Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 16 Oct 2012 14:01:49 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Oct/16/t135041069622nkp0k5pj2rosz.htm/, Retrieved Tue, 30 Apr 2024 11:52:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=179125, Retrieved Tue, 30 Apr 2024 11:52:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact34
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Centrummaten prij...] [2012-10-16 18:01:49] [4633288e60d40b4ed5f0b9573dd4d146] [Current]
Feedback Forum

Post a new message
Dataseries X:
132
133,7
127
128,7
127,3
136,7
133,8
137,2
147,4
137,6
123,6
117,4
113,7
106,8
103,3
96,3
96,2
94,7
94,6
95,7
106,7
100,2
94,2
97,6
94,3
98
93,6
86,3
90,7
81,8
87,6
73,8
63,3
59,1
52,9
54,6
52,4
67,5
90,4
126
144,3
167,8
166,2
156
137
129,3
118
114,7
112,8
115,7
103,9
96,9
88,8
93
86,3
82,3
82,4
76,6
72,7
67,5
77,3
73,7
73
78,2
90,7
91,5
86,3
86,8
86,1
77,1
75,7
78,7
71,5
69,6
73,6
78,1
78,3
71,5
68,7
61,2
64,7
64,6
56,3
54,5
49,5
54
59,2
52,4
52,8
47,8
45,2
47,1
42,6
42,1
39,4
39,6




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=179125&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]2 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=179125&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=179125&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 time2 seconds
R Server'George Udny Yule' @ yule.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean89.85729166666673.1082098929413128.9096601457743
Geometric Mean84.7620068035893
Harmonic Mean79.7266459353564
Quadratic Mean94.8268152783448
Winsorized Mean ( 1 / 32 )89.84270833333333.1034964523592228.948867740782
Winsorized Mean ( 2 / 32 )89.68229166666673.0428468011460729.4731537693216
Winsorized Mean ( 3 / 32 )89.42916666666672.9819092393948429.9905729809589
Winsorized Mean ( 4 / 32 )89.40833333333332.9384544610871630.42699300511
Winsorized Mean ( 5 / 32 )89.15833333333332.8574612500122631.2019396003885
Winsorized Mean ( 6 / 32 )89.17708333333332.8462739105031931.3311670406197
Winsorized Mean ( 7 / 32 )89.28645833333332.8250087795980931.6057277337156
Winsorized Mean ( 8 / 32 )89.5031252.7856959401356432.1295385151195
Winsorized Mean ( 9 / 32 )89.231252.7381532355672432.588114076645
Winsorized Mean ( 10 / 32 )89.26252.730490304438332.6910151832099
Winsorized Mean ( 11 / 32 )89.07916666666672.6958658719802133.0428778347325
Winsorized Mean ( 12 / 32 )88.87916666666672.6208324965831433.9125704456661
Winsorized Mean ( 13 / 32 )88.8656252.5982246925363734.2024403259943
Winsorized Mean ( 14 / 32 )88.67604166666672.5635226862931434.5914791941601
Winsorized Mean ( 15 / 32 )88.89479166666672.5193994558156535.2841195791587
Winsorized Mean ( 16 / 32 )89.19479166666672.4306383943172436.6960350314557
Winsorized Mean ( 17 / 32 )88.78752.3614578133826537.5985967214113
Winsorized Mean ( 18 / 32 )88.11252.1536832230944740.9124698818972
Winsorized Mean ( 19 / 32 )88.4093752.0825844679300842.4517595139235
Winsorized Mean ( 20 / 32 )88.32604166666671.9969484641329144.2305063215633
Winsorized Mean ( 21 / 32 )88.12916666666671.9628372526547844.898865938819
Winsorized Mean ( 22 / 32 )88.54166666666671.851370205395747.8249387446216
Winsorized Mean ( 23 / 32 )88.32604166666671.820692010328248.51234649552
Winsorized Mean ( 24 / 32 )87.12604166666671.5792064718343455.1707729296882
Winsorized Mean ( 25 / 32 )87.3343751.5472491351553756.4449337961531
Winsorized Mean ( 26 / 32 )87.0906251.3873370602327262.7753899873407
Winsorized Mean ( 27 / 32 )86.9218751.3659255610874363.635879930968
Winsorized Mean ( 28 / 32 )86.36770833333331.212869128828871.2094209345848
Winsorized Mean ( 29 / 32 )85.793751.1241232572933176.3205897959769
Winsorized Mean ( 30 / 32 )85.856251.0875197240598978.9468439979043
Winsorized Mean ( 31 / 32 )85.66251.0581992420923980.9512014302887
Winsorized Mean ( 32 / 32 )85.49583333333331.0320275953686282.8425845558866
Trimmed Mean ( 1 / 32 )89.56489361702133.0152323228495729.7041435043974
Trimmed Mean ( 2 / 32 )89.2752.91424316873830.6340256563629
Trimmed Mean ( 3 / 32 )89.05777777777782.8359181766341131.4035075170887
Trimmed Mean ( 4 / 32 )88.92272727272732.7726490730189232.0713963184336
Trimmed Mean ( 5 / 32 )88.78720930232562.7148130899888732.7047227043869
Trimmed Mean ( 6 / 32 )88.70238095238092.6714078492952333.2043573862308
Trimmed Mean ( 7 / 32 )88.6097560975612.6239060379486633.7701711936435
Trimmed Mean ( 8 / 32 )88.493752.5735118249452334.3863778445562
Trimmed Mean ( 9 / 32 )88.33846153846152.5229101635883235.0145093604199
Trimmed Mean ( 10 / 32 )88.21315789473682.473335940395835.6656596679788
Trimmed Mean ( 11 / 32 )88.0770270270272.4164916443216336.4483060531138
Trimmed Mean ( 12 / 32 )87.95555555555552.3560637388461837.3315687964493
Trimmed Mean ( 13 / 32 )87.852.2983374583519638.2232816511607
Trimmed Mean ( 14 / 32 )87.73970588235292.2337110501979639.2797921980898
Trimmed Mean ( 15 / 32 )87.64242424242422.16284158745640.5218878491753
Trimmed Mean ( 16 / 32 )87.51718752.085460288882441.9654058945906
Trimmed Mean ( 17 / 32 )87.35483870967742.0077621417038443.5085595525502
Trimmed Mean ( 18 / 32 )87.221.9264847528140145.2741709336645
Trimmed Mean ( 19 / 32 )87.13793103448281.8661596638614946.6937168999652
Trimmed Mean ( 20 / 32 )87.02321428571431.8044443528526348.2271532220653
Trimmed Mean ( 21 / 32 )86.90740740740741.7437777008048549.838581699545
Trimmed Mean ( 22 / 32 )86.81.6745432280548751.8350309181482
Trimmed Mean ( 23 / 32 )86.6481.608549200556953.8671742026923
Trimmed Mean ( 24 / 32 )86.50208333333331.530946983575556.5023376128345
Trimmed Mean ( 25 / 32 )86.44782608695651.4839812593398358.2539877393155
Trimmed Mean ( 26 / 32 )86.37045454545451.4291386972277760.4353200378626
Trimmed Mean ( 27 / 32 )86.30714285714281.391801917205962.0110820298395
Trimmed Mean ( 28 / 32 )86.25251.3463101878077264.0658451381475
Trimmed Mean ( 29 / 32 )86.24210526315791.3198809786147665.3408198621594
Trimmed Mean ( 30 / 32 )86.28333333333331.301924704623166.2736739128951
Trimmed Mean ( 31 / 32 )86.32352941176471.2829337676251467.2860373544925
Trimmed Mean ( 32 / 32 )86.38751.260190317807968.5511535672414
Median86.55
Midrange103.6
Midmean - Weighted Average at Xnp85.742
Midmean - Weighted Average at X(n+1)p86.5020833333333
Midmean - Empirical Distribution Function85.742
Midmean - Empirical Distribution Function - Averaging86.5020833333333
Midmean - Empirical Distribution Function - Interpolation86.5020833333333
Midmean - Closest Observation85.742
Midmean - True Basic - Statistics Graphics Toolkit86.5020833333333
Midmean - MS Excel (old versions)86.2725490196078
Number of observations96

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 89.8572916666667 & 3.10820989294131 & 28.9096601457743 \tabularnewline
Geometric Mean & 84.7620068035893 &  &  \tabularnewline
Harmonic Mean & 79.7266459353564 &  &  \tabularnewline
Quadratic Mean & 94.8268152783448 &  &  \tabularnewline
Winsorized Mean ( 1 / 32 ) & 89.8427083333333 & 3.10349645235922 & 28.948867740782 \tabularnewline
Winsorized Mean ( 2 / 32 ) & 89.6822916666667 & 3.04284680114607 & 29.4731537693216 \tabularnewline
Winsorized Mean ( 3 / 32 ) & 89.4291666666667 & 2.98190923939484 & 29.9905729809589 \tabularnewline
Winsorized Mean ( 4 / 32 ) & 89.4083333333333 & 2.93845446108716 & 30.42699300511 \tabularnewline
Winsorized Mean ( 5 / 32 ) & 89.1583333333333 & 2.85746125001226 & 31.2019396003885 \tabularnewline
Winsorized Mean ( 6 / 32 ) & 89.1770833333333 & 2.84627391050319 & 31.3311670406197 \tabularnewline
Winsorized Mean ( 7 / 32 ) & 89.2864583333333 & 2.82500877959809 & 31.6057277337156 \tabularnewline
Winsorized Mean ( 8 / 32 ) & 89.503125 & 2.78569594013564 & 32.1295385151195 \tabularnewline
Winsorized Mean ( 9 / 32 ) & 89.23125 & 2.73815323556724 & 32.588114076645 \tabularnewline
Winsorized Mean ( 10 / 32 ) & 89.2625 & 2.7304903044383 & 32.6910151832099 \tabularnewline
Winsorized Mean ( 11 / 32 ) & 89.0791666666667 & 2.69586587198021 & 33.0428778347325 \tabularnewline
Winsorized Mean ( 12 / 32 ) & 88.8791666666667 & 2.62083249658314 & 33.9125704456661 \tabularnewline
Winsorized Mean ( 13 / 32 ) & 88.865625 & 2.59822469253637 & 34.2024403259943 \tabularnewline
Winsorized Mean ( 14 / 32 ) & 88.6760416666667 & 2.56352268629314 & 34.5914791941601 \tabularnewline
Winsorized Mean ( 15 / 32 ) & 88.8947916666667 & 2.51939945581565 & 35.2841195791587 \tabularnewline
Winsorized Mean ( 16 / 32 ) & 89.1947916666667 & 2.43063839431724 & 36.6960350314557 \tabularnewline
Winsorized Mean ( 17 / 32 ) & 88.7875 & 2.36145781338265 & 37.5985967214113 \tabularnewline
Winsorized Mean ( 18 / 32 ) & 88.1125 & 2.15368322309447 & 40.9124698818972 \tabularnewline
Winsorized Mean ( 19 / 32 ) & 88.409375 & 2.08258446793008 & 42.4517595139235 \tabularnewline
Winsorized Mean ( 20 / 32 ) & 88.3260416666667 & 1.99694846413291 & 44.2305063215633 \tabularnewline
Winsorized Mean ( 21 / 32 ) & 88.1291666666667 & 1.96283725265478 & 44.898865938819 \tabularnewline
Winsorized Mean ( 22 / 32 ) & 88.5416666666667 & 1.8513702053957 & 47.8249387446216 \tabularnewline
Winsorized Mean ( 23 / 32 ) & 88.3260416666667 & 1.8206920103282 & 48.51234649552 \tabularnewline
Winsorized Mean ( 24 / 32 ) & 87.1260416666667 & 1.57920647183434 & 55.1707729296882 \tabularnewline
Winsorized Mean ( 25 / 32 ) & 87.334375 & 1.54724913515537 & 56.4449337961531 \tabularnewline
Winsorized Mean ( 26 / 32 ) & 87.090625 & 1.38733706023272 & 62.7753899873407 \tabularnewline
Winsorized Mean ( 27 / 32 ) & 86.921875 & 1.36592556108743 & 63.635879930968 \tabularnewline
Winsorized Mean ( 28 / 32 ) & 86.3677083333333 & 1.2128691288288 & 71.2094209345848 \tabularnewline
Winsorized Mean ( 29 / 32 ) & 85.79375 & 1.12412325729331 & 76.3205897959769 \tabularnewline
Winsorized Mean ( 30 / 32 ) & 85.85625 & 1.08751972405989 & 78.9468439979043 \tabularnewline
Winsorized Mean ( 31 / 32 ) & 85.6625 & 1.05819924209239 & 80.9512014302887 \tabularnewline
Winsorized Mean ( 32 / 32 ) & 85.4958333333333 & 1.03202759536862 & 82.8425845558866 \tabularnewline
Trimmed Mean ( 1 / 32 ) & 89.5648936170213 & 3.01523232284957 & 29.7041435043974 \tabularnewline
Trimmed Mean ( 2 / 32 ) & 89.275 & 2.914243168738 & 30.6340256563629 \tabularnewline
Trimmed Mean ( 3 / 32 ) & 89.0577777777778 & 2.83591817663411 & 31.4035075170887 \tabularnewline
Trimmed Mean ( 4 / 32 ) & 88.9227272727273 & 2.77264907301892 & 32.0713963184336 \tabularnewline
Trimmed Mean ( 5 / 32 ) & 88.7872093023256 & 2.71481308998887 & 32.7047227043869 \tabularnewline
Trimmed Mean ( 6 / 32 ) & 88.7023809523809 & 2.67140784929523 & 33.2043573862308 \tabularnewline
Trimmed Mean ( 7 / 32 ) & 88.609756097561 & 2.62390603794866 & 33.7701711936435 \tabularnewline
Trimmed Mean ( 8 / 32 ) & 88.49375 & 2.57351182494523 & 34.3863778445562 \tabularnewline
Trimmed Mean ( 9 / 32 ) & 88.3384615384615 & 2.52291016358832 & 35.0145093604199 \tabularnewline
Trimmed Mean ( 10 / 32 ) & 88.2131578947368 & 2.4733359403958 & 35.6656596679788 \tabularnewline
Trimmed Mean ( 11 / 32 ) & 88.077027027027 & 2.41649164432163 & 36.4483060531138 \tabularnewline
Trimmed Mean ( 12 / 32 ) & 87.9555555555555 & 2.35606373884618 & 37.3315687964493 \tabularnewline
Trimmed Mean ( 13 / 32 ) & 87.85 & 2.29833745835196 & 38.2232816511607 \tabularnewline
Trimmed Mean ( 14 / 32 ) & 87.7397058823529 & 2.23371105019796 & 39.2797921980898 \tabularnewline
Trimmed Mean ( 15 / 32 ) & 87.6424242424242 & 2.162841587456 & 40.5218878491753 \tabularnewline
Trimmed Mean ( 16 / 32 ) & 87.5171875 & 2.0854602888824 & 41.9654058945906 \tabularnewline
Trimmed Mean ( 17 / 32 ) & 87.3548387096774 & 2.00776214170384 & 43.5085595525502 \tabularnewline
Trimmed Mean ( 18 / 32 ) & 87.22 & 1.92648475281401 & 45.2741709336645 \tabularnewline
Trimmed Mean ( 19 / 32 ) & 87.1379310344828 & 1.86615966386149 & 46.6937168999652 \tabularnewline
Trimmed Mean ( 20 / 32 ) & 87.0232142857143 & 1.80444435285263 & 48.2271532220653 \tabularnewline
Trimmed Mean ( 21 / 32 ) & 86.9074074074074 & 1.74377770080485 & 49.838581699545 \tabularnewline
Trimmed Mean ( 22 / 32 ) & 86.8 & 1.67454322805487 & 51.8350309181482 \tabularnewline
Trimmed Mean ( 23 / 32 ) & 86.648 & 1.6085492005569 & 53.8671742026923 \tabularnewline
Trimmed Mean ( 24 / 32 ) & 86.5020833333333 & 1.5309469835755 & 56.5023376128345 \tabularnewline
Trimmed Mean ( 25 / 32 ) & 86.4478260869565 & 1.48398125933983 & 58.2539877393155 \tabularnewline
Trimmed Mean ( 26 / 32 ) & 86.3704545454545 & 1.42913869722777 & 60.4353200378626 \tabularnewline
Trimmed Mean ( 27 / 32 ) & 86.3071428571428 & 1.3918019172059 & 62.0110820298395 \tabularnewline
Trimmed Mean ( 28 / 32 ) & 86.2525 & 1.34631018780772 & 64.0658451381475 \tabularnewline
Trimmed Mean ( 29 / 32 ) & 86.2421052631579 & 1.31988097861476 & 65.3408198621594 \tabularnewline
Trimmed Mean ( 30 / 32 ) & 86.2833333333333 & 1.3019247046231 & 66.2736739128951 \tabularnewline
Trimmed Mean ( 31 / 32 ) & 86.3235294117647 & 1.28293376762514 & 67.2860373544925 \tabularnewline
Trimmed Mean ( 32 / 32 ) & 86.3875 & 1.2601903178079 & 68.5511535672414 \tabularnewline
Median & 86.55 &  &  \tabularnewline
Midrange & 103.6 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 85.742 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 86.5020833333333 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 85.742 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 86.5020833333333 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 86.5020833333333 &  &  \tabularnewline
Midmean - Closest Observation & 85.742 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 86.5020833333333 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 86.2725490196078 &  &  \tabularnewline
Number of observations & 96 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=179125&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]89.8572916666667[/C][C]3.10820989294131[/C][C]28.9096601457743[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]84.7620068035893[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]79.7266459353564[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]94.8268152783448[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 32 )[/C][C]89.8427083333333[/C][C]3.10349645235922[/C][C]28.948867740782[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 32 )[/C][C]89.6822916666667[/C][C]3.04284680114607[/C][C]29.4731537693216[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 32 )[/C][C]89.4291666666667[/C][C]2.98190923939484[/C][C]29.9905729809589[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 32 )[/C][C]89.4083333333333[/C][C]2.93845446108716[/C][C]30.42699300511[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 32 )[/C][C]89.1583333333333[/C][C]2.85746125001226[/C][C]31.2019396003885[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 32 )[/C][C]89.1770833333333[/C][C]2.84627391050319[/C][C]31.3311670406197[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 32 )[/C][C]89.2864583333333[/C][C]2.82500877959809[/C][C]31.6057277337156[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 32 )[/C][C]89.503125[/C][C]2.78569594013564[/C][C]32.1295385151195[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 32 )[/C][C]89.23125[/C][C]2.73815323556724[/C][C]32.588114076645[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 32 )[/C][C]89.2625[/C][C]2.7304903044383[/C][C]32.6910151832099[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 32 )[/C][C]89.0791666666667[/C][C]2.69586587198021[/C][C]33.0428778347325[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 32 )[/C][C]88.8791666666667[/C][C]2.62083249658314[/C][C]33.9125704456661[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 32 )[/C][C]88.865625[/C][C]2.59822469253637[/C][C]34.2024403259943[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 32 )[/C][C]88.6760416666667[/C][C]2.56352268629314[/C][C]34.5914791941601[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 32 )[/C][C]88.8947916666667[/C][C]2.51939945581565[/C][C]35.2841195791587[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 32 )[/C][C]89.1947916666667[/C][C]2.43063839431724[/C][C]36.6960350314557[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 32 )[/C][C]88.7875[/C][C]2.36145781338265[/C][C]37.5985967214113[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 32 )[/C][C]88.1125[/C][C]2.15368322309447[/C][C]40.9124698818972[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 32 )[/C][C]88.409375[/C][C]2.08258446793008[/C][C]42.4517595139235[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 32 )[/C][C]88.3260416666667[/C][C]1.99694846413291[/C][C]44.2305063215633[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 32 )[/C][C]88.1291666666667[/C][C]1.96283725265478[/C][C]44.898865938819[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 32 )[/C][C]88.5416666666667[/C][C]1.8513702053957[/C][C]47.8249387446216[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 32 )[/C][C]88.3260416666667[/C][C]1.8206920103282[/C][C]48.51234649552[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 32 )[/C][C]87.1260416666667[/C][C]1.57920647183434[/C][C]55.1707729296882[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 32 )[/C][C]87.334375[/C][C]1.54724913515537[/C][C]56.4449337961531[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 32 )[/C][C]87.090625[/C][C]1.38733706023272[/C][C]62.7753899873407[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 32 )[/C][C]86.921875[/C][C]1.36592556108743[/C][C]63.635879930968[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 32 )[/C][C]86.3677083333333[/C][C]1.2128691288288[/C][C]71.2094209345848[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 32 )[/C][C]85.79375[/C][C]1.12412325729331[/C][C]76.3205897959769[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 32 )[/C][C]85.85625[/C][C]1.08751972405989[/C][C]78.9468439979043[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 32 )[/C][C]85.6625[/C][C]1.05819924209239[/C][C]80.9512014302887[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 32 )[/C][C]85.4958333333333[/C][C]1.03202759536862[/C][C]82.8425845558866[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 32 )[/C][C]89.5648936170213[/C][C]3.01523232284957[/C][C]29.7041435043974[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 32 )[/C][C]89.275[/C][C]2.914243168738[/C][C]30.6340256563629[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 32 )[/C][C]89.0577777777778[/C][C]2.83591817663411[/C][C]31.4035075170887[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 32 )[/C][C]88.9227272727273[/C][C]2.77264907301892[/C][C]32.0713963184336[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 32 )[/C][C]88.7872093023256[/C][C]2.71481308998887[/C][C]32.7047227043869[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 32 )[/C][C]88.7023809523809[/C][C]2.67140784929523[/C][C]33.2043573862308[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 32 )[/C][C]88.609756097561[/C][C]2.62390603794866[/C][C]33.7701711936435[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 32 )[/C][C]88.49375[/C][C]2.57351182494523[/C][C]34.3863778445562[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 32 )[/C][C]88.3384615384615[/C][C]2.52291016358832[/C][C]35.0145093604199[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 32 )[/C][C]88.2131578947368[/C][C]2.4733359403958[/C][C]35.6656596679788[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 32 )[/C][C]88.077027027027[/C][C]2.41649164432163[/C][C]36.4483060531138[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 32 )[/C][C]87.9555555555555[/C][C]2.35606373884618[/C][C]37.3315687964493[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 32 )[/C][C]87.85[/C][C]2.29833745835196[/C][C]38.2232816511607[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 32 )[/C][C]87.7397058823529[/C][C]2.23371105019796[/C][C]39.2797921980898[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 32 )[/C][C]87.6424242424242[/C][C]2.162841587456[/C][C]40.5218878491753[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 32 )[/C][C]87.5171875[/C][C]2.0854602888824[/C][C]41.9654058945906[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 32 )[/C][C]87.3548387096774[/C][C]2.00776214170384[/C][C]43.5085595525502[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 32 )[/C][C]87.22[/C][C]1.92648475281401[/C][C]45.2741709336645[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 32 )[/C][C]87.1379310344828[/C][C]1.86615966386149[/C][C]46.6937168999652[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 32 )[/C][C]87.0232142857143[/C][C]1.80444435285263[/C][C]48.2271532220653[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 32 )[/C][C]86.9074074074074[/C][C]1.74377770080485[/C][C]49.838581699545[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 32 )[/C][C]86.8[/C][C]1.67454322805487[/C][C]51.8350309181482[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 32 )[/C][C]86.648[/C][C]1.6085492005569[/C][C]53.8671742026923[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 32 )[/C][C]86.5020833333333[/C][C]1.5309469835755[/C][C]56.5023376128345[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 32 )[/C][C]86.4478260869565[/C][C]1.48398125933983[/C][C]58.2539877393155[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 32 )[/C][C]86.3704545454545[/C][C]1.42913869722777[/C][C]60.4353200378626[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 32 )[/C][C]86.3071428571428[/C][C]1.3918019172059[/C][C]62.0110820298395[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 32 )[/C][C]86.2525[/C][C]1.34631018780772[/C][C]64.0658451381475[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 32 )[/C][C]86.2421052631579[/C][C]1.31988097861476[/C][C]65.3408198621594[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 32 )[/C][C]86.2833333333333[/C][C]1.3019247046231[/C][C]66.2736739128951[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 32 )[/C][C]86.3235294117647[/C][C]1.28293376762514[/C][C]67.2860373544925[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 32 )[/C][C]86.3875[/C][C]1.2601903178079[/C][C]68.5511535672414[/C][/ROW]
[ROW][C]Median[/C][C]86.55[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]103.6[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]85.742[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]86.5020833333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]85.742[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]86.5020833333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]86.5020833333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]85.742[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]86.5020833333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]86.2725490196078[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]96[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=179125&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=179125&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 Mean89.85729166666673.1082098929413128.9096601457743
Geometric Mean84.7620068035893
Harmonic Mean79.7266459353564
Quadratic Mean94.8268152783448
Winsorized Mean ( 1 / 32 )89.84270833333333.1034964523592228.948867740782
Winsorized Mean ( 2 / 32 )89.68229166666673.0428468011460729.4731537693216
Winsorized Mean ( 3 / 32 )89.42916666666672.9819092393948429.9905729809589
Winsorized Mean ( 4 / 32 )89.40833333333332.9384544610871630.42699300511
Winsorized Mean ( 5 / 32 )89.15833333333332.8574612500122631.2019396003885
Winsorized Mean ( 6 / 32 )89.17708333333332.8462739105031931.3311670406197
Winsorized Mean ( 7 / 32 )89.28645833333332.8250087795980931.6057277337156
Winsorized Mean ( 8 / 32 )89.5031252.7856959401356432.1295385151195
Winsorized Mean ( 9 / 32 )89.231252.7381532355672432.588114076645
Winsorized Mean ( 10 / 32 )89.26252.730490304438332.6910151832099
Winsorized Mean ( 11 / 32 )89.07916666666672.6958658719802133.0428778347325
Winsorized Mean ( 12 / 32 )88.87916666666672.6208324965831433.9125704456661
Winsorized Mean ( 13 / 32 )88.8656252.5982246925363734.2024403259943
Winsorized Mean ( 14 / 32 )88.67604166666672.5635226862931434.5914791941601
Winsorized Mean ( 15 / 32 )88.89479166666672.5193994558156535.2841195791587
Winsorized Mean ( 16 / 32 )89.19479166666672.4306383943172436.6960350314557
Winsorized Mean ( 17 / 32 )88.78752.3614578133826537.5985967214113
Winsorized Mean ( 18 / 32 )88.11252.1536832230944740.9124698818972
Winsorized Mean ( 19 / 32 )88.4093752.0825844679300842.4517595139235
Winsorized Mean ( 20 / 32 )88.32604166666671.9969484641329144.2305063215633
Winsorized Mean ( 21 / 32 )88.12916666666671.9628372526547844.898865938819
Winsorized Mean ( 22 / 32 )88.54166666666671.851370205395747.8249387446216
Winsorized Mean ( 23 / 32 )88.32604166666671.820692010328248.51234649552
Winsorized Mean ( 24 / 32 )87.12604166666671.5792064718343455.1707729296882
Winsorized Mean ( 25 / 32 )87.3343751.5472491351553756.4449337961531
Winsorized Mean ( 26 / 32 )87.0906251.3873370602327262.7753899873407
Winsorized Mean ( 27 / 32 )86.9218751.3659255610874363.635879930968
Winsorized Mean ( 28 / 32 )86.36770833333331.212869128828871.2094209345848
Winsorized Mean ( 29 / 32 )85.793751.1241232572933176.3205897959769
Winsorized Mean ( 30 / 32 )85.856251.0875197240598978.9468439979043
Winsorized Mean ( 31 / 32 )85.66251.0581992420923980.9512014302887
Winsorized Mean ( 32 / 32 )85.49583333333331.0320275953686282.8425845558866
Trimmed Mean ( 1 / 32 )89.56489361702133.0152323228495729.7041435043974
Trimmed Mean ( 2 / 32 )89.2752.91424316873830.6340256563629
Trimmed Mean ( 3 / 32 )89.05777777777782.8359181766341131.4035075170887
Trimmed Mean ( 4 / 32 )88.92272727272732.7726490730189232.0713963184336
Trimmed Mean ( 5 / 32 )88.78720930232562.7148130899888732.7047227043869
Trimmed Mean ( 6 / 32 )88.70238095238092.6714078492952333.2043573862308
Trimmed Mean ( 7 / 32 )88.6097560975612.6239060379486633.7701711936435
Trimmed Mean ( 8 / 32 )88.493752.5735118249452334.3863778445562
Trimmed Mean ( 9 / 32 )88.33846153846152.5229101635883235.0145093604199
Trimmed Mean ( 10 / 32 )88.21315789473682.473335940395835.6656596679788
Trimmed Mean ( 11 / 32 )88.0770270270272.4164916443216336.4483060531138
Trimmed Mean ( 12 / 32 )87.95555555555552.3560637388461837.3315687964493
Trimmed Mean ( 13 / 32 )87.852.2983374583519638.2232816511607
Trimmed Mean ( 14 / 32 )87.73970588235292.2337110501979639.2797921980898
Trimmed Mean ( 15 / 32 )87.64242424242422.16284158745640.5218878491753
Trimmed Mean ( 16 / 32 )87.51718752.085460288882441.9654058945906
Trimmed Mean ( 17 / 32 )87.35483870967742.0077621417038443.5085595525502
Trimmed Mean ( 18 / 32 )87.221.9264847528140145.2741709336645
Trimmed Mean ( 19 / 32 )87.13793103448281.8661596638614946.6937168999652
Trimmed Mean ( 20 / 32 )87.02321428571431.8044443528526348.2271532220653
Trimmed Mean ( 21 / 32 )86.90740740740741.7437777008048549.838581699545
Trimmed Mean ( 22 / 32 )86.81.6745432280548751.8350309181482
Trimmed Mean ( 23 / 32 )86.6481.608549200556953.8671742026923
Trimmed Mean ( 24 / 32 )86.50208333333331.530946983575556.5023376128345
Trimmed Mean ( 25 / 32 )86.44782608695651.4839812593398358.2539877393155
Trimmed Mean ( 26 / 32 )86.37045454545451.4291386972277760.4353200378626
Trimmed Mean ( 27 / 32 )86.30714285714281.391801917205962.0110820298395
Trimmed Mean ( 28 / 32 )86.25251.3463101878077264.0658451381475
Trimmed Mean ( 29 / 32 )86.24210526315791.3198809786147665.3408198621594
Trimmed Mean ( 30 / 32 )86.28333333333331.301924704623166.2736739128951
Trimmed Mean ( 31 / 32 )86.32352941176471.2829337676251467.2860373544925
Trimmed Mean ( 32 / 32 )86.38751.260190317807968.5511535672414
Median86.55
Midrange103.6
Midmean - Weighted Average at Xnp85.742
Midmean - Weighted Average at X(n+1)p86.5020833333333
Midmean - Empirical Distribution Function85.742
Midmean - Empirical Distribution Function - Averaging86.5020833333333
Midmean - Empirical Distribution Function - Interpolation86.5020833333333
Midmean - Closest Observation85.742
Midmean - True Basic - Statistics Graphics Toolkit86.5020833333333
Midmean - MS Excel (old versions)86.2725490196078
Number of observations96



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')