Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSun, 30 Nov 2008 03:42:08 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Nov/30/t1228041759t1vng5rw7ex9628.htm/, Retrieved Sun, 19 May 2024 08:00:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26421, Retrieved Sun, 19 May 2024 08:00:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact187
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [totale uitvoer be...] [2008-11-27 20:32:52] [1e1d8320a8a1170c475bf6e4ce119de6]
-   PD  [Univariate Data Series] [uitvoer van belgi...] [2008-11-27 20:39:12] [1e1d8320a8a1170c475bf6e4ce119de6]
- RMP       [Central Tendency] [uitvoer polen cen...] [2008-11-30 10:42:08] [fdd69703d301fae09456f660b2f52997] [Current]
Feedback Forum

Post a new message
Dataseries X:
156.3
151.5
159.1
166.9
160.5
162.8
178.9
148.5
184.1
197
186.8
139.2
162.7
187.5
235.8
219.4
212.4
220.2
197.5
185.6
232.4
223.8
219.4
191.4
210.4
212.6
274.4
256
227.6
261.7
237
234.9
310.6
274.2
288.1
242.5
271.7
282.2
317.4
280.3
322.6
328.2
280.7
288.8
347.9
360.1
348
275.7
332.6
340.8
390.5
351.2
377.4
413.5
366.9
364.8
388
429.8
423.6
326.4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26421&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26421&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26421&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean261.9810.251729577102325.5547123077792
Geometric Mean250.227671162488
Harmonic Mean238.864251207767
Quadratic Mean273.558586046938
Winsorized Mean ( 1 / 20 )262.03166666666710.193146997646625.7066504316249
Winsorized Mean ( 2 / 20 )261.79510.086291369357325.9555262100943
Winsorized Mean ( 3 / 20 )260.8859.7660549619472226.7134478575557
Winsorized Mean ( 4 / 20 )260.9059.6952397968030726.9106288723288
Winsorized Mean ( 5 / 20 )260.1383333333339.4837172655693427.4299967036940
Winsorized Mean ( 6 / 20 )259.3083333333339.2307908016039228.09167046536
Winsorized Mean ( 7 / 20 )259.0759.1806073630055828.2198104935819
Winsorized Mean ( 8 / 20 )258.9958.9633344232518128.8949388442029
Winsorized Mean ( 9 / 20 )259.468.408947413925830.8552292252793
Winsorized Mean ( 10 / 20 )259.7933333333338.1724239593279931.7890181207261
Winsorized Mean ( 11 / 20 )260.058.1261298214898232.001703850742
Winsorized Mean ( 12 / 20 )258.877.8327352698728233.0497573428399
Winsorized Mean ( 13 / 20 )257.2457.5000577869713534.2990690614238
Winsorized Mean ( 14 / 20 )257.1283333333337.1842448036830435.7905862564031
Winsorized Mean ( 15 / 20 )258.0783333333336.8950150221960237.4296984854337
Winsorized Mean ( 16 / 20 )257.1983333333336.7060848040601738.3529795474125
Winsorized Mean ( 17 / 20 )259.385.9293328099054743.7452253593664
Winsorized Mean ( 18 / 20 )257.945.510795363350346.8063107034308
Winsorized Mean ( 19 / 20 )251.14.4391466070484856.5649261507388
Winsorized Mean ( 20 / 20 )253.1333333333334.0796537093174162.0477499732904
Trimmed Mean ( 1 / 20 )261.2034482758629.9723349826484426.1928072743593
Trimmed Mean ( 2 / 20 )260.3160714285719.6976117614200226.8433174922702
Trimmed Mean ( 3 / 20 )259.4944444444449.4264560780042227.5283141720621
Trimmed Mean ( 4 / 20 )258.9596153846159.2413055872195628.0219729713027
Trimmed Mean ( 5 / 20 )258.3769.0315770584801728.6080712512328
Trimmed Mean ( 6 / 20 )257.9354166666678.8348030807160429.1953781323852
Trimmed Mean ( 7 / 20 )257.6369565217398.6572436837574329.7596978822616
Trimmed Mean ( 8 / 20 )257.3568181818188.436451538633630.5053394787236
Trimmed Mean ( 9 / 20 )257.0642857142868.204644319054331.3315575566493
Trimmed Mean ( 10 / 20 )256.6658.0439860877233731.9076882034541
Trimmed Mean ( 11 / 20 )256.1710526315797.8808642577719432.5054517185661
Trimmed Mean ( 12 / 20 )255.5833333333337.6592598796986833.3691945889931
Trimmed Mean ( 13 / 20 )255.17.4285665315060934.3404072532793
Trimmed Mean ( 14 / 20 )254.7906257.1938122483714135.4180254089452
Trimmed Mean ( 15 / 20 )254.4566666666676.9419823650804636.6547555560835
Trimmed Mean ( 16 / 20 )253.9392857142866.6509404579963438.1809591166882
Trimmed Mean ( 17 / 20 )253.4692307692316.2678956577412340.439286901048
Trimmed Mean ( 18 / 20 )252.65.9551463555434242.4170935387448
Trimmed Mean ( 19 / 20 )251.7909090909095.6179902319565944.8186804702252
Trimmed Mean ( 20 / 20 )251.95.5430658436796945.4441652153963
Median249.25
Midrange284.5
Midmean - Weighted Average at Xnp252.422580645161
Midmean - Weighted Average at X(n+1)p254.456666666667
Midmean - Empirical Distribution Function252.422580645161
Midmean - Empirical Distribution Function - Averaging254.456666666667
Midmean - Empirical Distribution Function - Interpolation254.456666666667
Midmean - Closest Observation252.422580645161
Midmean - True Basic - Statistics Graphics Toolkit254.456666666667
Midmean - MS Excel (old versions)254.790625
Number of observations60

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 261.98 & 10.2517295771023 & 25.5547123077792 \tabularnewline
Geometric Mean & 250.227671162488 &  &  \tabularnewline
Harmonic Mean & 238.864251207767 &  &  \tabularnewline
Quadratic Mean & 273.558586046938 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & 262.031666666667 & 10.1931469976466 & 25.7066504316249 \tabularnewline
Winsorized Mean ( 2 / 20 ) & 261.795 & 10.0862913693573 & 25.9555262100943 \tabularnewline
Winsorized Mean ( 3 / 20 ) & 260.885 & 9.76605496194722 & 26.7134478575557 \tabularnewline
Winsorized Mean ( 4 / 20 ) & 260.905 & 9.69523979680307 & 26.9106288723288 \tabularnewline
Winsorized Mean ( 5 / 20 ) & 260.138333333333 & 9.48371726556934 & 27.4299967036940 \tabularnewline
Winsorized Mean ( 6 / 20 ) & 259.308333333333 & 9.23079080160392 & 28.09167046536 \tabularnewline
Winsorized Mean ( 7 / 20 ) & 259.075 & 9.18060736300558 & 28.2198104935819 \tabularnewline
Winsorized Mean ( 8 / 20 ) & 258.995 & 8.96333442325181 & 28.8949388442029 \tabularnewline
Winsorized Mean ( 9 / 20 ) & 259.46 & 8.4089474139258 & 30.8552292252793 \tabularnewline
Winsorized Mean ( 10 / 20 ) & 259.793333333333 & 8.17242395932799 & 31.7890181207261 \tabularnewline
Winsorized Mean ( 11 / 20 ) & 260.05 & 8.12612982148982 & 32.001703850742 \tabularnewline
Winsorized Mean ( 12 / 20 ) & 258.87 & 7.83273526987282 & 33.0497573428399 \tabularnewline
Winsorized Mean ( 13 / 20 ) & 257.245 & 7.50005778697135 & 34.2990690614238 \tabularnewline
Winsorized Mean ( 14 / 20 ) & 257.128333333333 & 7.18424480368304 & 35.7905862564031 \tabularnewline
Winsorized Mean ( 15 / 20 ) & 258.078333333333 & 6.89501502219602 & 37.4296984854337 \tabularnewline
Winsorized Mean ( 16 / 20 ) & 257.198333333333 & 6.70608480406017 & 38.3529795474125 \tabularnewline
Winsorized Mean ( 17 / 20 ) & 259.38 & 5.92933280990547 & 43.7452253593664 \tabularnewline
Winsorized Mean ( 18 / 20 ) & 257.94 & 5.5107953633503 & 46.8063107034308 \tabularnewline
Winsorized Mean ( 19 / 20 ) & 251.1 & 4.43914660704848 & 56.5649261507388 \tabularnewline
Winsorized Mean ( 20 / 20 ) & 253.133333333333 & 4.07965370931741 & 62.0477499732904 \tabularnewline
Trimmed Mean ( 1 / 20 ) & 261.203448275862 & 9.97233498264844 & 26.1928072743593 \tabularnewline
Trimmed Mean ( 2 / 20 ) & 260.316071428571 & 9.69761176142002 & 26.8433174922702 \tabularnewline
Trimmed Mean ( 3 / 20 ) & 259.494444444444 & 9.42645607800422 & 27.5283141720621 \tabularnewline
Trimmed Mean ( 4 / 20 ) & 258.959615384615 & 9.24130558721956 & 28.0219729713027 \tabularnewline
Trimmed Mean ( 5 / 20 ) & 258.376 & 9.03157705848017 & 28.6080712512328 \tabularnewline
Trimmed Mean ( 6 / 20 ) & 257.935416666667 & 8.83480308071604 & 29.1953781323852 \tabularnewline
Trimmed Mean ( 7 / 20 ) & 257.636956521739 & 8.65724368375743 & 29.7596978822616 \tabularnewline
Trimmed Mean ( 8 / 20 ) & 257.356818181818 & 8.4364515386336 & 30.5053394787236 \tabularnewline
Trimmed Mean ( 9 / 20 ) & 257.064285714286 & 8.2046443190543 & 31.3315575566493 \tabularnewline
Trimmed Mean ( 10 / 20 ) & 256.665 & 8.04398608772337 & 31.9076882034541 \tabularnewline
Trimmed Mean ( 11 / 20 ) & 256.171052631579 & 7.88086425777194 & 32.5054517185661 \tabularnewline
Trimmed Mean ( 12 / 20 ) & 255.583333333333 & 7.65925987969868 & 33.3691945889931 \tabularnewline
Trimmed Mean ( 13 / 20 ) & 255.1 & 7.42856653150609 & 34.3404072532793 \tabularnewline
Trimmed Mean ( 14 / 20 ) & 254.790625 & 7.19381224837141 & 35.4180254089452 \tabularnewline
Trimmed Mean ( 15 / 20 ) & 254.456666666667 & 6.94198236508046 & 36.6547555560835 \tabularnewline
Trimmed Mean ( 16 / 20 ) & 253.939285714286 & 6.65094045799634 & 38.1809591166882 \tabularnewline
Trimmed Mean ( 17 / 20 ) & 253.469230769231 & 6.26789565774123 & 40.439286901048 \tabularnewline
Trimmed Mean ( 18 / 20 ) & 252.6 & 5.95514635554342 & 42.4170935387448 \tabularnewline
Trimmed Mean ( 19 / 20 ) & 251.790909090909 & 5.61799023195659 & 44.8186804702252 \tabularnewline
Trimmed Mean ( 20 / 20 ) & 251.9 & 5.54306584367969 & 45.4441652153963 \tabularnewline
Median & 249.25 &  &  \tabularnewline
Midrange & 284.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 252.422580645161 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 254.456666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 252.422580645161 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 254.456666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 254.456666666667 &  &  \tabularnewline
Midmean - Closest Observation & 252.422580645161 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 254.456666666667 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 254.790625 &  &  \tabularnewline
Number of observations & 60 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26421&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]261.98[/C][C]10.2517295771023[/C][C]25.5547123077792[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]250.227671162488[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]238.864251207767[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]273.558586046938[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]262.031666666667[/C][C]10.1931469976466[/C][C]25.7066504316249[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]261.795[/C][C]10.0862913693573[/C][C]25.9555262100943[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]260.885[/C][C]9.76605496194722[/C][C]26.7134478575557[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]260.905[/C][C]9.69523979680307[/C][C]26.9106288723288[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]260.138333333333[/C][C]9.48371726556934[/C][C]27.4299967036940[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]259.308333333333[/C][C]9.23079080160392[/C][C]28.09167046536[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]259.075[/C][C]9.18060736300558[/C][C]28.2198104935819[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]258.995[/C][C]8.96333442325181[/C][C]28.8949388442029[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]259.46[/C][C]8.4089474139258[/C][C]30.8552292252793[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]259.793333333333[/C][C]8.17242395932799[/C][C]31.7890181207261[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]260.05[/C][C]8.12612982148982[/C][C]32.001703850742[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]258.87[/C][C]7.83273526987282[/C][C]33.0497573428399[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]257.245[/C][C]7.50005778697135[/C][C]34.2990690614238[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]257.128333333333[/C][C]7.18424480368304[/C][C]35.7905862564031[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]258.078333333333[/C][C]6.89501502219602[/C][C]37.4296984854337[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]257.198333333333[/C][C]6.70608480406017[/C][C]38.3529795474125[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]259.38[/C][C]5.92933280990547[/C][C]43.7452253593664[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]257.94[/C][C]5.5107953633503[/C][C]46.8063107034308[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]251.1[/C][C]4.43914660704848[/C][C]56.5649261507388[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]253.133333333333[/C][C]4.07965370931741[/C][C]62.0477499732904[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]261.203448275862[/C][C]9.97233498264844[/C][C]26.1928072743593[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]260.316071428571[/C][C]9.69761176142002[/C][C]26.8433174922702[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]259.494444444444[/C][C]9.42645607800422[/C][C]27.5283141720621[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]258.959615384615[/C][C]9.24130558721956[/C][C]28.0219729713027[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]258.376[/C][C]9.03157705848017[/C][C]28.6080712512328[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]257.935416666667[/C][C]8.83480308071604[/C][C]29.1953781323852[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]257.636956521739[/C][C]8.65724368375743[/C][C]29.7596978822616[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]257.356818181818[/C][C]8.4364515386336[/C][C]30.5053394787236[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]257.064285714286[/C][C]8.2046443190543[/C][C]31.3315575566493[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]256.665[/C][C]8.04398608772337[/C][C]31.9076882034541[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]256.171052631579[/C][C]7.88086425777194[/C][C]32.5054517185661[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]255.583333333333[/C][C]7.65925987969868[/C][C]33.3691945889931[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]255.1[/C][C]7.42856653150609[/C][C]34.3404072532793[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]254.790625[/C][C]7.19381224837141[/C][C]35.4180254089452[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]254.456666666667[/C][C]6.94198236508046[/C][C]36.6547555560835[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]253.939285714286[/C][C]6.65094045799634[/C][C]38.1809591166882[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]253.469230769231[/C][C]6.26789565774123[/C][C]40.439286901048[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]252.6[/C][C]5.95514635554342[/C][C]42.4170935387448[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]251.790909090909[/C][C]5.61799023195659[/C][C]44.8186804702252[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]251.9[/C][C]5.54306584367969[/C][C]45.4441652153963[/C][/ROW]
[ROW][C]Median[/C][C]249.25[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]284.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]252.422580645161[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]254.456666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]252.422580645161[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]254.456666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]254.456666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]252.422580645161[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]254.456666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]254.790625[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]60[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26421&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26421&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 Mean261.9810.251729577102325.5547123077792
Geometric Mean250.227671162488
Harmonic Mean238.864251207767
Quadratic Mean273.558586046938
Winsorized Mean ( 1 / 20 )262.03166666666710.193146997646625.7066504316249
Winsorized Mean ( 2 / 20 )261.79510.086291369357325.9555262100943
Winsorized Mean ( 3 / 20 )260.8859.7660549619472226.7134478575557
Winsorized Mean ( 4 / 20 )260.9059.6952397968030726.9106288723288
Winsorized Mean ( 5 / 20 )260.1383333333339.4837172655693427.4299967036940
Winsorized Mean ( 6 / 20 )259.3083333333339.2307908016039228.09167046536
Winsorized Mean ( 7 / 20 )259.0759.1806073630055828.2198104935819
Winsorized Mean ( 8 / 20 )258.9958.9633344232518128.8949388442029
Winsorized Mean ( 9 / 20 )259.468.408947413925830.8552292252793
Winsorized Mean ( 10 / 20 )259.7933333333338.1724239593279931.7890181207261
Winsorized Mean ( 11 / 20 )260.058.1261298214898232.001703850742
Winsorized Mean ( 12 / 20 )258.877.8327352698728233.0497573428399
Winsorized Mean ( 13 / 20 )257.2457.5000577869713534.2990690614238
Winsorized Mean ( 14 / 20 )257.1283333333337.1842448036830435.7905862564031
Winsorized Mean ( 15 / 20 )258.0783333333336.8950150221960237.4296984854337
Winsorized Mean ( 16 / 20 )257.1983333333336.7060848040601738.3529795474125
Winsorized Mean ( 17 / 20 )259.385.9293328099054743.7452253593664
Winsorized Mean ( 18 / 20 )257.945.510795363350346.8063107034308
Winsorized Mean ( 19 / 20 )251.14.4391466070484856.5649261507388
Winsorized Mean ( 20 / 20 )253.1333333333334.0796537093174162.0477499732904
Trimmed Mean ( 1 / 20 )261.2034482758629.9723349826484426.1928072743593
Trimmed Mean ( 2 / 20 )260.3160714285719.6976117614200226.8433174922702
Trimmed Mean ( 3 / 20 )259.4944444444449.4264560780042227.5283141720621
Trimmed Mean ( 4 / 20 )258.9596153846159.2413055872195628.0219729713027
Trimmed Mean ( 5 / 20 )258.3769.0315770584801728.6080712512328
Trimmed Mean ( 6 / 20 )257.9354166666678.8348030807160429.1953781323852
Trimmed Mean ( 7 / 20 )257.6369565217398.6572436837574329.7596978822616
Trimmed Mean ( 8 / 20 )257.3568181818188.436451538633630.5053394787236
Trimmed Mean ( 9 / 20 )257.0642857142868.204644319054331.3315575566493
Trimmed Mean ( 10 / 20 )256.6658.0439860877233731.9076882034541
Trimmed Mean ( 11 / 20 )256.1710526315797.8808642577719432.5054517185661
Trimmed Mean ( 12 / 20 )255.5833333333337.6592598796986833.3691945889931
Trimmed Mean ( 13 / 20 )255.17.4285665315060934.3404072532793
Trimmed Mean ( 14 / 20 )254.7906257.1938122483714135.4180254089452
Trimmed Mean ( 15 / 20 )254.4566666666676.9419823650804636.6547555560835
Trimmed Mean ( 16 / 20 )253.9392857142866.6509404579963438.1809591166882
Trimmed Mean ( 17 / 20 )253.4692307692316.2678956577412340.439286901048
Trimmed Mean ( 18 / 20 )252.65.9551463555434242.4170935387448
Trimmed Mean ( 19 / 20 )251.7909090909095.6179902319565944.8186804702252
Trimmed Mean ( 20 / 20 )251.95.5430658436796945.4441652153963
Median249.25
Midrange284.5
Midmean - Weighted Average at Xnp252.422580645161
Midmean - Weighted Average at X(n+1)p254.456666666667
Midmean - Empirical Distribution Function252.422580645161
Midmean - Empirical Distribution Function - Averaging254.456666666667
Midmean - Empirical Distribution Function - Interpolation254.456666666667
Midmean - Closest Observation252.422580645161
Midmean - True Basic - Statistics Graphics Toolkit254.456666666667
Midmean - MS Excel (old versions)254.790625
Number of observations60



Parameters (Session):
par1 = totale uitvoer belgie naar frankrijk ; par2 = http://www.nbb.be/belgostat/PublicatieSelectieLinker?LinkID=931000000|910000082&Lang=E ;
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')