0857989383293
Trimmed Mean ( 10 / 28 )28.378468750.93586657331056330.3231994381562
Trimmed Mean ( 11 / 28 )28.34716129032260.92812603004867430.542362106616
Trimmed Mean ( 12 / 28 )28.31731666666670.91932191987800130.802394737226
Trimmed Mean ( 13 / 28 )28.28491379310340.91040211204541231.0685942166318
Trimmed Mean ( 14 / 28 )28.24782142857140.90072934520660931.3610537714767
Trimmed Mean ( 15 / 28 )28.20762962962960.88845600267578431.7490450226866
Trimmed Mean ( 16 / 28 )28.17163461538460.87490998116084932.1994664845473
Trimmed Mean ( 17 / 28 )28.13670.8594179678534732.7392503443648
Trimmed Mean ( 18 / 28 )28.08750.84242674882013333.3411777811402
Trimmed Mean ( 19 / 28 )28.03886956521740.82180235091520334.1187507361007
Trimmed Mean ( 20 / 28 )27.98286363636360.79630116875752335.1410555883342
Trimmed Mean ( 21 / 28 )27.9736190476190.78235685718041335.7555746982713
Trimmed Mean ( 22 / 28 )27.9995250.7727698424959136.2326833427745
Trimmed Mean ( 23 / 28 )28.02357894736840.76396757994224836.6816337278172
Trimmed Mean ( 24 / 28 )28.07222222222220.75644766508836337.1105940540421
Trimmed Mean ( 25 / 28 )28.11244117647060.7516889327891437.3990356252279
Trimmed Mean ( 26 / 28 )28.142968750.74836080342679337.6061501633056
Trimmed Mean ( 27 / 28 )28.20963333333330.74970982046670237.6274027139895
Trimmed Mean ( 28 / 28 )28.27507142857140.7509556027298537.6521212782577
Median30.198
Midrange29.592
Midmean - Weighted Average at Xnp27.7799069767442
Midmean - Weighted Average at X(n+1)p27.9736190476191
Midmean - Empirical Distribution Function27.7799069767442
Midmean - Empirical Distribution Function - Averaging27.9736190476191
Midmean - Empirical Distribution Function - Interpolation27.9736190476191
Midmean - Closest Observation27.7799069767442
Midmean - True Basic - Statistics Graphics Toolkit27.9736190476191
Midmean - MS Excel (old versions)27.9828636363636
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 28.5519761904762 & 0.999344973935171 & 28.5706907375995 \tabularnewline
Geometric Mean & 27.0515477453354 &  &  \tabularnewline
Harmonic Mean & 25.5753362643866 &  &  \tabularnewline
Quadratic Mean & 29.9684274807115 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 28.5481785714286 & 0.998603102675236 & 28.58811323032 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 28.5491071428571 & 0.998061789630387 & 28.6045487759127 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 28.5195 & 0.992600829017345 & 28.732093673782 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 28.5245952380952 & 0.990158828702874 & 28.8081006917476 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 28.4922738095238 & 0.984676492120137 & 28.9356697733041 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 28.5010595238095 & 0.980848707712588 & 29.0575491405561 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 28.4976428571429 & 0.975720611299488 & 29.206765263664 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 28.4912619047619 & 0.972069666260595 & 29.3098971129955 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 28.5452619047619 & 0.961201903199628 & 29.6974671083579 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 28.6095476190476 & 0.947685941561781 & 30.1888488204217 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 28.5816547619048 & 0.941423732517039 & 30.3600321244158 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 28.5857976190476 & 0.928119596136807 & 30.7996919125862 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 28.606380952381 & 0.917337282349456 & 31.1841473172388 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 28.6095476190476 & 0.915430435957055 & 31.2525632700176 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 28.541869047619 & 0.90303010422016 & 31.6067746958085 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 28.5043452380952 & 0.891967925338077 & 31.9566930921775 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 28.6146428571429 & 0.874620443970168 & 32.7166407490457 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 28.5668571428571 & 0.866497667137743 & 32.9681870203073 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 28.5962619047619 & 0.858346364296649 & 33.3155275005963 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 28.0753095238095 & 0.768068078829367 & 36.5531523801898 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 27.7145595238095 & 0.72042250929333 & 38.4698689536992 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 27.7601309523809 & 0.695028383414723 & 39.9410032954244 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 27.5440952380952 & 0.665794069195382 & 41.3702922757821 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 27.6815238095238 & 0.633189137224116 & 43.7176227167744 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 27.8217023809524 & 0.609061313203744 & 45.6796414052413 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 27.5239404761905 & 0.568166644582232 & 48.4434289457957 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 27.6206904761905 & 0.555122522430841 & 49.7560256702277 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 27.6060238095238 & 0.550524671764592 & 50.1449348692011 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 28.5266097560976 & 0.994408101220212 & 28.6870246944824 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 28.5039625 & 0.989120760703339 & 28.8174747032218 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 28.4796538461538 & 0.982888909457205 & 28.9754554885369 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 28.4649736842105 & 0.977509968536003 & 29.1198807177813 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 28.4480540540541 & 0.971565621796695 & 29.2806305779384 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 28.4377361111111 & 0.96566255806758 & 29.4489372851101 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 28.4250714285714 & 0.95915216126331 & 29.6356225597537 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 28.4122647058824 & 0.952095938141099 & 29.8418085485748 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 28.399696969697 & 0.943956882378675 & 30.0857989383293 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 28.37846875 & 0.935866573310563 & 30.3231994381562 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 28.3471612903226 & 0.928126030048674 & 30.542362106616 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 28.3173166666667 & 0.919321919878001 & 30.802394737226 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 28.2849137931034 & 0.910402112045412 & 31.0685942166318 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 28.2478214285714 & 0.900729345206609 & 31.3610537714767 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 28.2076296296296 & 0.888456002675784 & 31.7490450226866 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 28.1716346153846 & 0.874909981160849 & 32.1994664845473 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 28.1367 & 0.85941796785347 & 32.7392503443648 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 28.0875 & 0.842426748820133 & 33.3411777811402 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 28.0388695652174 & 0.821802350915203 & 34.1187507361007 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 27.9828636363636 & 0.796301168757523 & 35.1410555883342 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 27.973619047619 & 0.782356857180413 & 35.7555746982713 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 27.999525 & 0.77276984249591 & 36.2326833427745 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 28.0235789473684 & 0.763967579942248 & 36.6816337278172 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 28.0722222222222 & 0.756447665088363 & 37.1105940540421 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 28.1124411764706 & 0.75168893278914 & 37.3990356252279 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 28.14296875 & 0.748360803426793 & 37.6061501633056 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 28.2096333333333 & 0.749709820466702 & 37.6274027139895 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 28.2750714285714 & 0.75095560272985 & 37.6521212782577 \tabularnewline
Median & 30.198 &  &  \tabularnewline
Midrange & 29.592 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 27.7799069767442 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 27.9736190476191 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 27.7799069767442 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 27.9736190476191 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 27.9736190476191 &  &  \tabularnewline
Midmean - Closest Observation & 27.7799069767442 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 27.9736190476191 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 27.9828636363636 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=240818&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]28.5519761904762[/C][C]0.999344973935171[/C][C]28.5706907375995[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]27.0515477453354[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]25.5753362643866[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]29.9684274807115[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]28.5481785714286[/C][C]0.998603102675236[/C][C]28.58811323032[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]28.5491071428571[/C][C]0.998061789630387[/C][C]28.6045487759127[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]28.5195[/C][C]0.992600829017345[/C][C]28.732093673782[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]28.5245952380952[/C][C]0.990158828702874[/C][C]28.8081006917476[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]28.4922738095238[/C][C]0.984676492120137[/C][C]28.9356697733041[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]28.5010595238095[/C][C]0.980848707712588[/C][C]29.0575491405561[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]28.4976428571429[/C][C]0.975720611299488[/C][C]29.206765263664[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]28.4912619047619[/C][C]0.972069666260595[/C][C]29.3098971129955[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]28.5452619047619[/C][C]0.961201903199628[/C][C]29.6974671083579[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]28.6095476190476[/C][C]0.947685941561781[/C][C]30.1888488204217[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]28.5816547619048[/C][C]0.941423732517039[/C][C]30.3600321244158[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]28.5857976190476[/C][C]0.928119596136807[/C][C]30.7996919125862[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]28.606380952381[/C][C]0.917337282349456[/C][C]31.1841473172388[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]28.6095476190476[/C][C]0.915430435957055[/C][C]31.2525632700176[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]28.541869047619[/C][C]0.90303010422016[/C][C]31.6067746958085[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]28.5043452380952[/C][C]0.891967925338077[/C][C]31.9566930921775[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]28.6146428571429[/C][C]0.874620443970168[/C][C]32.7166407490457[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]28.5668571428571[/C][C]0.866497667137743[/C][C]32.9681870203073[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]28.5962619047619[/C][C]0.858346364296649[/C][C]33.3155275005963[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]28.0753095238095[/C][C]0.768068078829367[/C][C]36.5531523801898[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]27.7145595238095[/C][C]0.72042250929333[/C][C]38.4698689536992[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]27.7601309523809[/C][C]0.695028383414723[/C][C]39.9410032954244[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]27.5440952380952[/C][C]0.665794069195382[/C][C]41.3702922757821[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]27.6815238095238[/C][C]0.633189137224116[/C][C]43.7176227167744[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]27.8217023809524[/C][C]0.609061313203744[/C][C]45.6796414052413[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]27.5239404761905[/C][C]0.568166644582232[/C][C]48.4434289457957[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]27.6206904761905[/C][C]0.555122522430841[/C][C]49.7560256702277[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]27.6060238095238[/C][C]0.550524671764592[/C][C]50.1449348692011[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]28.5266097560976[/C][C]0.994408101220212[/C][C]28.6870246944824[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]28.5039625[/C][C]0.989120760703339[/C][C]28.8174747032218[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]28.4796538461538[/C][C]0.982888909457205[/C][C]28.9754554885369[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]28.4649736842105[/C][C]0.977509968536003[/C][C]29.1198807177813[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]28.4480540540541[/C][C]0.971565621796695[/C][C]29.2806305779384[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]28.4377361111111[/C][C]0.96566255806758[/C][C]29.4489372851101[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]28.4250714285714[/C][C]0.95915216126331[/C][C]29.6356225597537[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]28.4122647058824[/C][C]0.952095938141099[/C][C]29.8418085485748[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]28.399696969697[/C][C]0.943956882378675[/C][C]30.0857989383293[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]28.37846875[/C][C]0.935866573310563[/C][C]30.3231994381562[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]28.3471612903226[/C][C]0.928126030048674[/C][C]30.542362106616[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]28.3173166666667[/C][C]0.919321919878001[/C][C]30.802394737226[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]28.2849137931034[/C][C]0.910402112045412[/C][C]31.0685942166318[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]28.2478214285714[/C][C]0.900729345206609[/C][C]31.3610537714767[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]28.2076296296296[/C][C]0.888456002675784[/C][C]31.7490450226866[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]28.1716346153846[/C][C]0.874909981160849[/C][C]32.1994664845473[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]28.1367[/C][C]0.85941796785347[/C][C]32.7392503443648[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]28.0875[/C][C]0.842426748820133[/C][C]33.3411777811402[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]28.0388695652174[/C][C]0.821802350915203[/C][C]34.1187507361007[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]27.9828636363636[/C][C]0.796301168757523[/C][C]35.1410555883342[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]27.973619047619[/C][C]0.782356857180413[/C][C]35.7555746982713[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]27.999525[/C][C]0.77276984249591[/C][C]36.2326833427745[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]28.0235789473684[/C][C]0.763967579942248[/C][C]36.6816337278172[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]28.0722222222222[/C][C]0.756447665088363[/C][C]37.1105940540421[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]28.1124411764706[/C][C]0.75168893278914[/C][C]37.3990356252279[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]28.14296875[/C][C]0.748360803426793[/C][C]37.6061501633056[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]28.2096333333333[/C][C]0.749709820466702[/C][C]37.6274027139895[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]28.2750714285714[/C][C]0.75095560272985[/C][C]37.6521212782577[/C][/ROW]
[ROW][C]Median[/C][C]30.198[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]29.592[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]27.7799069767442[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]27.9736190476191[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]27.7799069767442[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]27.9736190476191[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]27.9736190476191[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]27.7799069767442[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]27.9736190476191[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]27.9828636363636[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]84[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=240818&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=240818&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 Mean28.55197619047620.99934497393517128.5706907375995
Geometric Mean27.0515477453354
Harmonic Mean25.5753362643866
Quadratic Mean29.9684274807115
Winsorized Mean ( 1 / 28 )28.54817857142860.99860310267523628.58811323032
Winsorized Mean ( 2 / 28 )28.54910714285710.99806178963038728.6045487759127
Winsorized Mean ( 3 / 28 )28.51950.99260082901734528.732093673782
Winsorized Mean ( 4 / 28 )28.52459523809520.99015882870287428.8081006917476
Winsorized Mean ( 5 / 28 )28.49227380952380.98467649212013728.9356697733041
Winsorized Mean ( 6 / 28 )28.50105952380950.98084870771258829.0575491405561
Winsorized Mean ( 7 / 28 )28.49764285714290.97572061129948829.206765263664
Winsorized Mean ( 8 / 28 )28.49126190476190.97206966626059529.3098971129955
Winsorized Mean ( 9 / 28 )28.54526190476190.96120190319962829.6974671083579
Winsorized Mean ( 10 / 28 )28.60954761904760.94768594156178130.1888488204217
Winsorized Mean ( 11 / 28 )28.58165476190480.94142373251703930.3600321244158
Winsorized Mean ( 12 / 28 )28.58579761904760.92811959613680730.7996919125862
Winsorized Mean ( 13 / 28 )28.6063809523810.91733728234945631.1841473172388
Winsorized Mean ( 14 / 28 )28.60954761904760.91543043595705531.2525632700176
Winsorized Mean ( 15 / 28 )28.5418690476190.9030301042201631.6067746958085
Winsorized Mean ( 16 / 28 )28.50434523809520.89196792533807731.9566930921775
Winsorized Mean ( 17 / 28 )28.61464285714290.87462044397016832.7166407490457
Winsorized Mean ( 18 / 28 )28.56685714285710.86649766713774332.9681870203073
Winsorized Mean ( 19 / 28 )28.59626190476190.85834636429664933.3155275005963
Winsorized Mean ( 20 / 28 )28.07530952380950.76806807882936736.5531523801898
Winsorized Mean ( 21 / 28 )27.71455952380950.7204225092933338.4698689536992
Winsorized Mean ( 22 / 28 )27.76013095238090.69502838341472339.9410032954244
Winsorized Mean ( 23 / 28 )27.54409523809520.66579406919538241.3702922757821
Winsorized Mean ( 24 / 28 )27.68152380952380.63318913722411643.7176227167744
Winsorized Mean ( 25 / 28 )27.82170238095240.60906131320374445.6796414052413
Winsorized Mean ( 26 / 28 )27.52394047619050.56816664458223248.4434289457957
Winsorized Mean ( 27 / 28 )27.62069047619050.55512252243084149.7560256702277
Winsorized Mean ( 28 / 28 )27.60602380952380.55052467176459250.1449348692011
Trimmed Mean ( 1 / 28 )28.52660975609760.99440810122021228.6870246944824
Trimmed Mean ( 2 / 28 )28.50396250.98912076070333928.8174747032218
Trimmed Mean ( 3 / 28 )28.47965384615380.98288890945720528.9754554885369
Trimmed Mean ( 4 / 28 )28.46497368421050.97750996853600329.1198807177813
Trimmed Mean ( 5 / 28 )28.44805405405410.97156562179669529.2806305779384
Trimmed Mean ( 6 / 28 )28.43773611111110.9656625580675829.4489372851101
Trimmed Mean ( 7 / 28 )28.42507142857140.9591521612633129.6356225597537
Trimmed Mean ( 8 / 28 )28.41226470588240.95209593814109929.8418085485748
Trimmed Mean ( 9 / 28 )28.3996969696970.94395688237867530.0857989383293
Trimmed Mean ( 10 / 28 )28.378468750.93586657331056330.3231994381562
Trimmed Mean ( 11 / 28 )28.34716129032260.92812603004867430.542362106616
Trimmed Mean ( 12 / 28 )28.31731666666670.91932191987800130.802394737226
Trimmed Mean ( 13 / 28 )28.28491379310340.91040211204541231.0685942166318
Trimmed Mean ( 14 / 28 )28.24782142857140.90072934520660931.3610537714767
Trimmed Mean ( 15 / 28 )28.20762962962960.88845600267578431.7490450226866
Trimmed Mean ( 16 / 28 )28.17163461538460.87490998116084932.1994664845473
Trimmed Mean ( 17 / 28 )28.13670.8594179678534732.7392503443648
Trimmed Mean ( 18 / 28 )28.08750.84242674882013333.3411777811402
Trimmed Mean ( 19 / 28 )28.03886956521740.82180235091520334.1187507361007
Trimmed Mean ( 20 / 28 )27.98286363636360.79630116875752335.1410555883342
Trimmed Mean ( 21 / 28 )27.9736190476190.78235685718041335.7555746982713
Trimmed Mean ( 22 / 28 )27.9995250.7727698424959136.2326833427745
Trimmed Mean ( 23 / 28 )28.02357894736840.76396757994224836.6816337278172
Trimmed Mean ( 24 / 28 )28.07222222222220.75644766508836337.1105940540421
Trimmed Mean ( 25 / 28 )28.11244117647060.7516889327891437.3990356252279
Trimmed Mean ( 26 / 28 )28.142968750.74836080342679337.6061501633056
Trimmed Mean ( 27 / 28 )28.20963333333330.74970982046670237.6274027139895
Trimmed Mean ( 28 / 28 )28.27507142857140.7509556027298537.6521212782577
Median30.198
Midrange29.592
Midmean - Weighted Average at Xnp27.7799069767442
Midmean - Weighted Average at X(n+1)p27.9736190476191
Midmean - Empirical Distribution Function27.7799069767442
Midmean - Empirical Distribution Function - Averaging27.9736190476191
Midmean - Empirical Distribution Function - Interpolation27.9736190476191
Midmean - Closest Observation27.7799069767442
Midmean - True Basic - Statistics Graphics Toolkit27.9736190476191
Midmean - MS Excel (old versions)27.9828636363636
Number of observations84



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')