Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*Unverified author*

R Software Module

rwasp_centraltendency.wasp

Title produced by software

Central Tendency

Date of computation

Thu, 10 Oct 2013 12:54:54 -0400

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Oct/10/t13814241154l38yl56jpd695w.htm/, Retrieved Thu, 02 May 2024 23:29:03 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=214657, Retrieved Thu, 02 May 2024 23:29:03 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Central Tendency] [] [2013-10-10 16:54:54] [da6056b86d6cc6ac74ca244744435ec9] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'George Udny Yule' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=214657&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=214657&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=214657&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'George Udny Yule' @ yule.wessa.net

Central Tendency - Ungrouped Data
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	89.7889285714286	1.15971189096583	77.4234784267416
Geometric Mean	89.1544467568236
Harmonic Mean	88.509829610566
Quadratic Mean	90.4084123443115
Winsorized Mean ( 1 / 28 )	89.8047619047619	1.15474061528482	77.7705059612987
Winsorized Mean ( 2 / 28 )	89.8064285714286	1.14675907965517	78.3132483227717
Winsorized Mean ( 3 / 28 )	89.8107142857143	1.14583549358642	78.3801119693111
Winsorized Mean ( 4 / 28 )	89.8088095238095	1.14292932724083	78.5777452579843
Winsorized Mean ( 5 / 28 )	89.8689285714286	1.13146231543625	79.4272397280669
Winsorized Mean ( 6 / 28 )	89.8989285714286	1.11664522484604	80.508049084098
Winsorized Mean ( 7 / 28 )	89.8964285714286	1.11599143373673	80.5529736643444
Winsorized Mean ( 8 / 28 )	89.9002380952381	1.09889527502796	81.8096502352786
Winsorized Mean ( 9 / 28 )	89.894880952381	1.08833056127964	82.5988758844412
Winsorized Mean ( 10 / 28 )	89.894880952381	1.07283243552366	83.7920983517823
Winsorized Mean ( 11 / 28 )	90.0075	1.05169174801634	85.5835373528113
Winsorized Mean ( 12 / 28 )	89.9575	1.04318022511508	86.233900752937
Winsorized Mean ( 13 / 28 )	89.9652380952381	1.04104310850385	86.4183599702544
Winsorized Mean ( 14 / 28 )	90.1152380952381	1.00672997101686	89.5128194149377
Winsorized Mean ( 15 / 28 )	90.1063095238095	0.997620674565334	90.3212130833887
Winsorized Mean ( 16 / 28 )	90.1101190476191	0.994832034679495	90.5782241689169
Winsorized Mean ( 17 / 28 )	90.2639285714286	0.940337444739222	95.9909967176314
Winsorized Mean ( 18 / 28 )	90.1332142857143	0.884927222628637	101.85381574993
Winsorized Mean ( 19 / 28 )	90.5403571428571	0.82456964638135	109.803165251348
Winsorized Mean ( 20 / 28 )	90.5355952380952	0.818804250237056	110.57049986231
Winsorized Mean ( 21 / 28 )	90.6855952380952	0.785037599020457	115.517518334472
Winsorized Mean ( 22 / 28 )	90.7091666666667	0.778649039114529	116.49557388502
Winsorized Mean ( 23 / 28 )	90.7173809523809	0.777626692982419	116.659293940199
Winsorized Mean ( 24 / 28 )	90.8145238095238	0.752972430763961	120.608033042304
Winsorized Mean ( 25 / 28 )	90.9692857142857	0.733569573883685	124.009076920507
Winsorized Mean ( 26 / 28 )	90.8795238095238	0.71791797732581	126.587614016915
Winsorized Mean ( 27 / 28 )	90.6191666666667	0.628076049574074	144.28056399877
Winsorized Mean ( 28 / 28 )	90.6025	0.620761240216507	145.95386137253
Trimmed Mean ( 1 / 28 )	89.840243902439	1.14379899939941	78.5454821604256
Trimmed Mean ( 2 / 28 )	89.8775	1.13085874589383	79.4772117440372
Trimmed Mean ( 3 / 28 )	89.9157692307692	1.12036253288951	80.2559587554835
Trimmed Mean ( 4 / 28 )	89.9544736842105	1.10818694025519	81.1726527507135
Trimmed Mean ( 5 / 28 )	89.9958108108108	1.09461902891629	82.2165597650079
Trimmed Mean ( 6 / 28 )	90.0254166666667	1.08172487920898	83.2239494505278
Trimmed Mean ( 7 / 28 )	90.0507142857143	1.0699630480922	84.162452569067
Trimmed Mean ( 8 / 28 )	90.0779411764706	1.05579843748608	85.3173654916099
Trimmed Mean ( 9 / 28 )	90.1062121212121	1.04230620587886	86.4488876809818
Trimmed Mean ( 10 / 28 )	90.13703125	1.02794236701536	87.6868530204801
Trimmed Mean ( 11 / 28 )	90.1698387096774	1.01333098618827	88.9835995727896
Trimmed Mean ( 12 / 28 )	90.1905	0.99933436674302	90.2505737833718
Trimmed Mean ( 13 / 28 )	90.2186206896552	0.983409210365559	91.7406708608297
Trimmed Mean ( 14 / 28 )	90.2478571428571	0.96386898643206	93.6308340793559
Trimmed Mean ( 15 / 28 )	90.2625925925926	0.945953986068336	95.4196440016608
Trimmed Mean ( 16 / 28 )	90.2794230769231	0.92497431432527	97.6020865431038
Trimmed Mean ( 17 / 28 )	90.2972	0.898838118044056	100.459913957025
Trimmed Mean ( 18 / 28 )	90.300625	0.876497523302546	103.024392652882
Trimmed Mean ( 19 / 28 )	90.3176086956522	0.85859987052186	105.191733421479
Trimmed Mean ( 20 / 28 )	90.2952272727273	0.846760990052362	106.636026379939
Trimmed Mean ( 21 / 28 )	90.2711904761905	0.831444330712094	108.571538877266
Trimmed Mean ( 22 / 28 )	90.22975	0.817180384277987	110.41595189503
Trimmed Mean ( 23 / 28 )	90.1815789473684	0.798286173345227	112.96898525683
Trimmed Mean ( 24 / 28 )	90.1272222222222	0.771766640763524	116.780406747119
Trimmed Mean ( 25 / 28 )	90.0564705882353	0.740494473031732	121.616668142743
Trimmed Mean ( 26 / 28 )	89.960625	0.700426128576556	128.43699189638
Trimmed Mean ( 27 / 28 )	89.8616666666667	0.64697369474023	138.895394661676
Trimmed Mean ( 28 / 28 )	89.7775	0.601805841749664	149.180173690214
Median	89.255
Midrange	87.685
Midmean - Weighted Average at Xnp	90.0718604651163
Midmean - Weighted Average at X(n+1)p	90.2711904761905
Midmean - Empirical Distribution Function	90.0718604651163
Midmean - Empirical Distribution Function - Averaging	90.2711904761905
Midmean - Empirical Distribution Function - Interpolation	90.2711904761905
Midmean - Closest Observation	90.0718604651163
Midmean - True Basic - Statistics Graphics Toolkit	90.2711904761905
Midmean - MS Excel (old versions)	90.2952272727273
Number of observations	84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 89.7889285714286 & 1.15971189096583 & 77.4234784267416 \tabularnewline
Geometric Mean & 89.1544467568236 &  &  \tabularnewline
Harmonic Mean & 88.509829610566 &  &  \tabularnewline
Quadratic Mean & 90.4084123443115 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 89.8047619047619 & 1.15474061528482 & 77.7705059612987 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 89.8064285714286 & 1.14675907965517 & 78.3132483227717 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 89.8107142857143 & 1.14583549358642 & 78.3801119693111 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 89.8088095238095 & 1.14292932724083 & 78.5777452579843 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 89.8689285714286 & 1.13146231543625 & 79.4272397280669 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 89.8989285714286 & 1.11664522484604 & 80.508049084098 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 89.8964285714286 & 1.11599143373673 & 80.5529736643444 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 89.9002380952381 & 1.09889527502796 & 81.8096502352786 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 89.894880952381 & 1.08833056127964 & 82.5988758844412 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 89.894880952381 & 1.07283243552366 & 83.7920983517823 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 90.0075 & 1.05169174801634 & 85.5835373528113 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 89.9575 & 1.04318022511508 & 86.233900752937 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 89.9652380952381 & 1.04104310850385 & 86.4183599702544 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 90.1152380952381 & 1.00672997101686 & 89.5128194149377 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 90.1063095238095 & 0.997620674565334 & 90.3212130833887 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 90.1101190476191 & 0.994832034679495 & 90.5782241689169 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 90.2639285714286 & 0.940337444739222 & 95.9909967176314 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 90.1332142857143 & 0.884927222628637 & 101.85381574993 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 90.5403571428571 & 0.82456964638135 & 109.803165251348 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 90.5355952380952 & 0.818804250237056 & 110.57049986231 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 90.6855952380952 & 0.785037599020457 & 115.517518334472 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 90.7091666666667 & 0.778649039114529 & 116.49557388502 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 90.7173809523809 & 0.777626692982419 & 116.659293940199 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 90.8145238095238 & 0.752972430763961 & 120.608033042304 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 90.9692857142857 & 0.733569573883685 & 124.009076920507 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 90.8795238095238 & 0.71791797732581 & 126.587614016915 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 90.6191666666667 & 0.628076049574074 & 144.28056399877 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 90.6025 & 0.620761240216507 & 145.95386137253 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 89.840243902439 & 1.14379899939941 & 78.5454821604256 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 89.8775 & 1.13085874589383 & 79.4772117440372 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 89.9157692307692 & 1.12036253288951 & 80.2559587554835 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 89.9544736842105 & 1.10818694025519 & 81.1726527507135 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 89.9958108108108 & 1.09461902891629 & 82.2165597650079 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 90.0254166666667 & 1.08172487920898 & 83.2239494505278 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 90.0507142857143 & 1.0699630480922 & 84.162452569067 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 90.0779411764706 & 1.05579843748608 & 85.3173654916099 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 90.1062121212121 & 1.04230620587886 & 86.4488876809818 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 90.13703125 & 1.02794236701536 & 87.6868530204801 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 90.1698387096774 & 1.01333098618827 & 88.9835995727896 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 90.1905 & 0.99933436674302 & 90.2505737833718 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 90.2186206896552 & 0.983409210365559 & 91.7406708608297 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 90.2478571428571 & 0.96386898643206 & 93.6308340793559 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 90.2625925925926 & 0.945953986068336 & 95.4196440016608 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 90.2794230769231 & 0.92497431432527 & 97.6020865431038 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 90.2972 & 0.898838118044056 & 100.459913957025 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 90.300625 & 0.876497523302546 & 103.024392652882 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 90.3176086956522 & 0.85859987052186 & 105.191733421479 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 90.2952272727273 & 0.846760990052362 & 106.636026379939 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 90.2711904761905 & 0.831444330712094 & 108.571538877266 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 90.22975 & 0.817180384277987 & 110.41595189503 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 90.1815789473684 & 0.798286173345227 & 112.96898525683 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 90.1272222222222 & 0.771766640763524 & 116.780406747119 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 90.0564705882353 & 0.740494473031732 & 121.616668142743 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 89.960625 & 0.700426128576556 & 128.43699189638 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 89.8616666666667 & 0.64697369474023 & 138.895394661676 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 89.7775 & 0.601805841749664 & 149.180173690214 \tabularnewline
Median & 89.255 &  &  \tabularnewline
Midrange & 87.685 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 90.0718604651163 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 90.2711904761905 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 90.0718604651163 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 90.2711904761905 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 90.2711904761905 &  &  \tabularnewline
Midmean - Closest Observation & 90.0718604651163 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 90.2711904761905 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 90.2952272727273 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=214657&T=1

[TABLE]
[ROW][C]Central Tendency - Ungrouped Data[/C][/ROW]
[ROW][C]Measure[/C][C]Value[/C][C]S.E.[/C][C]Value/S.E.[/C][/ROW]
[ROW][C]Arithmetic Mean[/C][C]89.7889285714286[/C][C]1.15971189096583[/C][C]77.4234784267416[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]89.1544467568236[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]88.509829610566[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]90.4084123443115[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]89.8047619047619[/C][C]1.15474061528482[/C][C]77.7705059612987[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]89.8064285714286[/C][C]1.14675907965517[/C][C]78.3132483227717[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]89.8107142857143[/C][C]1.14583549358642[/C][C]78.3801119693111[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]89.8088095238095[/C][C]1.14292932724083[/C][C]78.5777452579843[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]89.8689285714286[/C][C]1.13146231543625[/C][C]79.4272397280669[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]89.8989285714286[/C][C]1.11664522484604[/C][C]80.508049084098[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]89.8964285714286[/C][C]1.11599143373673[/C][C]80.5529736643444[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]89.9002380952381[/C][C]1.09889527502796[/C][C]81.8096502352786[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]89.894880952381[/C][C]1.08833056127964[/C][C]82.5988758844412[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]89.894880952381[/C][C]1.07283243552366[/C][C]83.7920983517823[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]90.0075[/C][C]1.05169174801634[/C][C]85.5835373528113[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]89.9575[/C][C]1.04318022511508[/C][C]86.233900752937[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]89.9652380952381[/C][C]1.04104310850385[/C][C]86.4183599702544[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]90.1152380952381[/C][C]1.00672997101686[/C][C]89.5128194149377[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]90.1063095238095[/C][C]0.997620674565334[/C][C]90.3212130833887[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]90.1101190476191[/C][C]0.994832034679495[/C][C]90.5782241689169[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]90.2639285714286[/C][C]0.940337444739222[/C][C]95.9909967176314[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]90.1332142857143[/C][C]0.884927222628637[/C][C]101.85381574993[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]90.5403571428571[/C][C]0.82456964638135[/C][C]109.803165251348[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]90.5355952380952[/C][C]0.818804250237056[/C][C]110.57049986231[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]90.6855952380952[/C][C]0.785037599020457[/C][C]115.517518334472[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]90.7091666666667[/C][C]0.778649039114529[/C][C]116.49557388502[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]90.7173809523809[/C][C]0.777626692982419[/C][C]116.659293940199[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]90.8145238095238[/C][C]0.752972430763961[/C][C]120.608033042304[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]90.9692857142857[/C][C]0.733569573883685[/C][C]124.009076920507[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]90.8795238095238[/C][C]0.71791797732581[/C][C]126.587614016915[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]90.6191666666667[/C][C]0.628076049574074[/C][C]144.28056399877[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]90.6025[/C][C]0.620761240216507[/C][C]145.95386137253[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]89.840243902439[/C][C]1.14379899939941[/C][C]78.5454821604256[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]89.8775[/C][C]1.13085874589383[/C][C]79.4772117440372[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]89.9157692307692[/C][C]1.12036253288951[/C][C]80.2559587554835[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]89.9544736842105[/C][C]1.10818694025519[/C][C]81.1726527507135[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]89.9958108108108[/C][C]1.09461902891629[/C][C]82.2165597650079[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]90.0254166666667[/C][C]1.08172487920898[/C][C]83.2239494505278[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]90.0507142857143[/C][C]1.0699630480922[/C][C]84.162452569067[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]90.0779411764706[/C][C]1.05579843748608[/C][C]85.3173654916099[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]90.1062121212121[/C][C]1.04230620587886[/C][C]86.4488876809818[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]90.13703125[/C][C]1.02794236701536[/C][C]87.6868530204801[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]90.1698387096774[/C][C]1.01333098618827[/C][C]88.9835995727896[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]90.1905[/C][C]0.99933436674302[/C][C]90.2505737833718[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]90.2186206896552[/C][C]0.983409210365559[/C][C]91.7406708608297[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]90.2478571428571[/C][C]0.96386898643206[/C][C]93.6308340793559[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]90.2625925925926[/C][C]0.945953986068336[/C][C]95.4196440016608[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]90.2794230769231[/C][C]0.92497431432527[/C][C]97.6020865431038[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]90.2972[/C][C]0.898838118044056[/C][C]100.459913957025[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]90.300625[/C][C]0.876497523302546[/C][C]103.024392652882[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]90.3176086956522[/C][C]0.85859987052186[/C][C]105.191733421479[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]90.2952272727273[/C][C]0.846760990052362[/C][C]106.636026379939[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]90.2711904761905[/C][C]0.831444330712094[/C][C]108.571538877266[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]90.22975[/C][C]0.817180384277987[/C][C]110.41595189503[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]90.1815789473684[/C][C]0.798286173345227[/C][C]112.96898525683[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]90.1272222222222[/C][C]0.771766640763524[/C][C]116.780406747119[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]90.0564705882353[/C][C]0.740494473031732[/C][C]121.616668142743[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]89.960625[/C][C]0.700426128576556[/C][C]128.43699189638[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]89.8616666666667[/C][C]0.64697369474023[/C][C]138.895394661676[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]89.7775[/C][C]0.601805841749664[/C][C]149.180173690214[/C][/ROW]
[ROW][C]Median[/C][C]89.255[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]87.685[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]90.0718604651163[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]90.2711904761905[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]90.0718604651163[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]90.2711904761905[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]90.2711904761905[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]90.0718604651163[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]90.2711904761905[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]90.2952272727273[/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=214657&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=214657&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
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	89.7889285714286	1.15971189096583	77.4234784267416
Geometric Mean	89.1544467568236
Harmonic Mean	88.509829610566
Quadratic Mean	90.4084123443115
Winsorized Mean ( 1 / 28 )	89.8047619047619	1.15474061528482	77.7705059612987
Winsorized Mean ( 2 / 28 )	89.8064285714286	1.14675907965517	78.3132483227717
Winsorized Mean ( 3 / 28 )	89.8107142857143	1.14583549358642	78.3801119693111
Winsorized Mean ( 4 / 28 )	89.8088095238095	1.14292932724083	78.5777452579843
Winsorized Mean ( 5 / 28 )	89.8689285714286	1.13146231543625	79.4272397280669
Winsorized Mean ( 6 / 28 )	89.8989285714286	1.11664522484604	80.508049084098
Winsorized Mean ( 7 / 28 )	89.8964285714286	1.11599143373673	80.5529736643444
Winsorized Mean ( 8 / 28 )	89.9002380952381	1.09889527502796	81.8096502352786
Winsorized Mean ( 9 / 28 )	89.894880952381	1.08833056127964	82.5988758844412
Winsorized Mean ( 10 / 28 )	89.894880952381	1.07283243552366	83.7920983517823
Winsorized Mean ( 11 / 28 )	90.0075	1.05169174801634	85.5835373528113
Winsorized Mean ( 12 / 28 )	89.9575	1.04318022511508	86.233900752937
Winsorized Mean ( 13 / 28 )	89.9652380952381	1.04104310850385	86.4183599702544
Winsorized Mean ( 14 / 28 )	90.1152380952381	1.00672997101686	89.5128194149377
Winsorized Mean ( 15 / 28 )	90.1063095238095	0.997620674565334	90.3212130833887
Winsorized Mean ( 16 / 28 )	90.1101190476191	0.994832034679495	90.5782241689169
Winsorized Mean ( 17 / 28 )	90.2639285714286	0.940337444739222	95.9909967176314
Winsorized Mean ( 18 / 28 )	90.1332142857143	0.884927222628637	101.85381574993
Winsorized Mean ( 19 / 28 )	90.5403571428571	0.82456964638135	109.803165251348
Winsorized Mean ( 20 / 28 )	90.5355952380952	0.818804250237056	110.57049986231
Winsorized Mean ( 21 / 28 )	90.6855952380952	0.785037599020457	115.517518334472
Winsorized Mean ( 22 / 28 )	90.7091666666667	0.778649039114529	116.49557388502
Winsorized Mean ( 23 / 28 )	90.7173809523809	0.777626692982419	116.659293940199
Winsorized Mean ( 24 / 28 )	90.8145238095238	0.752972430763961	120.608033042304
Winsorized Mean ( 25 / 28 )	90.9692857142857	0.733569573883685	124.009076920507
Winsorized Mean ( 26 / 28 )	90.8795238095238	0.71791797732581	126.587614016915
Winsorized Mean ( 27 / 28 )	90.6191666666667	0.628076049574074	144.28056399877
Winsorized Mean ( 28 / 28 )	90.6025	0.620761240216507	145.95386137253
Trimmed Mean ( 1 / 28 )	89.840243902439	1.14379899939941	78.5454821604256
Trimmed Mean ( 2 / 28 )	89.8775	1.13085874589383	79.4772117440372
Trimmed Mean ( 3 / 28 )	89.9157692307692	1.12036253288951	80.2559587554835
Trimmed Mean ( 4 / 28 )	89.9544736842105	1.10818694025519	81.1726527507135
Trimmed Mean ( 5 / 28 )	89.9958108108108	1.09461902891629	82.2165597650079
Trimmed Mean ( 6 / 28 )	90.0254166666667	1.08172487920898	83.2239494505278
Trimmed Mean ( 7 / 28 )	90.0507142857143	1.0699630480922	84.162452569067
Trimmed Mean ( 8 / 28 )	90.0779411764706	1.05579843748608	85.3173654916099
Trimmed Mean ( 9 / 28 )	90.1062121212121	1.04230620587886	86.4488876809818
Trimmed Mean ( 10 / 28 )	90.13703125	1.02794236701536	87.6868530204801
Trimmed Mean ( 11 / 28 )	90.1698387096774	1.01333098618827	88.9835995727896
Trimmed Mean ( 12 / 28 )	90.1905	0.99933436674302	90.2505737833718
Trimmed Mean ( 13 / 28 )	90.2186206896552	0.983409210365559	91.7406708608297
Trimmed Mean ( 14 / 28 )	90.2478571428571	0.96386898643206	93.6308340793559
Trimmed Mean ( 15 / 28 )	90.2625925925926	0.945953986068336	95.4196440016608
Trimmed Mean ( 16 / 28 )	90.2794230769231	0.92497431432527	97.6020865431038
Trimmed Mean ( 17 / 28 )	90.2972	0.898838118044056	100.459913957025
Trimmed Mean ( 18 / 28 )	90.300625	0.876497523302546	103.024392652882
Trimmed Mean ( 19 / 28 )	90.3176086956522	0.85859987052186	105.191733421479
Trimmed Mean ( 20 / 28 )	90.2952272727273	0.846760990052362	106.636026379939
Trimmed Mean ( 21 / 28 )	90.2711904761905	0.831444330712094	108.571538877266
Trimmed Mean ( 22 / 28 )	90.22975	0.817180384277987	110.41595189503
Trimmed Mean ( 23 / 28 )	90.1815789473684	0.798286173345227	112.96898525683
Trimmed Mean ( 24 / 28 )	90.1272222222222	0.771766640763524	116.780406747119
Trimmed Mean ( 25 / 28 )	90.0564705882353	0.740494473031732	121.616668142743
Trimmed Mean ( 26 / 28 )	89.960625	0.700426128576556	128.43699189638
Trimmed Mean ( 27 / 28 )	89.8616666666667	0.64697369474023	138.895394661676
Trimmed Mean ( 28 / 28 )	89.7775	0.601805841749664	149.180173690214
Median	89.255
Midrange	87.685
Midmean - Weighted Average at Xnp	90.0718604651163
Midmean - Weighted Average at X(n+1)p	90.2711904761905
Midmean - Empirical Distribution Function	90.0718604651163
Midmean - Empirical Distribution Function - Averaging	90.2711904761905
Midmean - Empirical Distribution Function - Interpolation	90.2711904761905
Midmean - Closest Observation	90.0718604651163
Midmean - True Basic - Statistics Graphics Toolkit	90.2711904761905
Midmean - MS Excel (old versions)	90.2952272727273
Number of observations	84

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code