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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSat, 12 Oct 2013 15:06:53 -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/12/t13816048286bh8aglja06yspn.htm/, Retrieved Mon, 29 Apr 2024 07:48:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=214982, Retrieved Mon, 29 Apr 2024 07:48:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact85

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2013-10-12 19:06:53] [2ad58ca14453c04e73fc838d0bf536d8] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
126,81
125,8
123,07
119,52
118,03
117,27
117,27
116,69
115,38
114,31
113,33
111,79
111,79
110,92
109,37
107,04
104,72
104,14
104,14
102,95
102,13
101,01
100,07
99,4
99,4
99,34
97,72
96,26
95,77
95,04
95,04
94,55
94
93,14
91,21
90,3
90,3
89,74
89,07
89,06
88,97
88,78
88,78
88,23
87,91
87,79
87,89
88
88
87,08
85,75
84,29
84,39
83,72
83,72
81,76
81,53
80,55
79,83
78,98
78,98
78,27
77,41
76,75
76,38
74,96
74,96
74,46
74,04
73,22
72,97
72,91
72,91
73,27
72,93
72,67
71,94
71,9
71,89
71,72
70,85
69,82
69,61
69,48

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=214982&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=214982&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=214982&T=0

As an alternative you can also use a QR Code:  
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'Gertrude Mary Cox' @ cox.wessa.net






Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean91.0373809523811.7069088973663553.3346455061811
Geometric Mean89.7557864093807
Harmonic Mean88.5283253891804
Quadratic Mean92.3559872630537
Winsorized Mean ( 1 / 28 )91.02690476190481.7036775127911153.4296567739378
Winsorized Mean ( 2 / 28 )90.96690476190481.6874774257531853.9070350652561
Winsorized Mean ( 3 / 28 )90.87690476190481.6542489579631854.9354462787743
Winsorized Mean ( 4 / 28 )90.8473809523811.6337911951984555.6052580154506
Winsorized Mean ( 5 / 28 )90.81226190476191.6233911436419255.9398529802455
Winsorized Mean ( 6 / 28 )90.81297619047621.623290855267955.9437490180951
Winsorized Mean ( 7 / 28 )90.76797619047621.6133987866793356.2588598304906
Winsorized Mean ( 8 / 28 )90.71273809523811.5799138696974557.4162553004293
Winsorized Mean ( 9 / 28 )90.62380952380951.5550763292182358.2761166259718
Winsorized Mean ( 10 / 28 )90.50714285714291.5339127179780859.0041022519486
Winsorized Mean ( 11 / 28 )90.30809523809521.4980442162320560.2839984691789
Winsorized Mean ( 12 / 28 )90.31380952380951.4972461324724660.3199484474013
Winsorized Mean ( 13 / 28 )90.21785714285711.4687803714117161.4236538687843
Winsorized Mean ( 14 / 28 )89.96785714285711.4244683568201963.1589018542263
Winsorized Mean ( 15 / 28 )89.68928571428571.3383886749161667.0128845194419
Winsorized Mean ( 16 / 28 )89.32738095238091.2599762098202170.8960853833323
Winsorized Mean ( 17 / 28 )89.31119047619051.2284860055716272.700209909704
Winsorized Mean ( 18 / 28 )89.31119047619051.2284860055716272.700209909704
Winsorized Mean ( 19 / 28 )89.36321428571431.1450978878293678.0398036146157
Winsorized Mean ( 20 / 28 )89.25607142857141.1054196018749380.7440643147471
Winsorized Mean ( 21 / 28 )89.14107142857141.044174480030285.3699004652877
Winsorized Mean ( 22 / 28 )89.12011904761910.98047818859708490.8945452168972
Winsorized Mean ( 23 / 28 )89.13107142857140.93018742856593795.8205504518419
Winsorized Mean ( 24 / 28 )89.13107142857140.93018742856593795.8205504518419
Winsorized Mean ( 25 / 28 )89.36619047619050.89492378455990699.858995836319
Winsorized Mean ( 26 / 28 )89.0876190476190.799971378200123111.363508089576
Winsorized Mean ( 27 / 28 )88.93333333333330.699444237481687127.148568202568
Winsorized Mean ( 28 / 28 )88.84666666666670.669175414463383132.770368944163
Trimmed Mean ( 1 / 28 )90.86402439024391.6719123218028954.3473621225912
Trimmed Mean ( 2 / 28 )90.6931.6348521049511855.4747427766309
Trimmed Mean ( 3 / 28 )90.54551282051281.6015974339933156.5345016785854
Trimmed Mean ( 4 / 28 )90.42342105263161.5771120459103457.3348109838559
Trimmed Mean ( 5 / 28 )90.30310810810811.5551384643514258.0675677299061
Trimmed Mean ( 6 / 28 )90.18430555555561.531951393306958.8689079494107
Trimmed Mean ( 7 / 28 )90.05857142857141.5041810643525359.8721613792799
Trimmed Mean ( 8 / 28 )89.93338235294121.473320439422861.0412914573929
Trimmed Mean ( 9 / 28 )89.80939393939391.443821122891862.2025765626124
Trimmed Mean ( 10 / 28 )89.6906251.4135334201605363.451365012519
Trimmed Mean ( 11 / 28 )89.581.381210047434864.856174603109
Trimmed Mean ( 12 / 28 )89.48733333333331.3492051827781466.3259632230809
Trimmed Mean ( 13 / 28 )89.38758620689661.3099792720901368.2358783160549
Trimmed Mean ( 14 / 28 )89.29178571428571.2674364941477770.4506980243819
Trimmed Mean ( 15 / 28 )89.21666666666671.223968696931972.8912977025509
Trimmed Mean ( 16 / 28 )89.16576923076921.1874506053441875.0900869724383
Trimmed Mean ( 17 / 28 )89.14881.1572689751377377.0337768619351
Trimmed Mean ( 18 / 28 )89.13208333333331.1249790367760579.2299948884083
Trimmed Mean ( 19 / 28 )89.11391304347831.0832592830103582.264619783209
Trimmed Mean ( 20 / 28 )89.08886363636361.047352810020885.0609868842519
Trimmed Mean ( 21 / 28 )89.07214285714291.0089883237011288.2786656345172
Trimmed Mean ( 22 / 28 )89.065250.9722347365800291.608792248362
Trimmed Mean ( 23 / 28 )89.05973684210530.93795118014532394.9513564536554
Trimmed Mean ( 24 / 28 )89.05250.90343606646540198.5708931772102
Trimmed Mean ( 25 / 28 )89.04441176470590.854827769413947104.166494059678
Trimmed Mean ( 26 / 28 )89.0106250.796247871509284111.787582968707
Trimmed Mean ( 27 / 28 )89.00233333333330.743941921372548119.636131230684
Trimmed Mean ( 28 / 28 )89.010.70240516503868126.721733310572
Median88.78
Midrange98.145
Midmean - Weighted Average at Xnp88.7855813953489
Midmean - Weighted Average at X(n+1)p89.0721428571429
Midmean - Empirical Distribution Function88.7855813953489
Midmean - Empirical Distribution Function - Averaging89.0721428571429
Midmean - Empirical Distribution Function - Interpolation89.0721428571429
Midmean - Closest Observation88.7855813953489
Midmean - True Basic - Statistics Graphics Toolkit89.0721428571429
Midmean - MS Excel (old versions)89.0888636363637
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 91.037380952381 & 1.70690889736635 & 53.3346455061811 \tabularnewline
Geometric Mean & 89.7557864093807 &  &  \tabularnewline
Harmonic Mean & 88.5283253891804 &  &  \tabularnewline
Quadratic Mean & 92.3559872630537 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 91.0269047619048 & 1.70367751279111 & 53.4296567739378 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 90.9669047619048 & 1.68747742575318 & 53.9070350652561 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 90.8769047619048 & 1.65424895796318 & 54.9354462787743 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 90.847380952381 & 1.63379119519845 & 55.6052580154506 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 90.8122619047619 & 1.62339114364192 & 55.9398529802455 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 90.8129761904762 & 1.6232908552679 & 55.9437490180951 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 90.7679761904762 & 1.61339878667933 & 56.2588598304906 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 90.7127380952381 & 1.57991386969745 & 57.4162553004293 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 90.6238095238095 & 1.55507632921823 & 58.2761166259718 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 90.5071428571429 & 1.53391271797808 & 59.0041022519486 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 90.3080952380952 & 1.49804421623205 & 60.2839984691789 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 90.3138095238095 & 1.49724613247246 & 60.3199484474013 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 90.2178571428571 & 1.46878037141171 & 61.4236538687843 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 89.9678571428571 & 1.42446835682019 & 63.1589018542263 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 89.6892857142857 & 1.33838867491616 & 67.0128845194419 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 89.3273809523809 & 1.25997620982021 & 70.8960853833323 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 89.3111904761905 & 1.22848600557162 & 72.700209909704 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 89.3111904761905 & 1.22848600557162 & 72.700209909704 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 89.3632142857143 & 1.14509788782936 & 78.0398036146157 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 89.2560714285714 & 1.10541960187493 & 80.7440643147471 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 89.1410714285714 & 1.0441744800302 & 85.3699004652877 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 89.1201190476191 & 0.980478188597084 & 90.8945452168972 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 89.1310714285714 & 0.930187428565937 & 95.8205504518419 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 89.1310714285714 & 0.930187428565937 & 95.8205504518419 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 89.3661904761905 & 0.894923784559906 & 99.858995836319 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 89.087619047619 & 0.799971378200123 & 111.363508089576 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 88.9333333333333 & 0.699444237481687 & 127.148568202568 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 88.8466666666667 & 0.669175414463383 & 132.770368944163 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 90.8640243902439 & 1.67191232180289 & 54.3473621225912 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 90.693 & 1.63485210495118 & 55.4747427766309 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 90.5455128205128 & 1.60159743399331 & 56.5345016785854 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 90.4234210526316 & 1.57711204591034 & 57.3348109838559 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 90.3031081081081 & 1.55513846435142 & 58.0675677299061 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 90.1843055555556 & 1.5319513933069 & 58.8689079494107 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 90.0585714285714 & 1.50418106435253 & 59.8721613792799 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 89.9333823529412 & 1.4733204394228 & 61.0412914573929 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 89.8093939393939 & 1.4438211228918 & 62.2025765626124 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 89.690625 & 1.41353342016053 & 63.451365012519 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 89.58 & 1.3812100474348 & 64.856174603109 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 89.4873333333333 & 1.34920518277814 & 66.3259632230809 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 89.3875862068966 & 1.30997927209013 & 68.2358783160549 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 89.2917857142857 & 1.26743649414777 & 70.4506980243819 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 89.2166666666667 & 1.2239686969319 & 72.8912977025509 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 89.1657692307692 & 1.18745060534418 & 75.0900869724383 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 89.1488 & 1.15726897513773 & 77.0337768619351 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 89.1320833333333 & 1.12497903677605 & 79.2299948884083 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 89.1139130434783 & 1.08325928301035 & 82.264619783209 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 89.0888636363636 & 1.0473528100208 & 85.0609868842519 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 89.0721428571429 & 1.00898832370112 & 88.2786656345172 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 89.06525 & 0.97223473658002 & 91.608792248362 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 89.0597368421053 & 0.937951180145323 & 94.9513564536554 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 89.0525 & 0.903436066465401 & 98.5708931772102 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 89.0444117647059 & 0.854827769413947 & 104.166494059678 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 89.010625 & 0.796247871509284 & 111.787582968707 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 89.0023333333333 & 0.743941921372548 & 119.636131230684 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 89.01 & 0.70240516503868 & 126.721733310572 \tabularnewline
Median & 88.78 &  &  \tabularnewline
Midrange & 98.145 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 88.7855813953489 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 89.0721428571429 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 88.7855813953489 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 89.0721428571429 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 89.0721428571429 &  &  \tabularnewline
Midmean - Closest Observation & 88.7855813953489 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 89.0721428571429 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 89.0888636363637 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=214982&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]91.037380952381[/C][C]1.70690889736635[/C][C]53.3346455061811[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]89.7557864093807[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]88.5283253891804[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]92.3559872630537[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]91.0269047619048[/C][C]1.70367751279111[/C][C]53.4296567739378[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]90.9669047619048[/C][C]1.68747742575318[/C][C]53.9070350652561[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]90.8769047619048[/C][C]1.65424895796318[/C][C]54.9354462787743[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]90.847380952381[/C][C]1.63379119519845[/C][C]55.6052580154506[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]90.8122619047619[/C][C]1.62339114364192[/C][C]55.9398529802455[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]90.8129761904762[/C][C]1.6232908552679[/C][C]55.9437490180951[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]90.7679761904762[/C][C]1.61339878667933[/C][C]56.2588598304906[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]90.7127380952381[/C][C]1.57991386969745[/C][C]57.4162553004293[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]90.6238095238095[/C][C]1.55507632921823[/C][C]58.2761166259718[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]90.5071428571429[/C][C]1.53391271797808[/C][C]59.0041022519486[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]90.3080952380952[/C][C]1.49804421623205[/C][C]60.2839984691789[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]90.3138095238095[/C][C]1.49724613247246[/C][C]60.3199484474013[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]90.2178571428571[/C][C]1.46878037141171[/C][C]61.4236538687843[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]89.9678571428571[/C][C]1.42446835682019[/C][C]63.1589018542263[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]89.6892857142857[/C][C]1.33838867491616[/C][C]67.0128845194419[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]89.3273809523809[/C][C]1.25997620982021[/C][C]70.8960853833323[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]89.3111904761905[/C][C]1.22848600557162[/C][C]72.700209909704[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]89.3111904761905[/C][C]1.22848600557162[/C][C]72.700209909704[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]89.3632142857143[/C][C]1.14509788782936[/C][C]78.0398036146157[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]89.2560714285714[/C][C]1.10541960187493[/C][C]80.7440643147471[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]89.1410714285714[/C][C]1.0441744800302[/C][C]85.3699004652877[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]89.1201190476191[/C][C]0.980478188597084[/C][C]90.8945452168972[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]89.1310714285714[/C][C]0.930187428565937[/C][C]95.8205504518419[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]89.1310714285714[/C][C]0.930187428565937[/C][C]95.8205504518419[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]89.3661904761905[/C][C]0.894923784559906[/C][C]99.858995836319[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]89.087619047619[/C][C]0.799971378200123[/C][C]111.363508089576[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]88.9333333333333[/C][C]0.699444237481687[/C][C]127.148568202568[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]88.8466666666667[/C][C]0.669175414463383[/C][C]132.770368944163[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]90.8640243902439[/C][C]1.67191232180289[/C][C]54.3473621225912[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]90.693[/C][C]1.63485210495118[/C][C]55.4747427766309[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]90.5455128205128[/C][C]1.60159743399331[/C][C]56.5345016785854[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]90.4234210526316[/C][C]1.57711204591034[/C][C]57.3348109838559[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]90.3031081081081[/C][C]1.55513846435142[/C][C]58.0675677299061[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]90.1843055555556[/C][C]1.5319513933069[/C][C]58.8689079494107[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]90.0585714285714[/C][C]1.50418106435253[/C][C]59.8721613792799[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]89.9333823529412[/C][C]1.4733204394228[/C][C]61.0412914573929[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]89.8093939393939[/C][C]1.4438211228918[/C][C]62.2025765626124[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]89.690625[/C][C]1.41353342016053[/C][C]63.451365012519[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]89.58[/C][C]1.3812100474348[/C][C]64.856174603109[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]89.4873333333333[/C][C]1.34920518277814[/C][C]66.3259632230809[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]89.3875862068966[/C][C]1.30997927209013[/C][C]68.2358783160549[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]89.2917857142857[/C][C]1.26743649414777[/C][C]70.4506980243819[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]89.2166666666667[/C][C]1.2239686969319[/C][C]72.8912977025509[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]89.1657692307692[/C][C]1.18745060534418[/C][C]75.0900869724383[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]89.1488[/C][C]1.15726897513773[/C][C]77.0337768619351[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]89.1320833333333[/C][C]1.12497903677605[/C][C]79.2299948884083[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]89.1139130434783[/C][C]1.08325928301035[/C][C]82.264619783209[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]89.0888636363636[/C][C]1.0473528100208[/C][C]85.0609868842519[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]89.0721428571429[/C][C]1.00898832370112[/C][C]88.2786656345172[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]89.06525[/C][C]0.97223473658002[/C][C]91.608792248362[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]89.0597368421053[/C][C]0.937951180145323[/C][C]94.9513564536554[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]89.0525[/C][C]0.903436066465401[/C][C]98.5708931772102[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]89.0444117647059[/C][C]0.854827769413947[/C][C]104.166494059678[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]89.010625[/C][C]0.796247871509284[/C][C]111.787582968707[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]89.0023333333333[/C][C]0.743941921372548[/C][C]119.636131230684[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]89.01[/C][C]0.70240516503868[/C][C]126.721733310572[/C][/ROW]
[ROW][C]Median[/C][C]88.78[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]98.145[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]88.7855813953489[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]89.0721428571429[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]88.7855813953489[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]89.0721428571429[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]89.0721428571429[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]88.7855813953489[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]89.0721428571429[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]89.0888636363637[/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=214982&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=214982&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean91.0373809523811.7069088973663553.3346455061811
Geometric Mean89.7557864093807
Harmonic Mean88.5283253891804
Quadratic Mean92.3559872630537
Winsorized Mean ( 1 / 28 )91.02690476190481.7036775127911153.4296567739378
Winsorized Mean ( 2 / 28 )90.96690476190481.6874774257531853.9070350652561
Winsorized Mean ( 3 / 28 )90.87690476190481.6542489579631854.9354462787743
Winsorized Mean ( 4 / 28 )90.8473809523811.6337911951984555.6052580154506
Winsorized Mean ( 5 / 28 )90.81226190476191.6233911436419255.9398529802455
Winsorized Mean ( 6 / 28 )90.81297619047621.623290855267955.9437490180951
Winsorized Mean ( 7 / 28 )90.76797619047621.6133987866793356.2588598304906
Winsorized Mean ( 8 / 28 )90.71273809523811.5799138696974557.4162553004293
Winsorized Mean ( 9 / 28 )90.62380952380951.5550763292182358.2761166259718
Winsorized Mean ( 10 / 28 )90.50714285714291.5339127179780859.0041022519486
Winsorized Mean ( 11 / 28 )90.30809523809521.4980442162320560.2839984691789
Winsorized Mean ( 12 / 28 )90.31380952380951.4972461324724660.3199484474013
Winsorized Mean ( 13 / 28 )90.21785714285711.4687803714117161.4236538687843
Winsorized Mean ( 14 / 28 )89.96785714285711.4244683568201963.1589018542263
Winsorized Mean ( 15 / 28 )89.68928571428571.3383886749161667.0128845194419
Winsorized Mean ( 16 / 28 )89.32738095238091.2599762098202170.8960853833323
Winsorized Mean ( 17 / 28 )89.31119047619051.2284860055716272.700209909704
Winsorized Mean ( 18 / 28 )89.31119047619051.2284860055716272.700209909704
Winsorized Mean ( 19 / 28 )89.36321428571431.1450978878293678.0398036146157
Winsorized Mean ( 20 / 28 )89.25607142857141.1054196018749380.7440643147471
Winsorized Mean ( 21 / 28 )89.14107142857141.044174480030285.3699004652877
Winsorized Mean ( 22 / 28 )89.12011904761910.98047818859708490.8945452168972
Winsorized Mean ( 23 / 28 )89.13107142857140.93018742856593795.8205504518419
Winsorized Mean ( 24 / 28 )89.13107142857140.93018742856593795.8205504518419
Winsorized Mean ( 25 / 28 )89.36619047619050.89492378455990699.858995836319
Winsorized Mean ( 26 / 28 )89.0876190476190.799971378200123111.363508089576
Winsorized Mean ( 27 / 28 )88.93333333333330.699444237481687127.148568202568
Winsorized Mean ( 28 / 28 )88.84666666666670.669175414463383132.770368944163
Trimmed Mean ( 1 / 28 )90.86402439024391.6719123218028954.3473621225912
Trimmed Mean ( 2 / 28 )90.6931.6348521049511855.4747427766309
Trimmed Mean ( 3 / 28 )90.54551282051281.6015974339933156.5345016785854
Trimmed Mean ( 4 / 28 )90.42342105263161.5771120459103457.3348109838559
Trimmed Mean ( 5 / 28 )90.30310810810811.5551384643514258.0675677299061
Trimmed Mean ( 6 / 28 )90.18430555555561.531951393306958.8689079494107
Trimmed Mean ( 7 / 28 )90.05857142857141.5041810643525359.8721613792799
Trimmed Mean ( 8 / 28 )89.93338235294121.473320439422861.0412914573929
Trimmed Mean ( 9 / 28 )89.80939393939391.443821122891862.2025765626124
Trimmed Mean ( 10 / 28 )89.6906251.4135334201605363.451365012519
Trimmed Mean ( 11 / 28 )89.581.381210047434864.856174603109
Trimmed Mean ( 12 / 28 )89.48733333333331.3492051827781466.3259632230809
Trimmed Mean ( 13 / 28 )89.38758620689661.3099792720901368.2358783160549
Trimmed Mean ( 14 / 28 )89.29178571428571.2674364941477770.4506980243819
Trimmed Mean ( 15 / 28 )89.21666666666671.223968696931972.8912977025509
Trimmed Mean ( 16 / 28 )89.16576923076921.1874506053441875.0900869724383
Trimmed Mean ( 17 / 28 )89.14881.1572689751377377.0337768619351
Trimmed Mean ( 18 / 28 )89.13208333333331.1249790367760579.2299948884083
Trimmed Mean ( 19 / 28 )89.11391304347831.0832592830103582.264619783209
Trimmed Mean ( 20 / 28 )89.08886363636361.047352810020885.0609868842519
Trimmed Mean ( 21 / 28 )89.07214285714291.0089883237011288.2786656345172
Trimmed Mean ( 22 / 28 )89.065250.9722347365800291.608792248362
Trimmed Mean ( 23 / 28 )89.05973684210530.93795118014532394.9513564536554
Trimmed Mean ( 24 / 28 )89.05250.90343606646540198.5708931772102
Trimmed Mean ( 25 / 28 )89.04441176470590.854827769413947104.166494059678
Trimmed Mean ( 26 / 28 )89.0106250.796247871509284111.787582968707
Trimmed Mean ( 27 / 28 )89.00233333333330.743941921372548119.636131230684
Trimmed Mean ( 28 / 28 )89.010.70240516503868126.721733310572
Median88.78
Midrange98.145
Midmean - Weighted Average at Xnp88.7855813953489
Midmean - Weighted Average at X(n+1)p89.0721428571429
Midmean - Empirical Distribution Function88.7855813953489
Midmean - Empirical Distribution Function - Averaging89.0721428571429
Midmean - Empirical Distribution Function - Interpolation89.0721428571429
Midmean - Closest Observation88.7855813953489
Midmean - True Basic - Statistics Graphics Toolkit89.0721428571429
Midmean - MS Excel (old versions)89.0888636363637
Number of observations84


Figures (Output of Computation)

Input Parameters & R Code

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')