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Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationWed, 09 Oct 2013 12:46:24 -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/2013/Oct/09/t1381337204g7juafyiwfu6bq6.htm/, Retrieved Sun, 28 Apr 2024 21:02:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=214467, Retrieved Sun, 28 Apr 2024 21:02:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kernel Density Estimation] [] [2013-09-26 09:08:29] [99f0649bd6aaa22f81266a2f80a3ecd7]
- RMPD  [Central Tendency] [] [2013-10-09 16:24:13] [99f0649bd6aaa22f81266a2f80a3ecd7]
-    D      [Central Tendency] [] [2013-10-09 16:46:24] [3050d341fa02a6066b7b273abfa2c28b] [Current]
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Dataseries X:
9969
9692
8943
8802
8250
8515
13973
13905
12467
9490
8483
7610
7839
7107
6584
6053
5725
6480
11663
11628
9203
7781
7020
6908
6912
6668
6189
6007
5148
6685
11044
11034
8986
8146
7818
8176
8935
8929
8835
8455
7924
8973
13575
13844
11738
10467
10145
10833
10179
10107
9533
9165
8382
9018
13911
13761
11316
9855
9034
8932
9278
8876
8298
7733
7226
7688
12226
12081
10439
9008
8377
8346
9167
8945
8428
7973
7446
7785
10561
12791
11583
10112
9597
9332




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 3 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=214467&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=214467&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=214467&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 time3 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean9238.63095238095225.89944387598140.8970947155274
Geometric Mean9016.96058393748
Harmonic Mean8801.5164903149
Quadratic Mean9465.08522148639
Winsorized Mean ( 1 / 28 )9244.7619047619224.31479820029141.2133393736567
Winsorized Mean ( 2 / 28 )9251.33333333333223.05583607019241.4754148392786
Winsorized Mean ( 3 / 28 )9250.79761904762222.22439903919441.6281815095202
Winsorized Mean ( 4 / 28 )9253.32142857143220.14017737304742.0337692964191
Winsorized Mean ( 5 / 28 )9259.57142857143214.62805977004143.1424084925913
Winsorized Mean ( 6 / 28 )9211200.6346807020245.9093112305945
Winsorized Mean ( 7 / 28 )9191193.88056295246147.4054740714448
Winsorized Mean ( 8 / 28 )9169.66666666667189.05258577289148.5032597104077
Winsorized Mean ( 9 / 28 )9178.02380952381182.36425171337950.3279766911163
Winsorized Mean ( 10 / 28 )9137.66666666667174.70969062772452.3020024466613
Winsorized Mean ( 11 / 28 )9141.9880952381170.81171629938853.5208491156109
Winsorized Mean ( 12 / 28 )9149.41666666667168.08294506688154.4339383333989
Winsorized Mean ( 13 / 28 )9160.86904761905164.18940808358955.7945189920853
Winsorized Mean ( 14 / 28 )9153.03571428571151.29776662029160.4968329589218
Winsorized Mean ( 15 / 28 )9133.75139.16690478746765.6316242281085
Winsorized Mean ( 16 / 28 )9146.70238095238136.91754303755566.8044589322171
Winsorized Mean ( 17 / 28 )9115.13095238095129.10383526857870.603099694277
Winsorized Mean ( 18 / 28 )9067.13095238095118.6664859030676.4085232943359
Winsorized Mean ( 19 / 28 )9046.77380952381115.35798300519478.4234742481282
Winsorized Mean ( 20 / 28 )9047.96428571429113.33923086275779.830824833023
Winsorized Mean ( 21 / 28 )8988.21428571429103.31206461029487.0006259154629
Winsorized Mean ( 22 / 28 )9001.5714285714399.124641609517290.8106327791975
Winsorized Mean ( 23 / 28 )9005.9523809523896.123090706954293.6918727302308
Winsorized Mean ( 24 / 28 )9053.9523809523889.7030079438978100.932539370529
Winsorized Mean ( 25 / 28 )9021.8095238095282.8744903233445108.861116232629
Winsorized Mean ( 26 / 28 )9009.4285714285775.2531914563008119.721547977939
Winsorized Mean ( 27 / 28 )8972.4642857142966.3968718512539135.133840428732
Winsorized Mean ( 28 / 28 )8956.7976190476260.3490487256336148.41655018902
Trimmed Mean ( 1 / 28 )9230.78048780488218.33748454812942.2775800816285
Trimmed Mean ( 2 / 28 )9216.1211.39242154362143.5971163616112
Trimmed Mean ( 3 / 28 )9197.12820512821204.06627128602545.06932060437
Trimmed Mean ( 4 / 28 )9177.3552631579195.83355061185246.8630387106023
Trimmed Mean ( 5 / 28 )9155.7972972973186.86257116773648.9974917934671
Trimmed Mean ( 6 / 28 )9131.58333333333177.95873929435551.3129243865293
Trimmed Mean ( 7 / 28 )9115.7171.45966737466853.1652728573225
Trimmed Mean ( 8 / 28 )9102.41176470588165.48005462610355.0060959628791
Trimmed Mean ( 9 / 28 )9091.71212121212159.50949254571656.9979377158786
Trimmed Mean ( 10 / 28 )9079.125153.85028910708459.012726285361
Trimmed Mean ( 11 / 28 )9071.1935483871148.73620229607360.9884709193399
Trimmed Mean ( 12 / 28 )9062.18333333333143.3432616946463.2201557729184
Trimmed Mean ( 13 / 28 )9051.65517241379137.30270793618365.9248117423943
Trimmed Mean ( 14 / 28 )9039.05357142857130.65172157464169.1843434015877
Trimmed Mean ( 15 / 28 )9026.38888888889125.17526613248972.110003579582
Trimmed Mean ( 16 / 28 )9014.82692307692120.8946935933574.5675980899527
Trimmed Mean ( 17 / 28 )9000.98115.90506491723977.658211109472
Trimmed Mean ( 18 / 28 )8989.22916666667111.29190277708580.7716369507303
Trimmed Mean ( 19 / 28 )8981.32608695652107.69748315813683.394020209079
Trimmed Mean ( 20 / 28 )8974.75103.75885364296586.4962331877928
Trimmed Mean ( 21 / 28 )8967.4285714285799.021731462384290.5602077341484
Trimmed Mean ( 22 / 28 )8965.3595.216699879261994.157327563005
Trimmed Mean ( 23 / 28 )8961.7105263157991.092686512822798.3801320323811
Trimmed Mean ( 24 / 28 )8957.2222222222286.2139099658804103.895325310812
Trimmed Mean ( 25 / 28 )8947.2647058823581.1126646406363110.306630234903
Trimmed Mean ( 26 / 28 )8939.437576.0755001878439117.507442973453
Trimmed Mean ( 27 / 28 )8931.971.3248896603245125.228374590371
Trimmed Mean ( 28 / 28 )8927.3928571428667.5119887312541132.234185733741
Median8944
Midrange9560.5
Midmean - Weighted Average at Xnp8940.6976744186
Midmean - Weighted Average at X(n+1)p8967.42857142857
Midmean - Empirical Distribution Function8940.6976744186
Midmean - Empirical Distribution Function - Averaging8967.42857142857
Midmean - Empirical Distribution Function - Interpolation8967.42857142857
Midmean - Closest Observation8940.6976744186
Midmean - True Basic - Statistics Graphics Toolkit8967.42857142857
Midmean - MS Excel (old versions)8974.75
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 9238.63095238095 & 225.899443875981 & 40.8970947155274 \tabularnewline
Geometric Mean & 9016.96058393748 &  &  \tabularnewline
Harmonic Mean & 8801.5164903149 &  &  \tabularnewline
Quadratic Mean & 9465.08522148639 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 9244.7619047619 & 224.314798200291 & 41.2133393736567 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 9251.33333333333 & 223.055836070192 & 41.4754148392786 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 9250.79761904762 & 222.224399039194 & 41.6281815095202 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 9253.32142857143 & 220.140177373047 & 42.0337692964191 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 9259.57142857143 & 214.628059770041 & 43.1424084925913 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 9211 & 200.63468070202 & 45.9093112305945 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 9191 & 193.880562952461 & 47.4054740714448 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 9169.66666666667 & 189.052585772891 & 48.5032597104077 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 9178.02380952381 & 182.364251713379 & 50.3279766911163 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 9137.66666666667 & 174.709690627724 & 52.3020024466613 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 9141.9880952381 & 170.811716299388 & 53.5208491156109 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 9149.41666666667 & 168.082945066881 & 54.4339383333989 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 9160.86904761905 & 164.189408083589 & 55.7945189920853 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 9153.03571428571 & 151.297766620291 & 60.4968329589218 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 9133.75 & 139.166904787467 & 65.6316242281085 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 9146.70238095238 & 136.917543037555 & 66.8044589322171 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 9115.13095238095 & 129.103835268578 & 70.603099694277 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 9067.13095238095 & 118.66648590306 & 76.4085232943359 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 9046.77380952381 & 115.357983005194 & 78.4234742481282 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 9047.96428571429 & 113.339230862757 & 79.830824833023 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 8988.21428571429 & 103.312064610294 & 87.0006259154629 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 9001.57142857143 & 99.1246416095172 & 90.8106327791975 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 9005.95238095238 & 96.1230907069542 & 93.6918727302308 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 9053.95238095238 & 89.7030079438978 & 100.932539370529 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 9021.80952380952 & 82.8744903233445 & 108.861116232629 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 9009.42857142857 & 75.2531914563008 & 119.721547977939 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 8972.46428571429 & 66.3968718512539 & 135.133840428732 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 8956.79761904762 & 60.3490487256336 & 148.41655018902 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 9230.78048780488 & 218.337484548129 & 42.2775800816285 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 9216.1 & 211.392421543621 & 43.5971163616112 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 9197.12820512821 & 204.066271286025 & 45.06932060437 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 9177.3552631579 & 195.833550611852 & 46.8630387106023 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 9155.7972972973 & 186.862571167736 & 48.9974917934671 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 9131.58333333333 & 177.958739294355 & 51.3129243865293 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 9115.7 & 171.459667374668 & 53.1652728573225 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 9102.41176470588 & 165.480054626103 & 55.0060959628791 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 9091.71212121212 & 159.509492545716 & 56.9979377158786 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 9079.125 & 153.850289107084 & 59.012726285361 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 9071.1935483871 & 148.736202296073 & 60.9884709193399 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 9062.18333333333 & 143.34326169464 & 63.2201557729184 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 9051.65517241379 & 137.302707936183 & 65.9248117423943 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 9039.05357142857 & 130.651721574641 & 69.1843434015877 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 9026.38888888889 & 125.175266132489 & 72.110003579582 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 9014.82692307692 & 120.89469359335 & 74.5675980899527 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 9000.98 & 115.905064917239 & 77.658211109472 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 8989.22916666667 & 111.291902777085 & 80.7716369507303 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 8981.32608695652 & 107.697483158136 & 83.394020209079 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 8974.75 & 103.758853642965 & 86.4962331877928 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 8967.42857142857 & 99.0217314623842 & 90.5602077341484 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 8965.35 & 95.2166998792619 & 94.157327563005 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 8961.71052631579 & 91.0926865128227 & 98.3801320323811 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 8957.22222222222 & 86.2139099658804 & 103.895325310812 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 8947.26470588235 & 81.1126646406363 & 110.306630234903 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 8939.4375 & 76.0755001878439 & 117.507442973453 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 8931.9 & 71.3248896603245 & 125.228374590371 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 8927.39285714286 & 67.5119887312541 & 132.234185733741 \tabularnewline
Median & 8944 &  &  \tabularnewline
Midrange & 9560.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 8940.6976744186 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 8967.42857142857 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 8940.6976744186 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 8967.42857142857 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 8967.42857142857 &  &  \tabularnewline
Midmean - Closest Observation & 8940.6976744186 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 8967.42857142857 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 8974.75 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=214467&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]9238.63095238095[/C][C]225.899443875981[/C][C]40.8970947155274[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]9016.96058393748[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]8801.5164903149[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]9465.08522148639[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]9244.7619047619[/C][C]224.314798200291[/C][C]41.2133393736567[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]9251.33333333333[/C][C]223.055836070192[/C][C]41.4754148392786[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]9250.79761904762[/C][C]222.224399039194[/C][C]41.6281815095202[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]9253.32142857143[/C][C]220.140177373047[/C][C]42.0337692964191[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]9259.57142857143[/C][C]214.628059770041[/C][C]43.1424084925913[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]9211[/C][C]200.63468070202[/C][C]45.9093112305945[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]9191[/C][C]193.880562952461[/C][C]47.4054740714448[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]9169.66666666667[/C][C]189.052585772891[/C][C]48.5032597104077[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]9178.02380952381[/C][C]182.364251713379[/C][C]50.3279766911163[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]9137.66666666667[/C][C]174.709690627724[/C][C]52.3020024466613[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]9141.9880952381[/C][C]170.811716299388[/C][C]53.5208491156109[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]9149.41666666667[/C][C]168.082945066881[/C][C]54.4339383333989[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]9160.86904761905[/C][C]164.189408083589[/C][C]55.7945189920853[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]9153.03571428571[/C][C]151.297766620291[/C][C]60.4968329589218[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]9133.75[/C][C]139.166904787467[/C][C]65.6316242281085[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]9146.70238095238[/C][C]136.917543037555[/C][C]66.8044589322171[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]9115.13095238095[/C][C]129.103835268578[/C][C]70.603099694277[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]9067.13095238095[/C][C]118.66648590306[/C][C]76.4085232943359[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]9046.77380952381[/C][C]115.357983005194[/C][C]78.4234742481282[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]9047.96428571429[/C][C]113.339230862757[/C][C]79.830824833023[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]8988.21428571429[/C][C]103.312064610294[/C][C]87.0006259154629[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]9001.57142857143[/C][C]99.1246416095172[/C][C]90.8106327791975[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]9005.95238095238[/C][C]96.1230907069542[/C][C]93.6918727302308[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]9053.95238095238[/C][C]89.7030079438978[/C][C]100.932539370529[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]9021.80952380952[/C][C]82.8744903233445[/C][C]108.861116232629[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]9009.42857142857[/C][C]75.2531914563008[/C][C]119.721547977939[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]8972.46428571429[/C][C]66.3968718512539[/C][C]135.133840428732[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]8956.79761904762[/C][C]60.3490487256336[/C][C]148.41655018902[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]9230.78048780488[/C][C]218.337484548129[/C][C]42.2775800816285[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]9216.1[/C][C]211.392421543621[/C][C]43.5971163616112[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]9197.12820512821[/C][C]204.066271286025[/C][C]45.06932060437[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]9177.3552631579[/C][C]195.833550611852[/C][C]46.8630387106023[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]9155.7972972973[/C][C]186.862571167736[/C][C]48.9974917934671[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]9131.58333333333[/C][C]177.958739294355[/C][C]51.3129243865293[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]9115.7[/C][C]171.459667374668[/C][C]53.1652728573225[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]9102.41176470588[/C][C]165.480054626103[/C][C]55.0060959628791[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]9091.71212121212[/C][C]159.509492545716[/C][C]56.9979377158786[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]9079.125[/C][C]153.850289107084[/C][C]59.012726285361[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]9071.1935483871[/C][C]148.736202296073[/C][C]60.9884709193399[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]9062.18333333333[/C][C]143.34326169464[/C][C]63.2201557729184[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]9051.65517241379[/C][C]137.302707936183[/C][C]65.9248117423943[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]9039.05357142857[/C][C]130.651721574641[/C][C]69.1843434015877[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]9026.38888888889[/C][C]125.175266132489[/C][C]72.110003579582[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]9014.82692307692[/C][C]120.89469359335[/C][C]74.5675980899527[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]9000.98[/C][C]115.905064917239[/C][C]77.658211109472[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]8989.22916666667[/C][C]111.291902777085[/C][C]80.7716369507303[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]8981.32608695652[/C][C]107.697483158136[/C][C]83.394020209079[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]8974.75[/C][C]103.758853642965[/C][C]86.4962331877928[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]8967.42857142857[/C][C]99.0217314623842[/C][C]90.5602077341484[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]8965.35[/C][C]95.2166998792619[/C][C]94.157327563005[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]8961.71052631579[/C][C]91.0926865128227[/C][C]98.3801320323811[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]8957.22222222222[/C][C]86.2139099658804[/C][C]103.895325310812[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]8947.26470588235[/C][C]81.1126646406363[/C][C]110.306630234903[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]8939.4375[/C][C]76.0755001878439[/C][C]117.507442973453[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]8931.9[/C][C]71.3248896603245[/C][C]125.228374590371[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]8927.39285714286[/C][C]67.5119887312541[/C][C]132.234185733741[/C][/ROW]
[ROW][C]Median[/C][C]8944[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]9560.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]8940.6976744186[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]8967.42857142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]8940.6976744186[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]8967.42857142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]8967.42857142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]8940.6976744186[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]8967.42857142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]8974.75[/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=214467&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=214467&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 Mean9238.63095238095225.89944387598140.8970947155274
Geometric Mean9016.96058393748
Harmonic Mean8801.5164903149
Quadratic Mean9465.08522148639
Winsorized Mean ( 1 / 28 )9244.7619047619224.31479820029141.2133393736567
Winsorized Mean ( 2 / 28 )9251.33333333333223.05583607019241.4754148392786
Winsorized Mean ( 3 / 28 )9250.79761904762222.22439903919441.6281815095202
Winsorized Mean ( 4 / 28 )9253.32142857143220.14017737304742.0337692964191
Winsorized Mean ( 5 / 28 )9259.57142857143214.62805977004143.1424084925913
Winsorized Mean ( 6 / 28 )9211200.6346807020245.9093112305945
Winsorized Mean ( 7 / 28 )9191193.88056295246147.4054740714448
Winsorized Mean ( 8 / 28 )9169.66666666667189.05258577289148.5032597104077
Winsorized Mean ( 9 / 28 )9178.02380952381182.36425171337950.3279766911163
Winsorized Mean ( 10 / 28 )9137.66666666667174.70969062772452.3020024466613
Winsorized Mean ( 11 / 28 )9141.9880952381170.81171629938853.5208491156109
Winsorized Mean ( 12 / 28 )9149.41666666667168.08294506688154.4339383333989
Winsorized Mean ( 13 / 28 )9160.86904761905164.18940808358955.7945189920853
Winsorized Mean ( 14 / 28 )9153.03571428571151.29776662029160.4968329589218
Winsorized Mean ( 15 / 28 )9133.75139.16690478746765.6316242281085
Winsorized Mean ( 16 / 28 )9146.70238095238136.91754303755566.8044589322171
Winsorized Mean ( 17 / 28 )9115.13095238095129.10383526857870.603099694277
Winsorized Mean ( 18 / 28 )9067.13095238095118.6664859030676.4085232943359
Winsorized Mean ( 19 / 28 )9046.77380952381115.35798300519478.4234742481282
Winsorized Mean ( 20 / 28 )9047.96428571429113.33923086275779.830824833023
Winsorized Mean ( 21 / 28 )8988.21428571429103.31206461029487.0006259154629
Winsorized Mean ( 22 / 28 )9001.5714285714399.124641609517290.8106327791975
Winsorized Mean ( 23 / 28 )9005.9523809523896.123090706954293.6918727302308
Winsorized Mean ( 24 / 28 )9053.9523809523889.7030079438978100.932539370529
Winsorized Mean ( 25 / 28 )9021.8095238095282.8744903233445108.861116232629
Winsorized Mean ( 26 / 28 )9009.4285714285775.2531914563008119.721547977939
Winsorized Mean ( 27 / 28 )8972.4642857142966.3968718512539135.133840428732
Winsorized Mean ( 28 / 28 )8956.7976190476260.3490487256336148.41655018902
Trimmed Mean ( 1 / 28 )9230.78048780488218.33748454812942.2775800816285
Trimmed Mean ( 2 / 28 )9216.1211.39242154362143.5971163616112
Trimmed Mean ( 3 / 28 )9197.12820512821204.06627128602545.06932060437
Trimmed Mean ( 4 / 28 )9177.3552631579195.83355061185246.8630387106023
Trimmed Mean ( 5 / 28 )9155.7972972973186.86257116773648.9974917934671
Trimmed Mean ( 6 / 28 )9131.58333333333177.95873929435551.3129243865293
Trimmed Mean ( 7 / 28 )9115.7171.45966737466853.1652728573225
Trimmed Mean ( 8 / 28 )9102.41176470588165.48005462610355.0060959628791
Trimmed Mean ( 9 / 28 )9091.71212121212159.50949254571656.9979377158786
Trimmed Mean ( 10 / 28 )9079.125153.85028910708459.012726285361
Trimmed Mean ( 11 / 28 )9071.1935483871148.73620229607360.9884709193399
Trimmed Mean ( 12 / 28 )9062.18333333333143.3432616946463.2201557729184
Trimmed Mean ( 13 / 28 )9051.65517241379137.30270793618365.9248117423943
Trimmed Mean ( 14 / 28 )9039.05357142857130.65172157464169.1843434015877
Trimmed Mean ( 15 / 28 )9026.38888888889125.17526613248972.110003579582
Trimmed Mean ( 16 / 28 )9014.82692307692120.8946935933574.5675980899527
Trimmed Mean ( 17 / 28 )9000.98115.90506491723977.658211109472
Trimmed Mean ( 18 / 28 )8989.22916666667111.29190277708580.7716369507303
Trimmed Mean ( 19 / 28 )8981.32608695652107.69748315813683.394020209079
Trimmed Mean ( 20 / 28 )8974.75103.75885364296586.4962331877928
Trimmed Mean ( 21 / 28 )8967.4285714285799.021731462384290.5602077341484
Trimmed Mean ( 22 / 28 )8965.3595.216699879261994.157327563005
Trimmed Mean ( 23 / 28 )8961.7105263157991.092686512822798.3801320323811
Trimmed Mean ( 24 / 28 )8957.2222222222286.2139099658804103.895325310812
Trimmed Mean ( 25 / 28 )8947.2647058823581.1126646406363110.306630234903
Trimmed Mean ( 26 / 28 )8939.437576.0755001878439117.507442973453
Trimmed Mean ( 27 / 28 )8931.971.3248896603245125.228374590371
Trimmed Mean ( 28 / 28 )8927.3928571428667.5119887312541132.234185733741
Median8944
Midrange9560.5
Midmean - Weighted Average at Xnp8940.6976744186
Midmean - Weighted Average at X(n+1)p8967.42857142857
Midmean - Empirical Distribution Function8940.6976744186
Midmean - Empirical Distribution Function - Averaging8967.42857142857
Midmean - Empirical Distribution Function - Interpolation8967.42857142857
Midmean - Closest Observation8940.6976744186
Midmean - True Basic - Statistics Graphics Toolkit8967.42857142857
Midmean - MS Excel (old versions)8974.75
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')