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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationWed, 18 Apr 2012 08:00:11 -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/Apr/18/t1334750585i46z1otjnv1us7f.htm/, Retrieved Thu, 02 May 2024 05:43:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=164440, Retrieved Thu, 02 May 2024 05:43:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Centrummaten Aant...] [2012-04-18 12:00:11] [e9055fb3c64f4ec827f818bb591f77b7] [Current]
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Dataseries X:
9676
8642
9402
9610
9294
9448
10319
9548
9801
9596
8923
9746
9829
9125
9782
9441
9162
9915
10444
10209
9985
9842
9429
10132
9849
9172
10313
9819
9955
10048
10082
10541
10208
10233
9439
9963
10158
9225
10474
9757
10490
10281
10444
10640
10695
10786
9832
9747
10411
9511
10402
9701
10540
10112
10915
11183
10384
10834
9886
10216
10943
9867
10203
10837
10573
10647
11502
10656
10866
10835
9945
10331
9769
9321
9939
9336
10195
9464
10010
10213
9563
9890
9305
9391
9928
8686
9843
9627
10074
9503
10119
10000
9313
9866
9172
9241




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164440&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164440&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164440&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'Gertrude Mary Cox' @ cox.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean9963.7395833333356.3631556678676176.77753250806
Geometric Mean9948.61552853982
Harmonic Mean9933.50434777206
Quadratic Mean9978.87283161697
Winsorized Mean ( 1 / 32 )9960.87555.3870457374855179.841240264211
Winsorized Mean ( 2 / 32 )9960.812553.2119300378709187.191340229736
Winsorized Mean ( 3 / 32 )9966.2551.8542745535379192.197269864612
Winsorized Mean ( 4 / 32 )9965.7551.2096996020611194.606687354965
Winsorized Mean ( 5 / 32 )9964.7604166666750.8478072824853195.972273913551
Winsorized Mean ( 6 / 32 )9964.6354166666750.8252555843792196.056769456349
Winsorized Mean ( 7 / 32 )9968.4270833333350.1935000177639198.599959751869
Winsorized Mean ( 8 / 32 )9965.7604166666749.272707706549202.257210543801
Winsorized Mean ( 9 / 32 )9962.1979166666747.0688549850476211.651588291905
Winsorized Mean ( 10 / 32 )9959.2812546.2427867848887215.369400125654
Winsorized Mean ( 11 / 32 )9959.1666666666745.9436336260013216.769242671098
Winsorized Mean ( 12 / 32 )9959.2916666666745.6584260316763218.126040082004
Winsorized Mean ( 13 / 32 )9952.2543.9724096112272226.329420834353
Winsorized Mean ( 14 / 32 )9955.6041666666742.1262890353212236.327585330844
Winsorized Mean ( 15 / 32 )9957.1666666666741.8621999726449237.855790502488
Winsorized Mean ( 16 / 32 )9953.3333333333340.0388289244007248.592019315218
Winsorized Mean ( 17 / 32 )9952.2708333333339.3979736075176252.608698418802
Winsorized Mean ( 18 / 32 )9947.0208333333338.572769515072257.876760170063
Winsorized Mean ( 19 / 32 )9948.4062538.3820464075448259.194263494102
Winsorized Mean ( 20 / 32 )9944.8645833333337.0020554780871268.765193036986
Winsorized Mean ( 21 / 32 )9951.4270833333335.5907529903376279.607095866587
Winsorized Mean ( 22 / 32 )9949.1354166666734.8015225134269285.88218842518
Winsorized Mean ( 23 / 32 )9945.3020833333331.992372034211310.864792166656
Winsorized Mean ( 24 / 32 )9946.0520833333331.1247679121611319.554256963542
Winsorized Mean ( 25 / 32 )9953.0833333333329.8285843520011333.676020822142
Winsorized Mean ( 26 / 32 )9948.2083333333328.2630381210232351.986516479043
Winsorized Mean ( 27 / 32 )9939.4895833333326.0201760228737381.991635052575
Winsorized Mean ( 28 / 32 )9948.8229166666723.6586562678797420.515130023414
Winsorized Mean ( 29 / 32 )9955.4687522.6452909066479439.626445561686
Winsorized Mean ( 30 / 32 )9968.2812520.8729905174474477.56842708608
Winsorized Mean ( 31 / 32 )9968.2812520.7976187018553479.299163663902
Winsorized Mean ( 32 / 32 )9969.9479166666720.2240106658015492.975803930211
Trimmed Mean ( 1 / 32 )9961.4361702127753.3253881032313186.804757068597
Trimmed Mean ( 2 / 32 )9962.0217391304350.9580197321922195.494679571252
Trimmed Mean ( 3 / 32 )9962.6666666666749.5898483429487200.901333631186
Trimmed Mean ( 4 / 32 )9961.3636363636448.6078962870973204.933033462874
Trimmed Mean ( 5 / 32 )9960.1395348837247.6988448319364208.813013606044
Trimmed Mean ( 6 / 32 )9959.0833333333346.7556458752164213.0027967085
Trimmed Mean ( 7 / 32 )995845.6717336746739218.034201874888
Trimmed Mean ( 8 / 32 )9956.212544.5612851131287223.427409571424
Trimmed Mean ( 9 / 32 )9954.7435897435943.4704742306313229.00011481193
Trimmed Mean ( 10 / 32 )9953.6973684210542.6425083185445233.421948213407
Trimmed Mean ( 11 / 32 )9952.9729729729741.8268276900628237.956678109193
Trimmed Mean ( 12 / 32 )9952.2222222222240.9191883765457243.216510812484
Trimmed Mean ( 13 / 32 )9951.4142857142939.8960994936381249.433263201611
Trimmed Mean ( 14 / 32 )9951.3235294117638.9806487254319255.288812649218
Trimmed Mean ( 15 / 32 )9950.8787878787938.202951564364260.47408329468
Trimmed Mean ( 16 / 32 )9950.2537.3102009009579266.68979956483
Trimmed Mean ( 17 / 32 )9949.9516129032336.540339605961272.300469021367
Trimmed Mean ( 18 / 32 )9949.7333333333335.7091662943675278.632473559113
Trimmed Mean ( 19 / 32 )9949.9827586206934.8312802393062285.662275123393
Trimmed Mean ( 20 / 32 )9950.12533.7814698158928294.543874326003
Trimmed Mean ( 21 / 32 )9950.5925925925932.7310527767741304.010771069775
Trimmed Mean ( 22 / 32 )9950.5192307692331.6824302717142314.07057935366
Trimmed Mean ( 23 / 32 )9950.6430.5121690009553326.120375109631
Trimmed Mean ( 24 / 32 )9951.1041666666729.5813615302816336.397773864465
Trimmed Mean ( 25 / 32 )9951.5434782608728.5574885315347348.474042711139
Trimmed Mean ( 26 / 32 )9951.4090909090927.5024949508587361.836593686872
Trimmed Mean ( 27 / 32 )9951.6904761904826.4629008186735376.061964800475
Trimmed Mean ( 28 / 32 )9952.77525.5865170699185388.985142948637
Trimmed Mean ( 29 / 32 )9953.1315789473724.9521354329398398.88896907028
Trimmed Mean ( 30 / 32 )9952.9166666666724.3043655037461409.511479126357
Trimmed Mean ( 31 / 32 )9951.4705882352923.8051446413945418.038652490722
Trimmed Mean ( 32 / 32 )9949.8437523.073345071146431.226756212415
Median9933.5
Midrange10072
Midmean - Weighted Average at Xnp9942.87755102041
Midmean - Weighted Average at X(n+1)p9951.10416666667
Midmean - Empirical Distribution Function9942.87755102041
Midmean - Empirical Distribution Function - Averaging9951.10416666667
Midmean - Empirical Distribution Function - Interpolation9951.10416666667
Midmean - Closest Observation9942.87755102041
Midmean - True Basic - Statistics Graphics Toolkit9951.10416666667
Midmean - MS Excel (old versions)9950.64
Number of observations96

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 9963.73958333333 & 56.3631556678676 & 176.77753250806 \tabularnewline
Geometric Mean & 9948.61552853982 &  &  \tabularnewline
Harmonic Mean & 9933.50434777206 &  &  \tabularnewline
Quadratic Mean & 9978.87283161697 &  &  \tabularnewline
Winsorized Mean ( 1 / 32 ) & 9960.875 & 55.3870457374855 & 179.841240264211 \tabularnewline
Winsorized Mean ( 2 / 32 ) & 9960.8125 & 53.2119300378709 & 187.191340229736 \tabularnewline
Winsorized Mean ( 3 / 32 ) & 9966.25 & 51.8542745535379 & 192.197269864612 \tabularnewline
Winsorized Mean ( 4 / 32 ) & 9965.75 & 51.2096996020611 & 194.606687354965 \tabularnewline
Winsorized Mean ( 5 / 32 ) & 9964.76041666667 & 50.8478072824853 & 195.972273913551 \tabularnewline
Winsorized Mean ( 6 / 32 ) & 9964.63541666667 & 50.8252555843792 & 196.056769456349 \tabularnewline
Winsorized Mean ( 7 / 32 ) & 9968.42708333333 & 50.1935000177639 & 198.599959751869 \tabularnewline
Winsorized Mean ( 8 / 32 ) & 9965.76041666667 & 49.272707706549 & 202.257210543801 \tabularnewline
Winsorized Mean ( 9 / 32 ) & 9962.19791666667 & 47.0688549850476 & 211.651588291905 \tabularnewline
Winsorized Mean ( 10 / 32 ) & 9959.28125 & 46.2427867848887 & 215.369400125654 \tabularnewline
Winsorized Mean ( 11 / 32 ) & 9959.16666666667 & 45.9436336260013 & 216.769242671098 \tabularnewline
Winsorized Mean ( 12 / 32 ) & 9959.29166666667 & 45.6584260316763 & 218.126040082004 \tabularnewline
Winsorized Mean ( 13 / 32 ) & 9952.25 & 43.9724096112272 & 226.329420834353 \tabularnewline
Winsorized Mean ( 14 / 32 ) & 9955.60416666667 & 42.1262890353212 & 236.327585330844 \tabularnewline
Winsorized Mean ( 15 / 32 ) & 9957.16666666667 & 41.8621999726449 & 237.855790502488 \tabularnewline
Winsorized Mean ( 16 / 32 ) & 9953.33333333333 & 40.0388289244007 & 248.592019315218 \tabularnewline
Winsorized Mean ( 17 / 32 ) & 9952.27083333333 & 39.3979736075176 & 252.608698418802 \tabularnewline
Winsorized Mean ( 18 / 32 ) & 9947.02083333333 & 38.572769515072 & 257.876760170063 \tabularnewline
Winsorized Mean ( 19 / 32 ) & 9948.40625 & 38.3820464075448 & 259.194263494102 \tabularnewline
Winsorized Mean ( 20 / 32 ) & 9944.86458333333 & 37.0020554780871 & 268.765193036986 \tabularnewline
Winsorized Mean ( 21 / 32 ) & 9951.42708333333 & 35.5907529903376 & 279.607095866587 \tabularnewline
Winsorized Mean ( 22 / 32 ) & 9949.13541666667 & 34.8015225134269 & 285.88218842518 \tabularnewline
Winsorized Mean ( 23 / 32 ) & 9945.30208333333 & 31.992372034211 & 310.864792166656 \tabularnewline
Winsorized Mean ( 24 / 32 ) & 9946.05208333333 & 31.1247679121611 & 319.554256963542 \tabularnewline
Winsorized Mean ( 25 / 32 ) & 9953.08333333333 & 29.8285843520011 & 333.676020822142 \tabularnewline
Winsorized Mean ( 26 / 32 ) & 9948.20833333333 & 28.2630381210232 & 351.986516479043 \tabularnewline
Winsorized Mean ( 27 / 32 ) & 9939.48958333333 & 26.0201760228737 & 381.991635052575 \tabularnewline
Winsorized Mean ( 28 / 32 ) & 9948.82291666667 & 23.6586562678797 & 420.515130023414 \tabularnewline
Winsorized Mean ( 29 / 32 ) & 9955.46875 & 22.6452909066479 & 439.626445561686 \tabularnewline
Winsorized Mean ( 30 / 32 ) & 9968.28125 & 20.8729905174474 & 477.56842708608 \tabularnewline
Winsorized Mean ( 31 / 32 ) & 9968.28125 & 20.7976187018553 & 479.299163663902 \tabularnewline
Winsorized Mean ( 32 / 32 ) & 9969.94791666667 & 20.2240106658015 & 492.975803930211 \tabularnewline
Trimmed Mean ( 1 / 32 ) & 9961.43617021277 & 53.3253881032313 & 186.804757068597 \tabularnewline
Trimmed Mean ( 2 / 32 ) & 9962.02173913043 & 50.9580197321922 & 195.494679571252 \tabularnewline
Trimmed Mean ( 3 / 32 ) & 9962.66666666667 & 49.5898483429487 & 200.901333631186 \tabularnewline
Trimmed Mean ( 4 / 32 ) & 9961.36363636364 & 48.6078962870973 & 204.933033462874 \tabularnewline
Trimmed Mean ( 5 / 32 ) & 9960.13953488372 & 47.6988448319364 & 208.813013606044 \tabularnewline
Trimmed Mean ( 6 / 32 ) & 9959.08333333333 & 46.7556458752164 & 213.0027967085 \tabularnewline
Trimmed Mean ( 7 / 32 ) & 9958 & 45.6717336746739 & 218.034201874888 \tabularnewline
Trimmed Mean ( 8 / 32 ) & 9956.2125 & 44.5612851131287 & 223.427409571424 \tabularnewline
Trimmed Mean ( 9 / 32 ) & 9954.74358974359 & 43.4704742306313 & 229.00011481193 \tabularnewline
Trimmed Mean ( 10 / 32 ) & 9953.69736842105 & 42.6425083185445 & 233.421948213407 \tabularnewline
Trimmed Mean ( 11 / 32 ) & 9952.97297297297 & 41.8268276900628 & 237.956678109193 \tabularnewline
Trimmed Mean ( 12 / 32 ) & 9952.22222222222 & 40.9191883765457 & 243.216510812484 \tabularnewline
Trimmed Mean ( 13 / 32 ) & 9951.41428571429 & 39.8960994936381 & 249.433263201611 \tabularnewline
Trimmed Mean ( 14 / 32 ) & 9951.32352941176 & 38.9806487254319 & 255.288812649218 \tabularnewline
Trimmed Mean ( 15 / 32 ) & 9950.87878787879 & 38.202951564364 & 260.47408329468 \tabularnewline
Trimmed Mean ( 16 / 32 ) & 9950.25 & 37.3102009009579 & 266.68979956483 \tabularnewline
Trimmed Mean ( 17 / 32 ) & 9949.95161290323 & 36.540339605961 & 272.300469021367 \tabularnewline
Trimmed Mean ( 18 / 32 ) & 9949.73333333333 & 35.7091662943675 & 278.632473559113 \tabularnewline
Trimmed Mean ( 19 / 32 ) & 9949.98275862069 & 34.8312802393062 & 285.662275123393 \tabularnewline
Trimmed Mean ( 20 / 32 ) & 9950.125 & 33.7814698158928 & 294.543874326003 \tabularnewline
Trimmed Mean ( 21 / 32 ) & 9950.59259259259 & 32.7310527767741 & 304.010771069775 \tabularnewline
Trimmed Mean ( 22 / 32 ) & 9950.51923076923 & 31.6824302717142 & 314.07057935366 \tabularnewline
Trimmed Mean ( 23 / 32 ) & 9950.64 & 30.5121690009553 & 326.120375109631 \tabularnewline
Trimmed Mean ( 24 / 32 ) & 9951.10416666667 & 29.5813615302816 & 336.397773864465 \tabularnewline
Trimmed Mean ( 25 / 32 ) & 9951.54347826087 & 28.5574885315347 & 348.474042711139 \tabularnewline
Trimmed Mean ( 26 / 32 ) & 9951.40909090909 & 27.5024949508587 & 361.836593686872 \tabularnewline
Trimmed Mean ( 27 / 32 ) & 9951.69047619048 & 26.4629008186735 & 376.061964800475 \tabularnewline
Trimmed Mean ( 28 / 32 ) & 9952.775 & 25.5865170699185 & 388.985142948637 \tabularnewline
Trimmed Mean ( 29 / 32 ) & 9953.13157894737 & 24.9521354329398 & 398.88896907028 \tabularnewline
Trimmed Mean ( 30 / 32 ) & 9952.91666666667 & 24.3043655037461 & 409.511479126357 \tabularnewline
Trimmed Mean ( 31 / 32 ) & 9951.47058823529 & 23.8051446413945 & 418.038652490722 \tabularnewline
Trimmed Mean ( 32 / 32 ) & 9949.84375 & 23.073345071146 & 431.226756212415 \tabularnewline
Median & 9933.5 &  &  \tabularnewline
Midrange & 10072 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 9942.87755102041 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 9951.10416666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 9942.87755102041 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 9951.10416666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 9951.10416666667 &  &  \tabularnewline
Midmean - Closest Observation & 9942.87755102041 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 9951.10416666667 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 9950.64 &  &  \tabularnewline
Number of observations & 96 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164440&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]9963.73958333333[/C][C]56.3631556678676[/C][C]176.77753250806[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]9948.61552853982[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]9933.50434777206[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]9978.87283161697[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 32 )[/C][C]9960.875[/C][C]55.3870457374855[/C][C]179.841240264211[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 32 )[/C][C]9960.8125[/C][C]53.2119300378709[/C][C]187.191340229736[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 32 )[/C][C]9966.25[/C][C]51.8542745535379[/C][C]192.197269864612[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 32 )[/C][C]9965.75[/C][C]51.2096996020611[/C][C]194.606687354965[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 32 )[/C][C]9964.76041666667[/C][C]50.8478072824853[/C][C]195.972273913551[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 32 )[/C][C]9964.63541666667[/C][C]50.8252555843792[/C][C]196.056769456349[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 32 )[/C][C]9968.42708333333[/C][C]50.1935000177639[/C][C]198.599959751869[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 32 )[/C][C]9965.76041666667[/C][C]49.272707706549[/C][C]202.257210543801[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 32 )[/C][C]9962.19791666667[/C][C]47.0688549850476[/C][C]211.651588291905[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 32 )[/C][C]9959.28125[/C][C]46.2427867848887[/C][C]215.369400125654[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 32 )[/C][C]9959.16666666667[/C][C]45.9436336260013[/C][C]216.769242671098[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 32 )[/C][C]9959.29166666667[/C][C]45.6584260316763[/C][C]218.126040082004[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 32 )[/C][C]9952.25[/C][C]43.9724096112272[/C][C]226.329420834353[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 32 )[/C][C]9955.60416666667[/C][C]42.1262890353212[/C][C]236.327585330844[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 32 )[/C][C]9957.16666666667[/C][C]41.8621999726449[/C][C]237.855790502488[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 32 )[/C][C]9953.33333333333[/C][C]40.0388289244007[/C][C]248.592019315218[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 32 )[/C][C]9952.27083333333[/C][C]39.3979736075176[/C][C]252.608698418802[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 32 )[/C][C]9947.02083333333[/C][C]38.572769515072[/C][C]257.876760170063[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 32 )[/C][C]9948.40625[/C][C]38.3820464075448[/C][C]259.194263494102[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 32 )[/C][C]9944.86458333333[/C][C]37.0020554780871[/C][C]268.765193036986[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 32 )[/C][C]9951.42708333333[/C][C]35.5907529903376[/C][C]279.607095866587[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 32 )[/C][C]9949.13541666667[/C][C]34.8015225134269[/C][C]285.88218842518[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 32 )[/C][C]9945.30208333333[/C][C]31.992372034211[/C][C]310.864792166656[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 32 )[/C][C]9946.05208333333[/C][C]31.1247679121611[/C][C]319.554256963542[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 32 )[/C][C]9953.08333333333[/C][C]29.8285843520011[/C][C]333.676020822142[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 32 )[/C][C]9948.20833333333[/C][C]28.2630381210232[/C][C]351.986516479043[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 32 )[/C][C]9939.48958333333[/C][C]26.0201760228737[/C][C]381.991635052575[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 32 )[/C][C]9948.82291666667[/C][C]23.6586562678797[/C][C]420.515130023414[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 32 )[/C][C]9955.46875[/C][C]22.6452909066479[/C][C]439.626445561686[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 32 )[/C][C]9968.28125[/C][C]20.8729905174474[/C][C]477.56842708608[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 32 )[/C][C]9968.28125[/C][C]20.7976187018553[/C][C]479.299163663902[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 32 )[/C][C]9969.94791666667[/C][C]20.2240106658015[/C][C]492.975803930211[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 32 )[/C][C]9961.43617021277[/C][C]53.3253881032313[/C][C]186.804757068597[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 32 )[/C][C]9962.02173913043[/C][C]50.9580197321922[/C][C]195.494679571252[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 32 )[/C][C]9962.66666666667[/C][C]49.5898483429487[/C][C]200.901333631186[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 32 )[/C][C]9961.36363636364[/C][C]48.6078962870973[/C][C]204.933033462874[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 32 )[/C][C]9960.13953488372[/C][C]47.6988448319364[/C][C]208.813013606044[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 32 )[/C][C]9959.08333333333[/C][C]46.7556458752164[/C][C]213.0027967085[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 32 )[/C][C]9958[/C][C]45.6717336746739[/C][C]218.034201874888[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 32 )[/C][C]9956.2125[/C][C]44.5612851131287[/C][C]223.427409571424[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 32 )[/C][C]9954.74358974359[/C][C]43.4704742306313[/C][C]229.00011481193[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 32 )[/C][C]9953.69736842105[/C][C]42.6425083185445[/C][C]233.421948213407[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 32 )[/C][C]9952.97297297297[/C][C]41.8268276900628[/C][C]237.956678109193[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 32 )[/C][C]9952.22222222222[/C][C]40.9191883765457[/C][C]243.216510812484[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 32 )[/C][C]9951.41428571429[/C][C]39.8960994936381[/C][C]249.433263201611[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 32 )[/C][C]9951.32352941176[/C][C]38.9806487254319[/C][C]255.288812649218[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 32 )[/C][C]9950.87878787879[/C][C]38.202951564364[/C][C]260.47408329468[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 32 )[/C][C]9950.25[/C][C]37.3102009009579[/C][C]266.68979956483[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 32 )[/C][C]9949.95161290323[/C][C]36.540339605961[/C][C]272.300469021367[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 32 )[/C][C]9949.73333333333[/C][C]35.7091662943675[/C][C]278.632473559113[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 32 )[/C][C]9949.98275862069[/C][C]34.8312802393062[/C][C]285.662275123393[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 32 )[/C][C]9950.125[/C][C]33.7814698158928[/C][C]294.543874326003[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 32 )[/C][C]9950.59259259259[/C][C]32.7310527767741[/C][C]304.010771069775[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 32 )[/C][C]9950.51923076923[/C][C]31.6824302717142[/C][C]314.07057935366[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 32 )[/C][C]9950.64[/C][C]30.5121690009553[/C][C]326.120375109631[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 32 )[/C][C]9951.10416666667[/C][C]29.5813615302816[/C][C]336.397773864465[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 32 )[/C][C]9951.54347826087[/C][C]28.5574885315347[/C][C]348.474042711139[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 32 )[/C][C]9951.40909090909[/C][C]27.5024949508587[/C][C]361.836593686872[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 32 )[/C][C]9951.69047619048[/C][C]26.4629008186735[/C][C]376.061964800475[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 32 )[/C][C]9952.775[/C][C]25.5865170699185[/C][C]388.985142948637[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 32 )[/C][C]9953.13157894737[/C][C]24.9521354329398[/C][C]398.88896907028[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 32 )[/C][C]9952.91666666667[/C][C]24.3043655037461[/C][C]409.511479126357[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 32 )[/C][C]9951.47058823529[/C][C]23.8051446413945[/C][C]418.038652490722[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 32 )[/C][C]9949.84375[/C][C]23.073345071146[/C][C]431.226756212415[/C][/ROW]
[ROW][C]Median[/C][C]9933.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]10072[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]9942.87755102041[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]9951.10416666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]9942.87755102041[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]9951.10416666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]9951.10416666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]9942.87755102041[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]9951.10416666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]9950.64[/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=164440&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164440&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 Mean9963.7395833333356.3631556678676176.77753250806
Geometric Mean9948.61552853982
Harmonic Mean9933.50434777206
Quadratic Mean9978.87283161697
Winsorized Mean ( 1 / 32 )9960.87555.3870457374855179.841240264211
Winsorized Mean ( 2 / 32 )9960.812553.2119300378709187.191340229736
Winsorized Mean ( 3 / 32 )9966.2551.8542745535379192.197269864612
Winsorized Mean ( 4 / 32 )9965.7551.2096996020611194.606687354965
Winsorized Mean ( 5 / 32 )9964.7604166666750.8478072824853195.972273913551
Winsorized Mean ( 6 / 32 )9964.6354166666750.8252555843792196.056769456349
Winsorized Mean ( 7 / 32 )9968.4270833333350.1935000177639198.599959751869
Winsorized Mean ( 8 / 32 )9965.7604166666749.272707706549202.257210543801
Winsorized Mean ( 9 / 32 )9962.1979166666747.0688549850476211.651588291905
Winsorized Mean ( 10 / 32 )9959.2812546.2427867848887215.369400125654
Winsorized Mean ( 11 / 32 )9959.1666666666745.9436336260013216.769242671098
Winsorized Mean ( 12 / 32 )9959.2916666666745.6584260316763218.126040082004
Winsorized Mean ( 13 / 32 )9952.2543.9724096112272226.329420834353
Winsorized Mean ( 14 / 32 )9955.6041666666742.1262890353212236.327585330844
Winsorized Mean ( 15 / 32 )9957.1666666666741.8621999726449237.855790502488
Winsorized Mean ( 16 / 32 )9953.3333333333340.0388289244007248.592019315218
Winsorized Mean ( 17 / 32 )9952.2708333333339.3979736075176252.608698418802
Winsorized Mean ( 18 / 32 )9947.0208333333338.572769515072257.876760170063
Winsorized Mean ( 19 / 32 )9948.4062538.3820464075448259.194263494102
Winsorized Mean ( 20 / 32 )9944.8645833333337.0020554780871268.765193036986
Winsorized Mean ( 21 / 32 )9951.4270833333335.5907529903376279.607095866587
Winsorized Mean ( 22 / 32 )9949.1354166666734.8015225134269285.88218842518
Winsorized Mean ( 23 / 32 )9945.3020833333331.992372034211310.864792166656
Winsorized Mean ( 24 / 32 )9946.0520833333331.1247679121611319.554256963542
Winsorized Mean ( 25 / 32 )9953.0833333333329.8285843520011333.676020822142
Winsorized Mean ( 26 / 32 )9948.2083333333328.2630381210232351.986516479043
Winsorized Mean ( 27 / 32 )9939.4895833333326.0201760228737381.991635052575
Winsorized Mean ( 28 / 32 )9948.8229166666723.6586562678797420.515130023414
Winsorized Mean ( 29 / 32 )9955.4687522.6452909066479439.626445561686
Winsorized Mean ( 30 / 32 )9968.2812520.8729905174474477.56842708608
Winsorized Mean ( 31 / 32 )9968.2812520.7976187018553479.299163663902
Winsorized Mean ( 32 / 32 )9969.9479166666720.2240106658015492.975803930211
Trimmed Mean ( 1 / 32 )9961.4361702127753.3253881032313186.804757068597
Trimmed Mean ( 2 / 32 )9962.0217391304350.9580197321922195.494679571252
Trimmed Mean ( 3 / 32 )9962.6666666666749.5898483429487200.901333631186
Trimmed Mean ( 4 / 32 )9961.3636363636448.6078962870973204.933033462874
Trimmed Mean ( 5 / 32 )9960.1395348837247.6988448319364208.813013606044
Trimmed Mean ( 6 / 32 )9959.0833333333346.7556458752164213.0027967085
Trimmed Mean ( 7 / 32 )995845.6717336746739218.034201874888
Trimmed Mean ( 8 / 32 )9956.212544.5612851131287223.427409571424
Trimmed Mean ( 9 / 32 )9954.7435897435943.4704742306313229.00011481193
Trimmed Mean ( 10 / 32 )9953.6973684210542.6425083185445233.421948213407
Trimmed Mean ( 11 / 32 )9952.9729729729741.8268276900628237.956678109193
Trimmed Mean ( 12 / 32 )9952.2222222222240.9191883765457243.216510812484
Trimmed Mean ( 13 / 32 )9951.4142857142939.8960994936381249.433263201611
Trimmed Mean ( 14 / 32 )9951.3235294117638.9806487254319255.288812649218
Trimmed Mean ( 15 / 32 )9950.8787878787938.202951564364260.47408329468
Trimmed Mean ( 16 / 32 )9950.2537.3102009009579266.68979956483
Trimmed Mean ( 17 / 32 )9949.9516129032336.540339605961272.300469021367
Trimmed Mean ( 18 / 32 )9949.7333333333335.7091662943675278.632473559113
Trimmed Mean ( 19 / 32 )9949.9827586206934.8312802393062285.662275123393
Trimmed Mean ( 20 / 32 )9950.12533.7814698158928294.543874326003
Trimmed Mean ( 21 / 32 )9950.5925925925932.7310527767741304.010771069775
Trimmed Mean ( 22 / 32 )9950.5192307692331.6824302717142314.07057935366
Trimmed Mean ( 23 / 32 )9950.6430.5121690009553326.120375109631
Trimmed Mean ( 24 / 32 )9951.1041666666729.5813615302816336.397773864465
Trimmed Mean ( 25 / 32 )9951.5434782608728.5574885315347348.474042711139
Trimmed Mean ( 26 / 32 )9951.4090909090927.5024949508587361.836593686872
Trimmed Mean ( 27 / 32 )9951.6904761904826.4629008186735376.061964800475
Trimmed Mean ( 28 / 32 )9952.77525.5865170699185388.985142948637
Trimmed Mean ( 29 / 32 )9953.1315789473724.9521354329398398.88896907028
Trimmed Mean ( 30 / 32 )9952.9166666666724.3043655037461409.511479126357
Trimmed Mean ( 31 / 32 )9951.4705882352923.8051446413945418.038652490722
Trimmed Mean ( 32 / 32 )9949.8437523.073345071146431.226756212415
Median9933.5
Midrange10072
Midmean - Weighted Average at Xnp9942.87755102041
Midmean - Weighted Average at X(n+1)p9951.10416666667
Midmean - Empirical Distribution Function9942.87755102041
Midmean - Empirical Distribution Function - Averaging9951.10416666667
Midmean - Empirical Distribution Function - Interpolation9951.10416666667
Midmean - Closest Observation9942.87755102041
Midmean - True Basic - Statistics Graphics Toolkit9951.10416666667
Midmean - MS Excel (old versions)9950.64
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')