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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 computationSun, 19 Oct 2008 13:04:35 -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/19/t1224443141io31sv6cor27plo.htm/, Retrieved Sun, 19 May 2024 14:38:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17060, Retrieved Sun, 19 May 2024 14:38:24 +0000
QR Codes:

Original text written by user:Werkelijk begonnen woongebouwen - koninkrijk, Aantal woningen
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [blog 1e tijdreeks...] [2008-10-13 19:23:31] [7173087adebe3e3a714c80ea2417b3eb]
-   PD  [Univariate Data Series] [tijdreeksen opnie...] [2008-10-19 17:21:24] [7173087adebe3e3a714c80ea2417b3eb]
- RMPD      [Central Tendency] [central tendency ...] [2008-10-19 19:04:35] [95d95b0e883740fcbc85e18ec42dcafb] [Current]
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Dataseries X:
3180
4151
4023
3431
3874
2617
3580
5267
3832
3441
3228
3397
3971
4625
4486
4131
4686
3174
4282
4209
4159
3936
3153
3620
4227
4441
4808
4850
5040
3546
4669
5410
5134
4864
3999
4459
4622
5360
4658
5173
4845
3325
4720
4895
5071
4895
3805
4187
4435
4475
4774
5161
4529
3284
4303
4610
4691
4200
3471
3132




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=17060&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=17060&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17060&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 Mean4242.0166666666786.749527397943148.8995939679004
Geometric Mean4186.64647655668
Harmonic Mean4128.25766442641
Quadratic Mean4294.03175931432
Winsorized Mean ( 1 / 20 )4249.7666666666784.227558216349350.4557742936177
Winsorized Mean ( 2 / 20 )4247.3666666666783.403403196652850.9255798189915
Winsorized Mean ( 3 / 20 )4243.7166666666782.233579720877951.6056418931408
Winsorized Mean ( 4 / 20 )4243.3166666666781.993028819241251.7521639067795
Winsorized Mean ( 5 / 20 )4245.0666666666780.702648276216652.6013304066219
Winsorized Mean ( 6 / 20 )4244.3666666666778.371175977558654.1572410229244
Winsorized Mean ( 7 / 20 )4245.5333333333376.747492889236655.3182022435647
Winsorized Mean ( 8 / 20 )4235.871.607056275723159.1533882316017
Winsorized Mean ( 9 / 20 )4240.970.60492732601560.0652130186019
Winsorized Mean ( 10 / 20 )4237.469.480417108577660.9869683622967
Winsorized Mean ( 11 / 20 )4240.3333333333368.027855156640162.332309662999
Winsorized Mean ( 12 / 20 )4254.3333333333365.052029010191165.3989337160697
Winsorized Mean ( 13 / 20 )4253.6833333333362.479069904111668.0817326484146
Winsorized Mean ( 14 / 20 )4255.0833333333359.601066856501471.3927377101838
Winsorized Mean ( 15 / 20 )4287.8333333333349.581583551710986.4803627915868
Winsorized Mean ( 16 / 20 )4287.347.268270912190690.701434963941
Winsorized Mean ( 17 / 20 )4297.7833333333345.143857260974695.2019520283357
Winsorized Mean ( 18 / 20 )4311.2833333333341.4919234647663103.906567189982
Winsorized Mean ( 19 / 20 )4318.8833333333339.3012707465999109.891696916873
Winsorized Mean ( 20 / 20 )4317.2166666666736.3126652327924118.890107321783
Trimmed Mean ( 1 / 20 )4249.8965517241482.738473424806351.3654213790456
Trimmed Mean ( 2 / 20 )4250.0357142857180.883337360195552.5452565756424
Trimmed Mean ( 3 / 20 )4251.5185185185279.110819938900453.7413026663368
Trimmed Mean ( 4 / 20 )4254.5192307692377.433489634861154.9441753281621
Trimmed Mean ( 5 / 20 )4257.8875.38847224170856.4791920222037
Trimmed Mean ( 6 / 20 )4261.0833333333373.222590261382458.1935618246031
Trimmed Mean ( 7 / 20 )4264.7173913043571.168261279650359.924428595304
Trimmed Mean ( 8 / 20 )4268.4545454545568.968697548898161.8897368973548
Trimmed Mean ( 9 / 20 )4274.2857142857167.501540273339563.321306402454
Trimmed Mean ( 10 / 20 )4279.8565.77235946224565.0706472292019
Trimmed Mean ( 11 / 20 )4286.5526315789563.682385529262467.3114330745234
Trimmed Mean ( 12 / 20 )4293.5555555555661.189225688743770.1684897500737
Trimmed Mean ( 13 / 20 )4299.3235294117658.604777971156573.3613141837644
Trimmed Mean ( 14 / 20 )4305.9062555.68458406027477.3267201805657
Trimmed Mean ( 15 / 20 )4313.1666666666752.356055174258182.3814294700209
Trimmed Mean ( 16 / 20 )4316.7857142857150.926504703644384.7650106640207
Trimmed Mean ( 17 / 20 )4321.0384615384649.383412997583987.499793943968
Trimmed Mean ( 18 / 20 )4324.4583333333347.621849021505490.808282798521
Trimmed Mean ( 19 / 20 )4326.4545454545546.107146400884493.834793154138
Trimmed Mean ( 20 / 20 )4327.6544.30315867318197.682651296368
Median4292.5
Midrange4013.5
Midmean - Weighted Average at Xnp4290.8064516129
Midmean - Weighted Average at X(n+1)p4313.16666666667
Midmean - Empirical Distribution Function4290.8064516129
Midmean - Empirical Distribution Function - Averaging4313.16666666667
Midmean - Empirical Distribution Function - Interpolation4313.16666666667
Midmean - Closest Observation4290.8064516129
Midmean - True Basic - Statistics Graphics Toolkit4313.16666666667
Midmean - MS Excel (old versions)4305.90625
Number of observations60

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 4242.01666666667 & 86.7495273979431 & 48.8995939679004 \tabularnewline
Geometric Mean & 4186.64647655668 &  &  \tabularnewline
Harmonic Mean & 4128.25766442641 &  &  \tabularnewline
Quadratic Mean & 4294.03175931432 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & 4249.76666666667 & 84.2275582163493 & 50.4557742936177 \tabularnewline
Winsorized Mean ( 2 / 20 ) & 4247.36666666667 & 83.4034031966528 & 50.9255798189915 \tabularnewline
Winsorized Mean ( 3 / 20 ) & 4243.71666666667 & 82.2335797208779 & 51.6056418931408 \tabularnewline
Winsorized Mean ( 4 / 20 ) & 4243.31666666667 & 81.9930288192412 & 51.7521639067795 \tabularnewline
Winsorized Mean ( 5 / 20 ) & 4245.06666666667 & 80.7026482762166 & 52.6013304066219 \tabularnewline
Winsorized Mean ( 6 / 20 ) & 4244.36666666667 & 78.3711759775586 & 54.1572410229244 \tabularnewline
Winsorized Mean ( 7 / 20 ) & 4245.53333333333 & 76.7474928892366 & 55.3182022435647 \tabularnewline
Winsorized Mean ( 8 / 20 ) & 4235.8 & 71.6070562757231 & 59.1533882316017 \tabularnewline
Winsorized Mean ( 9 / 20 ) & 4240.9 & 70.604927326015 & 60.0652130186019 \tabularnewline
Winsorized Mean ( 10 / 20 ) & 4237.4 & 69.4804171085776 & 60.9869683622967 \tabularnewline
Winsorized Mean ( 11 / 20 ) & 4240.33333333333 & 68.0278551566401 & 62.332309662999 \tabularnewline
Winsorized Mean ( 12 / 20 ) & 4254.33333333333 & 65.0520290101911 & 65.3989337160697 \tabularnewline
Winsorized Mean ( 13 / 20 ) & 4253.68333333333 & 62.4790699041116 & 68.0817326484146 \tabularnewline
Winsorized Mean ( 14 / 20 ) & 4255.08333333333 & 59.6010668565014 & 71.3927377101838 \tabularnewline
Winsorized Mean ( 15 / 20 ) & 4287.83333333333 & 49.5815835517109 & 86.4803627915868 \tabularnewline
Winsorized Mean ( 16 / 20 ) & 4287.3 & 47.2682709121906 & 90.701434963941 \tabularnewline
Winsorized Mean ( 17 / 20 ) & 4297.78333333333 & 45.1438572609746 & 95.2019520283357 \tabularnewline
Winsorized Mean ( 18 / 20 ) & 4311.28333333333 & 41.4919234647663 & 103.906567189982 \tabularnewline
Winsorized Mean ( 19 / 20 ) & 4318.88333333333 & 39.3012707465999 & 109.891696916873 \tabularnewline
Winsorized Mean ( 20 / 20 ) & 4317.21666666667 & 36.3126652327924 & 118.890107321783 \tabularnewline
Trimmed Mean ( 1 / 20 ) & 4249.89655172414 & 82.7384734248063 & 51.3654213790456 \tabularnewline
Trimmed Mean ( 2 / 20 ) & 4250.03571428571 & 80.8833373601955 & 52.5452565756424 \tabularnewline
Trimmed Mean ( 3 / 20 ) & 4251.51851851852 & 79.1108199389004 & 53.7413026663368 \tabularnewline
Trimmed Mean ( 4 / 20 ) & 4254.51923076923 & 77.4334896348611 & 54.9441753281621 \tabularnewline
Trimmed Mean ( 5 / 20 ) & 4257.88 & 75.388472241708 & 56.4791920222037 \tabularnewline
Trimmed Mean ( 6 / 20 ) & 4261.08333333333 & 73.2225902613824 & 58.1935618246031 \tabularnewline
Trimmed Mean ( 7 / 20 ) & 4264.71739130435 & 71.1682612796503 & 59.924428595304 \tabularnewline
Trimmed Mean ( 8 / 20 ) & 4268.45454545455 & 68.9686975488981 & 61.8897368973548 \tabularnewline
Trimmed Mean ( 9 / 20 ) & 4274.28571428571 & 67.5015402733395 & 63.321306402454 \tabularnewline
Trimmed Mean ( 10 / 20 ) & 4279.85 & 65.772359462245 & 65.0706472292019 \tabularnewline
Trimmed Mean ( 11 / 20 ) & 4286.55263157895 & 63.6823855292624 & 67.3114330745234 \tabularnewline
Trimmed Mean ( 12 / 20 ) & 4293.55555555556 & 61.1892256887437 & 70.1684897500737 \tabularnewline
Trimmed Mean ( 13 / 20 ) & 4299.32352941176 & 58.6047779711565 & 73.3613141837644 \tabularnewline
Trimmed Mean ( 14 / 20 ) & 4305.90625 & 55.684584060274 & 77.3267201805657 \tabularnewline
Trimmed Mean ( 15 / 20 ) & 4313.16666666667 & 52.3560551742581 & 82.3814294700209 \tabularnewline
Trimmed Mean ( 16 / 20 ) & 4316.78571428571 & 50.9265047036443 & 84.7650106640207 \tabularnewline
Trimmed Mean ( 17 / 20 ) & 4321.03846153846 & 49.3834129975839 & 87.499793943968 \tabularnewline
Trimmed Mean ( 18 / 20 ) & 4324.45833333333 & 47.6218490215054 & 90.808282798521 \tabularnewline
Trimmed Mean ( 19 / 20 ) & 4326.45454545455 & 46.1071464008844 & 93.834793154138 \tabularnewline
Trimmed Mean ( 20 / 20 ) & 4327.65 & 44.303158673181 & 97.682651296368 \tabularnewline
Median & 4292.5 &  &  \tabularnewline
Midrange & 4013.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 4290.8064516129 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 4313.16666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 4290.8064516129 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 4313.16666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 4313.16666666667 &  &  \tabularnewline
Midmean - Closest Observation & 4290.8064516129 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 4313.16666666667 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 4305.90625 &  &  \tabularnewline
Number of observations & 60 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17060&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]4242.01666666667[/C][C]86.7495273979431[/C][C]48.8995939679004[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]4186.64647655668[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]4128.25766442641[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]4294.03175931432[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]4249.76666666667[/C][C]84.2275582163493[/C][C]50.4557742936177[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]4247.36666666667[/C][C]83.4034031966528[/C][C]50.9255798189915[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]4243.71666666667[/C][C]82.2335797208779[/C][C]51.6056418931408[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]4243.31666666667[/C][C]81.9930288192412[/C][C]51.7521639067795[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]4245.06666666667[/C][C]80.7026482762166[/C][C]52.6013304066219[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]4244.36666666667[/C][C]78.3711759775586[/C][C]54.1572410229244[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]4245.53333333333[/C][C]76.7474928892366[/C][C]55.3182022435647[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]4235.8[/C][C]71.6070562757231[/C][C]59.1533882316017[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]4240.9[/C][C]70.604927326015[/C][C]60.0652130186019[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]4237.4[/C][C]69.4804171085776[/C][C]60.9869683622967[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]4240.33333333333[/C][C]68.0278551566401[/C][C]62.332309662999[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]4254.33333333333[/C][C]65.0520290101911[/C][C]65.3989337160697[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]4253.68333333333[/C][C]62.4790699041116[/C][C]68.0817326484146[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]4255.08333333333[/C][C]59.6010668565014[/C][C]71.3927377101838[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]4287.83333333333[/C][C]49.5815835517109[/C][C]86.4803627915868[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]4287.3[/C][C]47.2682709121906[/C][C]90.701434963941[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]4297.78333333333[/C][C]45.1438572609746[/C][C]95.2019520283357[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]4311.28333333333[/C][C]41.4919234647663[/C][C]103.906567189982[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]4318.88333333333[/C][C]39.3012707465999[/C][C]109.891696916873[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]4317.21666666667[/C][C]36.3126652327924[/C][C]118.890107321783[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]4249.89655172414[/C][C]82.7384734248063[/C][C]51.3654213790456[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]4250.03571428571[/C][C]80.8833373601955[/C][C]52.5452565756424[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]4251.51851851852[/C][C]79.1108199389004[/C][C]53.7413026663368[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]4254.51923076923[/C][C]77.4334896348611[/C][C]54.9441753281621[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]4257.88[/C][C]75.388472241708[/C][C]56.4791920222037[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]4261.08333333333[/C][C]73.2225902613824[/C][C]58.1935618246031[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]4264.71739130435[/C][C]71.1682612796503[/C][C]59.924428595304[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]4268.45454545455[/C][C]68.9686975488981[/C][C]61.8897368973548[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]4274.28571428571[/C][C]67.5015402733395[/C][C]63.321306402454[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]4279.85[/C][C]65.772359462245[/C][C]65.0706472292019[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]4286.55263157895[/C][C]63.6823855292624[/C][C]67.3114330745234[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]4293.55555555556[/C][C]61.1892256887437[/C][C]70.1684897500737[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]4299.32352941176[/C][C]58.6047779711565[/C][C]73.3613141837644[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]4305.90625[/C][C]55.684584060274[/C][C]77.3267201805657[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]4313.16666666667[/C][C]52.3560551742581[/C][C]82.3814294700209[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]4316.78571428571[/C][C]50.9265047036443[/C][C]84.7650106640207[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]4321.03846153846[/C][C]49.3834129975839[/C][C]87.499793943968[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]4324.45833333333[/C][C]47.6218490215054[/C][C]90.808282798521[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]4326.45454545455[/C][C]46.1071464008844[/C][C]93.834793154138[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]4327.65[/C][C]44.303158673181[/C][C]97.682651296368[/C][/ROW]
[ROW][C]Median[/C][C]4292.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]4013.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]4290.8064516129[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]4313.16666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]4290.8064516129[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]4313.16666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]4313.16666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]4290.8064516129[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]4313.16666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]4305.90625[/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=17060&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17060&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 Mean4242.0166666666786.749527397943148.8995939679004
Geometric Mean4186.64647655668
Harmonic Mean4128.25766442641
Quadratic Mean4294.03175931432
Winsorized Mean ( 1 / 20 )4249.7666666666784.227558216349350.4557742936177
Winsorized Mean ( 2 / 20 )4247.3666666666783.403403196652850.9255798189915
Winsorized Mean ( 3 / 20 )4243.7166666666782.233579720877951.6056418931408
Winsorized Mean ( 4 / 20 )4243.3166666666781.993028819241251.7521639067795
Winsorized Mean ( 5 / 20 )4245.0666666666780.702648276216652.6013304066219
Winsorized Mean ( 6 / 20 )4244.3666666666778.371175977558654.1572410229244
Winsorized Mean ( 7 / 20 )4245.5333333333376.747492889236655.3182022435647
Winsorized Mean ( 8 / 20 )4235.871.607056275723159.1533882316017
Winsorized Mean ( 9 / 20 )4240.970.60492732601560.0652130186019
Winsorized Mean ( 10 / 20 )4237.469.480417108577660.9869683622967
Winsorized Mean ( 11 / 20 )4240.3333333333368.027855156640162.332309662999
Winsorized Mean ( 12 / 20 )4254.3333333333365.052029010191165.3989337160697
Winsorized Mean ( 13 / 20 )4253.6833333333362.479069904111668.0817326484146
Winsorized Mean ( 14 / 20 )4255.0833333333359.601066856501471.3927377101838
Winsorized Mean ( 15 / 20 )4287.8333333333349.581583551710986.4803627915868
Winsorized Mean ( 16 / 20 )4287.347.268270912190690.701434963941
Winsorized Mean ( 17 / 20 )4297.7833333333345.143857260974695.2019520283357
Winsorized Mean ( 18 / 20 )4311.2833333333341.4919234647663103.906567189982
Winsorized Mean ( 19 / 20 )4318.8833333333339.3012707465999109.891696916873
Winsorized Mean ( 20 / 20 )4317.2166666666736.3126652327924118.890107321783
Trimmed Mean ( 1 / 20 )4249.8965517241482.738473424806351.3654213790456
Trimmed Mean ( 2 / 20 )4250.0357142857180.883337360195552.5452565756424
Trimmed Mean ( 3 / 20 )4251.5185185185279.110819938900453.7413026663368
Trimmed Mean ( 4 / 20 )4254.5192307692377.433489634861154.9441753281621
Trimmed Mean ( 5 / 20 )4257.8875.38847224170856.4791920222037
Trimmed Mean ( 6 / 20 )4261.0833333333373.222590261382458.1935618246031
Trimmed Mean ( 7 / 20 )4264.7173913043571.168261279650359.924428595304
Trimmed Mean ( 8 / 20 )4268.4545454545568.968697548898161.8897368973548
Trimmed Mean ( 9 / 20 )4274.2857142857167.501540273339563.321306402454
Trimmed Mean ( 10 / 20 )4279.8565.77235946224565.0706472292019
Trimmed Mean ( 11 / 20 )4286.5526315789563.682385529262467.3114330745234
Trimmed Mean ( 12 / 20 )4293.5555555555661.189225688743770.1684897500737
Trimmed Mean ( 13 / 20 )4299.3235294117658.604777971156573.3613141837644
Trimmed Mean ( 14 / 20 )4305.9062555.68458406027477.3267201805657
Trimmed Mean ( 15 / 20 )4313.1666666666752.356055174258182.3814294700209
Trimmed Mean ( 16 / 20 )4316.7857142857150.926504703644384.7650106640207
Trimmed Mean ( 17 / 20 )4321.0384615384649.383412997583987.499793943968
Trimmed Mean ( 18 / 20 )4324.4583333333347.621849021505490.808282798521
Trimmed Mean ( 19 / 20 )4326.4545454545546.107146400884493.834793154138
Trimmed Mean ( 20 / 20 )4327.6544.30315867318197.682651296368
Median4292.5
Midrange4013.5
Midmean - Weighted Average at Xnp4290.8064516129
Midmean - Weighted Average at X(n+1)p4313.16666666667
Midmean - Empirical Distribution Function4290.8064516129
Midmean - Empirical Distribution Function - Averaging4313.16666666667
Midmean - Empirical Distribution Function - Interpolation4313.16666666667
Midmean - Closest Observation4290.8064516129
Midmean - True Basic - Statistics Graphics Toolkit4313.16666666667
Midmean - MS Excel (old versions)4305.90625
Number of observations60



Parameters (Session):
par1 = grey ; par2 = grey ; par3 = TRUE ; par4 = bouwvergunningen ; par5 = werkelijk begonnen woningen ;
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')