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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 20 Oct 2008 12:57:54 -0600
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/Oct/20/t1224529111okgpmumbk3z943s.htm/, Retrieved Sun, 19 May 2024 16:36:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17904, Retrieved Sun, 19 May 2024 16:36:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact165
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Werkloosheid BELGIE] [2008-10-19 10:57:42] [46c5a5fbda57fdfa1d4ef48658f82a0c]
- RMP   [Histogram] [Histogram - Werkl...] [2008-10-19 11:37:28] [46c5a5fbda57fdfa1d4ef48658f82a0c]
- RM      [Central Tendency] [] [2008-10-19 12:22:19] [46c5a5fbda57fdfa1d4ef48658f82a0c]
F   PD        [Central Tendency] [Prijsindexcijfers...] [2008-10-20 18:57:54] [dbfa7caa6871c163dec68ca05d48bb00] [Current]
Feedback Forum
2008-10-27 20:41:57 [Thomas Baken] [reply
We kunnen hier inderdaad analyseren dat er een schommelende tendens in dalende lijn is bij de prijsindexcijfers van grondstoffen. Ook bemerken we een lichte stijging van werkloosheid naarmate het einde.

Post a new message
Dataseries X:
98,5
96,8
91,2
97,1
104,9
110,9
104,8
94,1
95,8
99,3
101,1
104
99
105,4
107,1
110,7
117,1
118,7
126,5
127,5
134,6
131,8
135,9
142,7
141,7
153,4
145
137,7
148,3
152,2
169,4
168,6
161,1
174,1
179
190,6
190
181,6
174,8
180,5
196,8
193,8
197
216,3
221,4
217,9
229,7
227,4
204,2
196,6
198,8
207,5
190,7
201,6
210,5
223,5
223,8
231,2
244
234,7
250,2
265,7
287,6
283,3
295,4
312,3
333,8
347,7
383,2
407,1
413,6
362,7
321,9




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17904&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17904&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17904&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean189.5260273972609.4251335894422620.1085773054253
Geometric Mean174.391440371510
Harmonic Mean161.141015700804
Quadratic Mean205.708778057386
Winsorized Mean ( 1 / 24 )189.4767123287679.3904221745883920.1776564254495
Winsorized Mean ( 2 / 24 )188.8684931506859.182138018304120.5691193896439
Winsorized Mean ( 3 / 24 )188.0671232876718.9380771955043521.0411164699120
Winsorized Mean ( 4 / 24 )187.2616438356168.7191047582827821.4771641156996
Winsorized Mean ( 5 / 24 )186.4054794520558.4684807970908422.0116788262767
Winsorized Mean ( 6 / 24 )185.4684931506858.2316469157996522.5311526414842
Winsorized Mean ( 7 / 24 )184.5767123287678.0196053339856923.0156852665259
Winsorized Mean ( 8 / 24 )182.9219178082197.5945750000518824.0858662672986
Winsorized Mean ( 9 / 24 )182.3178082191787.3466940199712524.8163061811974
Winsorized Mean ( 10 / 24 )181.8383561643847.2142950193412625.2052841860337
Winsorized Mean ( 11 / 24 )179.2013698630146.7149857095127226.6867835041182
Winsorized Mean ( 12 / 24 )176.7356164383566.266098405773228.2050496167636
Winsorized Mean ( 13 / 24 )175.9342465753426.0418763840717329.1191403781713
Winsorized Mean ( 14 / 24 )174.8410958904115.6621775247001330.8787732506975
Winsorized Mean ( 15 / 24 )174.163013698635.5515683013405731.3718582290654
Winsorized Mean ( 16 / 24 )175.1931506849315.2934055240924933.0964914529134
Winsorized Mean ( 17 / 24 )175.0301369863015.1607101048100533.9159017715729
Winsorized Mean ( 18 / 24 )176.0657534246584.7507939011218337.0602802582284
Winsorized Mean ( 19 / 24 )176.2479452054794.7023012070976337.4812113140374
Winsorized Mean ( 20 / 24 )176.8506849315074.4545827151641539.7008420854948
Winsorized Mean ( 21 / 24 )176.6493150684934.2034595283435242.0247450647173
Winsorized Mean ( 22 / 24 )176.5589041095894.0837008667026443.2350237866836
Winsorized Mean ( 23 / 24 )175.2986301369863.7627280156896646.5881746982597
Winsorized Mean ( 24 / 24 )175.6273972602743.454401412436350.8416296461645
Trimmed Mean ( 1 / 24 )187.7549295774659.0472394911036720.7527312349903
Trimmed Mean ( 2 / 24 )185.9333333333338.633074859448621.5373243439255
Trimmed Mean ( 3 / 24 )184.3343283582098.2707083006740422.2876108861421
Trimmed Mean ( 4 / 24 )182.9369230769237.9493848241760323.0127144581763
Trimmed Mean ( 5 / 24 )181.6841269841277.6446284486907223.7662468756403
Trimmed Mean ( 6 / 24 )180.5540983606567.357596191324524.5398216571808
Trimmed Mean ( 7 / 24 )179.5406779661027.0781089736706125.3656278299703
Trimmed Mean ( 8 / 24 )178.6192982456146.7937971297226426.2915266433495
Trimmed Mean ( 9 / 24 )177.9054545454556.5559988301674527.1362852791892
Trimmed Mean ( 10 / 24 )177.2301886792456.321538380464628.0359270184831
Trimmed Mean ( 11 / 24 )176.5705882352946.0590469024120129.1416440702917
Trimmed Mean ( 12 / 24 )176.2142857142865.8513611126598830.1150932785591
Trimmed Mean ( 13 / 24 )176.1468085106385.6917429288099430.9477800936923
Trimmed Mean ( 14 / 24 )176.1733333333335.5353988477832731.8266737732701
Trimmed Mean ( 15 / 24 )176.3348837209305.4149631535983332.5643737028483
Trimmed Mean ( 16 / 24 )176.5926829268295.2765350214172533.4675468295096
Trimmed Mean ( 17 / 24 )176.7564102564105.1495696332001134.3245014334466
Trimmed Mean ( 18 / 24 )176.9567567567575.0047253054979635.3579359415312
Trimmed Mean ( 19 / 24 )177.064.904330447967136.1027875014812
Trimmed Mean ( 20 / 24 )177.1545454545454.7682327322006637.1530827885543
Trimmed Mean ( 21 / 24 )177.1903225806454.6367544146641838.2142996446531
Trimmed Mean ( 22 / 24 )177.2551724137934.5109597959811239.2943365559835
Trimmed Mean ( 23 / 24 )177.3407407407414.3507613351481940.7608524301415
Trimmed Mean ( 24 / 24 )177.64.2062730930520142.2226508053798
Median180.5
Midrange252.4
Midmean - Weighted Average at Xnp175.655555555556
Midmean - Weighted Average at X(n+1)p176.956756756757
Midmean - Empirical Distribution Function176.956756756757
Midmean - Empirical Distribution Function - Averaging176.956756756757
Midmean - Empirical Distribution Function - Interpolation176.956756756757
Midmean - Closest Observation175.423684210526
Midmean - True Basic - Statistics Graphics Toolkit176.956756756757
Midmean - MS Excel (old versions)176.956756756757
Number of observations73

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 189.526027397260 & 9.42513358944226 & 20.1085773054253 \tabularnewline
Geometric Mean & 174.391440371510 &  &  \tabularnewline
Harmonic Mean & 161.141015700804 &  &  \tabularnewline
Quadratic Mean & 205.708778057386 &  &  \tabularnewline
Winsorized Mean ( 1 / 24 ) & 189.476712328767 & 9.39042217458839 & 20.1776564254495 \tabularnewline
Winsorized Mean ( 2 / 24 ) & 188.868493150685 & 9.1821380183041 & 20.5691193896439 \tabularnewline
Winsorized Mean ( 3 / 24 ) & 188.067123287671 & 8.93807719550435 & 21.0411164699120 \tabularnewline
Winsorized Mean ( 4 / 24 ) & 187.261643835616 & 8.71910475828278 & 21.4771641156996 \tabularnewline
Winsorized Mean ( 5 / 24 ) & 186.405479452055 & 8.46848079709084 & 22.0116788262767 \tabularnewline
Winsorized Mean ( 6 / 24 ) & 185.468493150685 & 8.23164691579965 & 22.5311526414842 \tabularnewline
Winsorized Mean ( 7 / 24 ) & 184.576712328767 & 8.01960533398569 & 23.0156852665259 \tabularnewline
Winsorized Mean ( 8 / 24 ) & 182.921917808219 & 7.59457500005188 & 24.0858662672986 \tabularnewline
Winsorized Mean ( 9 / 24 ) & 182.317808219178 & 7.34669401997125 & 24.8163061811974 \tabularnewline
Winsorized Mean ( 10 / 24 ) & 181.838356164384 & 7.21429501934126 & 25.2052841860337 \tabularnewline
Winsorized Mean ( 11 / 24 ) & 179.201369863014 & 6.71498570951272 & 26.6867835041182 \tabularnewline
Winsorized Mean ( 12 / 24 ) & 176.735616438356 & 6.2660984057732 & 28.2050496167636 \tabularnewline
Winsorized Mean ( 13 / 24 ) & 175.934246575342 & 6.04187638407173 & 29.1191403781713 \tabularnewline
Winsorized Mean ( 14 / 24 ) & 174.841095890411 & 5.66217752470013 & 30.8787732506975 \tabularnewline
Winsorized Mean ( 15 / 24 ) & 174.16301369863 & 5.55156830134057 & 31.3718582290654 \tabularnewline
Winsorized Mean ( 16 / 24 ) & 175.193150684931 & 5.29340552409249 & 33.0964914529134 \tabularnewline
Winsorized Mean ( 17 / 24 ) & 175.030136986301 & 5.16071010481005 & 33.9159017715729 \tabularnewline
Winsorized Mean ( 18 / 24 ) & 176.065753424658 & 4.75079390112183 & 37.0602802582284 \tabularnewline
Winsorized Mean ( 19 / 24 ) & 176.247945205479 & 4.70230120709763 & 37.4812113140374 \tabularnewline
Winsorized Mean ( 20 / 24 ) & 176.850684931507 & 4.45458271516415 & 39.7008420854948 \tabularnewline
Winsorized Mean ( 21 / 24 ) & 176.649315068493 & 4.20345952834352 & 42.0247450647173 \tabularnewline
Winsorized Mean ( 22 / 24 ) & 176.558904109589 & 4.08370086670264 & 43.2350237866836 \tabularnewline
Winsorized Mean ( 23 / 24 ) & 175.298630136986 & 3.76272801568966 & 46.5881746982597 \tabularnewline
Winsorized Mean ( 24 / 24 ) & 175.627397260274 & 3.4544014124363 & 50.8416296461645 \tabularnewline
Trimmed Mean ( 1 / 24 ) & 187.754929577465 & 9.04723949110367 & 20.7527312349903 \tabularnewline
Trimmed Mean ( 2 / 24 ) & 185.933333333333 & 8.6330748594486 & 21.5373243439255 \tabularnewline
Trimmed Mean ( 3 / 24 ) & 184.334328358209 & 8.27070830067404 & 22.2876108861421 \tabularnewline
Trimmed Mean ( 4 / 24 ) & 182.936923076923 & 7.94938482417603 & 23.0127144581763 \tabularnewline
Trimmed Mean ( 5 / 24 ) & 181.684126984127 & 7.64462844869072 & 23.7662468756403 \tabularnewline
Trimmed Mean ( 6 / 24 ) & 180.554098360656 & 7.3575961913245 & 24.5398216571808 \tabularnewline
Trimmed Mean ( 7 / 24 ) & 179.540677966102 & 7.07810897367061 & 25.3656278299703 \tabularnewline
Trimmed Mean ( 8 / 24 ) & 178.619298245614 & 6.79379712972264 & 26.2915266433495 \tabularnewline
Trimmed Mean ( 9 / 24 ) & 177.905454545455 & 6.55599883016745 & 27.1362852791892 \tabularnewline
Trimmed Mean ( 10 / 24 ) & 177.230188679245 & 6.3215383804646 & 28.0359270184831 \tabularnewline
Trimmed Mean ( 11 / 24 ) & 176.570588235294 & 6.05904690241201 & 29.1416440702917 \tabularnewline
Trimmed Mean ( 12 / 24 ) & 176.214285714286 & 5.85136111265988 & 30.1150932785591 \tabularnewline
Trimmed Mean ( 13 / 24 ) & 176.146808510638 & 5.69174292880994 & 30.9477800936923 \tabularnewline
Trimmed Mean ( 14 / 24 ) & 176.173333333333 & 5.53539884778327 & 31.8266737732701 \tabularnewline
Trimmed Mean ( 15 / 24 ) & 176.334883720930 & 5.41496315359833 & 32.5643737028483 \tabularnewline
Trimmed Mean ( 16 / 24 ) & 176.592682926829 & 5.27653502141725 & 33.4675468295096 \tabularnewline
Trimmed Mean ( 17 / 24 ) & 176.756410256410 & 5.14956963320011 & 34.3245014334466 \tabularnewline
Trimmed Mean ( 18 / 24 ) & 176.956756756757 & 5.00472530549796 & 35.3579359415312 \tabularnewline
Trimmed Mean ( 19 / 24 ) & 177.06 & 4.9043304479671 & 36.1027875014812 \tabularnewline
Trimmed Mean ( 20 / 24 ) & 177.154545454545 & 4.76823273220066 & 37.1530827885543 \tabularnewline
Trimmed Mean ( 21 / 24 ) & 177.190322580645 & 4.63675441466418 & 38.2142996446531 \tabularnewline
Trimmed Mean ( 22 / 24 ) & 177.255172413793 & 4.51095979598112 & 39.2943365559835 \tabularnewline
Trimmed Mean ( 23 / 24 ) & 177.340740740741 & 4.35076133514819 & 40.7608524301415 \tabularnewline
Trimmed Mean ( 24 / 24 ) & 177.6 & 4.20627309305201 & 42.2226508053798 \tabularnewline
Median & 180.5 &  &  \tabularnewline
Midrange & 252.4 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 175.655555555556 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 176.956756756757 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 176.956756756757 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 176.956756756757 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 176.956756756757 &  &  \tabularnewline
Midmean - Closest Observation & 175.423684210526 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 176.956756756757 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 176.956756756757 &  &  \tabularnewline
Number of observations & 73 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17904&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]189.526027397260[/C][C]9.42513358944226[/C][C]20.1085773054253[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]174.391440371510[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]161.141015700804[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]205.708778057386[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 24 )[/C][C]189.476712328767[/C][C]9.39042217458839[/C][C]20.1776564254495[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 24 )[/C][C]188.868493150685[/C][C]9.1821380183041[/C][C]20.5691193896439[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 24 )[/C][C]188.067123287671[/C][C]8.93807719550435[/C][C]21.0411164699120[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 24 )[/C][C]187.261643835616[/C][C]8.71910475828278[/C][C]21.4771641156996[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 24 )[/C][C]186.405479452055[/C][C]8.46848079709084[/C][C]22.0116788262767[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 24 )[/C][C]185.468493150685[/C][C]8.23164691579965[/C][C]22.5311526414842[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 24 )[/C][C]184.576712328767[/C][C]8.01960533398569[/C][C]23.0156852665259[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 24 )[/C][C]182.921917808219[/C][C]7.59457500005188[/C][C]24.0858662672986[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 24 )[/C][C]182.317808219178[/C][C]7.34669401997125[/C][C]24.8163061811974[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 24 )[/C][C]181.838356164384[/C][C]7.21429501934126[/C][C]25.2052841860337[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 24 )[/C][C]179.201369863014[/C][C]6.71498570951272[/C][C]26.6867835041182[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 24 )[/C][C]176.735616438356[/C][C]6.2660984057732[/C][C]28.2050496167636[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 24 )[/C][C]175.934246575342[/C][C]6.04187638407173[/C][C]29.1191403781713[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 24 )[/C][C]174.841095890411[/C][C]5.66217752470013[/C][C]30.8787732506975[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 24 )[/C][C]174.16301369863[/C][C]5.55156830134057[/C][C]31.3718582290654[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 24 )[/C][C]175.193150684931[/C][C]5.29340552409249[/C][C]33.0964914529134[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 24 )[/C][C]175.030136986301[/C][C]5.16071010481005[/C][C]33.9159017715729[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 24 )[/C][C]176.065753424658[/C][C]4.75079390112183[/C][C]37.0602802582284[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 24 )[/C][C]176.247945205479[/C][C]4.70230120709763[/C][C]37.4812113140374[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 24 )[/C][C]176.850684931507[/C][C]4.45458271516415[/C][C]39.7008420854948[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 24 )[/C][C]176.649315068493[/C][C]4.20345952834352[/C][C]42.0247450647173[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 24 )[/C][C]176.558904109589[/C][C]4.08370086670264[/C][C]43.2350237866836[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 24 )[/C][C]175.298630136986[/C][C]3.76272801568966[/C][C]46.5881746982597[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 24 )[/C][C]175.627397260274[/C][C]3.4544014124363[/C][C]50.8416296461645[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 24 )[/C][C]187.754929577465[/C][C]9.04723949110367[/C][C]20.7527312349903[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 24 )[/C][C]185.933333333333[/C][C]8.6330748594486[/C][C]21.5373243439255[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 24 )[/C][C]184.334328358209[/C][C]8.27070830067404[/C][C]22.2876108861421[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 24 )[/C][C]182.936923076923[/C][C]7.94938482417603[/C][C]23.0127144581763[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 24 )[/C][C]181.684126984127[/C][C]7.64462844869072[/C][C]23.7662468756403[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 24 )[/C][C]180.554098360656[/C][C]7.3575961913245[/C][C]24.5398216571808[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 24 )[/C][C]179.540677966102[/C][C]7.07810897367061[/C][C]25.3656278299703[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 24 )[/C][C]178.619298245614[/C][C]6.79379712972264[/C][C]26.2915266433495[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 24 )[/C][C]177.905454545455[/C][C]6.55599883016745[/C][C]27.1362852791892[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 24 )[/C][C]177.230188679245[/C][C]6.3215383804646[/C][C]28.0359270184831[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 24 )[/C][C]176.570588235294[/C][C]6.05904690241201[/C][C]29.1416440702917[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 24 )[/C][C]176.214285714286[/C][C]5.85136111265988[/C][C]30.1150932785591[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 24 )[/C][C]176.146808510638[/C][C]5.69174292880994[/C][C]30.9477800936923[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 24 )[/C][C]176.173333333333[/C][C]5.53539884778327[/C][C]31.8266737732701[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 24 )[/C][C]176.334883720930[/C][C]5.41496315359833[/C][C]32.5643737028483[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 24 )[/C][C]176.592682926829[/C][C]5.27653502141725[/C][C]33.4675468295096[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 24 )[/C][C]176.756410256410[/C][C]5.14956963320011[/C][C]34.3245014334466[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 24 )[/C][C]176.956756756757[/C][C]5.00472530549796[/C][C]35.3579359415312[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 24 )[/C][C]177.06[/C][C]4.9043304479671[/C][C]36.1027875014812[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 24 )[/C][C]177.154545454545[/C][C]4.76823273220066[/C][C]37.1530827885543[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 24 )[/C][C]177.190322580645[/C][C]4.63675441466418[/C][C]38.2142996446531[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 24 )[/C][C]177.255172413793[/C][C]4.51095979598112[/C][C]39.2943365559835[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 24 )[/C][C]177.340740740741[/C][C]4.35076133514819[/C][C]40.7608524301415[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 24 )[/C][C]177.6[/C][C]4.20627309305201[/C][C]42.2226508053798[/C][/ROW]
[ROW][C]Median[/C][C]180.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]252.4[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]175.655555555556[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]176.956756756757[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]176.956756756757[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]176.956756756757[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]176.956756756757[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]175.423684210526[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]176.956756756757[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]176.956756756757[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]73[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17904&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17904&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 Mean189.5260273972609.4251335894422620.1085773054253
Geometric Mean174.391440371510
Harmonic Mean161.141015700804
Quadratic Mean205.708778057386
Winsorized Mean ( 1 / 24 )189.4767123287679.3904221745883920.1776564254495
Winsorized Mean ( 2 / 24 )188.8684931506859.182138018304120.5691193896439
Winsorized Mean ( 3 / 24 )188.0671232876718.9380771955043521.0411164699120
Winsorized Mean ( 4 / 24 )187.2616438356168.7191047582827821.4771641156996
Winsorized Mean ( 5 / 24 )186.4054794520558.4684807970908422.0116788262767
Winsorized Mean ( 6 / 24 )185.4684931506858.2316469157996522.5311526414842
Winsorized Mean ( 7 / 24 )184.5767123287678.0196053339856923.0156852665259
Winsorized Mean ( 8 / 24 )182.9219178082197.5945750000518824.0858662672986
Winsorized Mean ( 9 / 24 )182.3178082191787.3466940199712524.8163061811974
Winsorized Mean ( 10 / 24 )181.8383561643847.2142950193412625.2052841860337
Winsorized Mean ( 11 / 24 )179.2013698630146.7149857095127226.6867835041182
Winsorized Mean ( 12 / 24 )176.7356164383566.266098405773228.2050496167636
Winsorized Mean ( 13 / 24 )175.9342465753426.0418763840717329.1191403781713
Winsorized Mean ( 14 / 24 )174.8410958904115.6621775247001330.8787732506975
Winsorized Mean ( 15 / 24 )174.163013698635.5515683013405731.3718582290654
Winsorized Mean ( 16 / 24 )175.1931506849315.2934055240924933.0964914529134
Winsorized Mean ( 17 / 24 )175.0301369863015.1607101048100533.9159017715729
Winsorized Mean ( 18 / 24 )176.0657534246584.7507939011218337.0602802582284
Winsorized Mean ( 19 / 24 )176.2479452054794.7023012070976337.4812113140374
Winsorized Mean ( 20 / 24 )176.8506849315074.4545827151641539.7008420854948
Winsorized Mean ( 21 / 24 )176.6493150684934.2034595283435242.0247450647173
Winsorized Mean ( 22 / 24 )176.5589041095894.0837008667026443.2350237866836
Winsorized Mean ( 23 / 24 )175.2986301369863.7627280156896646.5881746982597
Winsorized Mean ( 24 / 24 )175.6273972602743.454401412436350.8416296461645
Trimmed Mean ( 1 / 24 )187.7549295774659.0472394911036720.7527312349903
Trimmed Mean ( 2 / 24 )185.9333333333338.633074859448621.5373243439255
Trimmed Mean ( 3 / 24 )184.3343283582098.2707083006740422.2876108861421
Trimmed Mean ( 4 / 24 )182.9369230769237.9493848241760323.0127144581763
Trimmed Mean ( 5 / 24 )181.6841269841277.6446284486907223.7662468756403
Trimmed Mean ( 6 / 24 )180.5540983606567.357596191324524.5398216571808
Trimmed Mean ( 7 / 24 )179.5406779661027.0781089736706125.3656278299703
Trimmed Mean ( 8 / 24 )178.6192982456146.7937971297226426.2915266433495
Trimmed Mean ( 9 / 24 )177.9054545454556.5559988301674527.1362852791892
Trimmed Mean ( 10 / 24 )177.2301886792456.321538380464628.0359270184831
Trimmed Mean ( 11 / 24 )176.5705882352946.0590469024120129.1416440702917
Trimmed Mean ( 12 / 24 )176.2142857142865.8513611126598830.1150932785591
Trimmed Mean ( 13 / 24 )176.1468085106385.6917429288099430.9477800936923
Trimmed Mean ( 14 / 24 )176.1733333333335.5353988477832731.8266737732701
Trimmed Mean ( 15 / 24 )176.3348837209305.4149631535983332.5643737028483
Trimmed Mean ( 16 / 24 )176.5926829268295.2765350214172533.4675468295096
Trimmed Mean ( 17 / 24 )176.7564102564105.1495696332001134.3245014334466
Trimmed Mean ( 18 / 24 )176.9567567567575.0047253054979635.3579359415312
Trimmed Mean ( 19 / 24 )177.064.904330447967136.1027875014812
Trimmed Mean ( 20 / 24 )177.1545454545454.7682327322006637.1530827885543
Trimmed Mean ( 21 / 24 )177.1903225806454.6367544146641838.2142996446531
Trimmed Mean ( 22 / 24 )177.2551724137934.5109597959811239.2943365559835
Trimmed Mean ( 23 / 24 )177.3407407407414.3507613351481940.7608524301415
Trimmed Mean ( 24 / 24 )177.64.2062730930520142.2226508053798
Median180.5
Midrange252.4
Midmean - Weighted Average at Xnp175.655555555556
Midmean - Weighted Average at X(n+1)p176.956756756757
Midmean - Empirical Distribution Function176.956756756757
Midmean - Empirical Distribution Function - Averaging176.956756756757
Midmean - Empirical Distribution Function - Interpolation176.956756756757
Midmean - Closest Observation175.423684210526
Midmean - True Basic - Statistics Graphics Toolkit176.956756756757
Midmean - MS Excel (old versions)176.956756756757
Number of observations73



Parameters (Session):
par1 = Investeringen ; par3 = Investeringen ;
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')