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, 14 Dec 2008 10:03:16 -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/Dec/14/t1229274240n65o12xbn5pliwl.htm/, Retrieved Wed, 15 May 2024 01:35:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33484, Retrieved Wed, 15 May 2024 01:35:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact221
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Industriele produ...] [2008-12-14 16:49:51] [b82ef11dce0545f3fd4676ec3ebed828]
- RMP     [Central Tendency] [Central Tendency ...] [2008-12-14 17:03:16] [4b953869c7238aca4b6e0cfb0c5cddd6] [Current]
- RM        [Percentiles] [Percentiles - - ...] [2008-12-14 17:08:17] [b82ef11dce0545f3fd4676ec3ebed828]
- RM          [Tukey lambda PPCC Plot] [Tukey lambda PPCC...] [2008-12-14 17:26:43] [b82ef11dce0545f3fd4676ec3ebed828]
- RMP           [Blocked Bootstrap Plot - Central Tendency] [Blocked bootstrap...] [2008-12-14 17:29:20] [b82ef11dce0545f3fd4676ec3ebed828]
- RMP             [Harrell-Davis Quantiles] [Harrell-Davis Qua...] [2008-12-14 17:35:42] [b82ef11dce0545f3fd4676ec3ebed828]
- RMP               [Univariate Explorative Data Analysis] [Univariate EDA -...] [2008-12-14 17:39:39] [b82ef11dce0545f3fd4676ec3ebed828]
- RMP                 [Mean Plot] [Mean plot - Indus...] [2008-12-14 17:56:47] [b82ef11dce0545f3fd4676ec3ebed828]
- RM                    [Variance Reduction Matrix] [VRM - Industriele...] [2008-12-14 18:03:27] [b82ef11dce0545f3fd4676ec3ebed828]
- RM                      [Standard Deviation-Mean Plot] [SDMP - Industriel...] [2008-12-14 18:07:34] [b82ef11dce0545f3fd4676ec3ebed828]
- RM                        [(Partial) Autocorrelation Function] [(Partial) ACF - ...] [2008-12-14 18:14:08] [b82ef11dce0545f3fd4676ec3ebed828]
- RM                          [Spectral Analysis] [Spectrum - Indust...] [2008-12-14 18:16:42] [b82ef11dce0545f3fd4676ec3ebed828]
- RM                            [ARIMA Backward Selection] [ARIMA Backward Se...] [2008-12-14 18:25:02] [b82ef11dce0545f3fd4676ec3ebed828]
- RM                              [ARIMA Forecasting] [ARIMA Forecasting...] [2008-12-14 18:33:23] [b82ef11dce0545f3fd4676ec3ebed828]
Feedback Forum

Post a new message
Dataseries X:
97.4
97
105.4
102.7
98.1
104.5
87.4
89.9
109.8
111.7
98.6
96.9
95.1
97
112.7
102.9
97.4
111.4
87.4
96.8
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
80.9
95.7
113.2
105.9
108.8
102.3
99
100.7
115.5
100.7
109.9
114.6
85.4
100.5
114.8
116.5
112.9
102
106
105.3
118.8
106.1
109.3
117.2
92.5
104.2
112.5
122.4
113.3
100
110.7
112.8
109.8
117.3
109.1
115.9
96
99.8
117




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33484&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33484&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33484&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean104.5695652173911.0736066811595797.4002556545654
Geometric Mean104.185078938795
Harmonic Mean103.79039043635
Quadratic Mean104.943665356946
Winsorized Mean ( 1 / 23 )104.5826086956521.0425658486091100.312712942954
Winsorized Mean ( 2 / 23 )104.5971014492751.01917458832822102.629228247192
Winsorized Mean ( 3 / 23 )104.5927536231881.01838035418135102.704999358779
Winsorized Mean ( 4 / 23 )104.7260869565220.982148097616547106.629628678881
Winsorized Mean ( 5 / 23 )104.8782608695650.936220270779617112.023061391557
Winsorized Mean ( 6 / 23 )105.0086956521740.893332170183571117.547200422208
Winsorized Mean ( 7 / 23 )105.0188405797100.877567540657516119.670379445695
Winsorized Mean ( 8 / 23 )105.0072463768120.852208201431608123.217831276925
Winsorized Mean ( 9 / 23 )105.0072463768120.843657240717412124.466716231248
Winsorized Mean ( 10 / 23 )104.9492753623190.829418656474801126.533535920659
Winsorized Mean ( 11 / 23 )105.0449275362320.80451500916105130.569257677085
Winsorized Mean ( 12 / 23 )104.9579710144930.785293223392041133.654497311375
Winsorized Mean ( 13 / 23 )104.9579710144930.779521039574007134.644179805397
Winsorized Mean ( 14 / 23 )104.8971014492750.770137361709912136.205703897258
Winsorized Mean ( 15 / 23 )104.9623188405800.75384239221385139.236423852910
Winsorized Mean ( 16 / 23 )104.9391304347830.750306039836825139.861769548869
Winsorized Mean ( 17 / 23 )105.0623188405800.71775112179941146.377087613862
Winsorized Mean ( 18 / 23 )104.8536231884060.68653341634388152.729088915732
Winsorized Mean ( 19 / 23 )104.9086956521740.654734671374254160.230854174831
Winsorized Mean ( 20 / 23 )104.8217391304350.609168614206074172.073440236327
Winsorized Mean ( 21 / 23 )104.9434782608700.558311141779608187.965939433635
Winsorized Mean ( 22 / 23 )104.8797101449280.531836319639072197.2029857158
Winsorized Mean ( 23 / 23 )105.0130434782610.504995982374429207.948275121918
Trimmed Mean ( 1 / 23 )104.6567164179101.01207817570734103.407739569887
Trimmed Mean ( 2 / 23 )104.7353846153850.975444747600448107.371929443497
Trimmed Mean ( 3 / 23 )104.8111111111110.946530331129238110.731909653723
Trimmed Mean ( 4 / 23 )104.8934426229510.911735476127115115.048109204348
Trimmed Mean ( 5 / 23 )104.9423728813560.883464579536343118.785037127840
Trimmed Mean ( 6 / 23 )104.9578947368420.863942656277586121.487107939626
Trimmed Mean ( 7 / 23 )104.9472727272730.851909538776831123.190629932323
Trimmed Mean ( 8 / 23 )104.9339622641510.840540911077311124.840993319003
Trimmed Mean ( 9 / 23 )104.9215686274510.831847995755871126.130698352062
Trimmed Mean ( 10 / 23 )104.9081632653060.822064126462227127.615547118910
Trimmed Mean ( 11 / 23 )104.9081632653060.812030775983479129.192348822307
Trimmed Mean ( 12 / 23 )104.8822222222220.80371164793045130.497327607847
Trimmed Mean ( 13 / 23 )104.8720930232560.796033394274075131.743333605862
Trimmed Mean ( 14 / 23 )104.8609756097560.785958154170487133.418013482446
Trimmed Mean ( 15 / 23 )104.8564102564100.773487770816818135.563113228901
Trimmed Mean ( 16 / 23 )104.8432432432430.75930207938334138.078435565975
Trimmed Mean ( 17 / 23 )104.8314285714290.739529391903118141.754242250810
Trimmed Mean ( 18 / 23 )104.8030303030300.71949957420551145.661003925897
Trimmed Mean ( 19 / 23 )104.7967741935480.698823648604402149.961688335583
Trimmed Mean ( 20 / 23 )104.7827586206900.676998391291124154.775491298961
Trimmed Mean ( 21 / 23 )104.7777777777780.657746592007321159.298092990517
Trimmed Mean ( 22 / 23 )104.7777777777780.643456292221935162.835889623469
Trimmed Mean ( 23 / 23 )104.7391304347830.627648196141717166.875538046051
Median104.5
Midrange101.65
Midmean - Weighted Average at Xnp104.605882352941
Midmean - Weighted Average at X(n+1)p104.831428571429
Midmean - Empirical Distribution Function104.831428571429
Midmean - Empirical Distribution Function - Averaging104.831428571429
Midmean - Empirical Distribution Function - Interpolation104.831428571429
Midmean - Closest Observation104.429729729730
Midmean - True Basic - Statistics Graphics Toolkit104.831428571429
Midmean - MS Excel (old versions)104.831428571429
Number of observations69

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 104.569565217391 & 1.07360668115957 & 97.4002556545654 \tabularnewline
Geometric Mean & 104.185078938795 &  &  \tabularnewline
Harmonic Mean & 103.79039043635 &  &  \tabularnewline
Quadratic Mean & 104.943665356946 &  &  \tabularnewline
Winsorized Mean ( 1 / 23 ) & 104.582608695652 & 1.0425658486091 & 100.312712942954 \tabularnewline
Winsorized Mean ( 2 / 23 ) & 104.597101449275 & 1.01917458832822 & 102.629228247192 \tabularnewline
Winsorized Mean ( 3 / 23 ) & 104.592753623188 & 1.01838035418135 & 102.704999358779 \tabularnewline
Winsorized Mean ( 4 / 23 ) & 104.726086956522 & 0.982148097616547 & 106.629628678881 \tabularnewline
Winsorized Mean ( 5 / 23 ) & 104.878260869565 & 0.936220270779617 & 112.023061391557 \tabularnewline
Winsorized Mean ( 6 / 23 ) & 105.008695652174 & 0.893332170183571 & 117.547200422208 \tabularnewline
Winsorized Mean ( 7 / 23 ) & 105.018840579710 & 0.877567540657516 & 119.670379445695 \tabularnewline
Winsorized Mean ( 8 / 23 ) & 105.007246376812 & 0.852208201431608 & 123.217831276925 \tabularnewline
Winsorized Mean ( 9 / 23 ) & 105.007246376812 & 0.843657240717412 & 124.466716231248 \tabularnewline
Winsorized Mean ( 10 / 23 ) & 104.949275362319 & 0.829418656474801 & 126.533535920659 \tabularnewline
Winsorized Mean ( 11 / 23 ) & 105.044927536232 & 0.80451500916105 & 130.569257677085 \tabularnewline
Winsorized Mean ( 12 / 23 ) & 104.957971014493 & 0.785293223392041 & 133.654497311375 \tabularnewline
Winsorized Mean ( 13 / 23 ) & 104.957971014493 & 0.779521039574007 & 134.644179805397 \tabularnewline
Winsorized Mean ( 14 / 23 ) & 104.897101449275 & 0.770137361709912 & 136.205703897258 \tabularnewline
Winsorized Mean ( 15 / 23 ) & 104.962318840580 & 0.75384239221385 & 139.236423852910 \tabularnewline
Winsorized Mean ( 16 / 23 ) & 104.939130434783 & 0.750306039836825 & 139.861769548869 \tabularnewline
Winsorized Mean ( 17 / 23 ) & 105.062318840580 & 0.71775112179941 & 146.377087613862 \tabularnewline
Winsorized Mean ( 18 / 23 ) & 104.853623188406 & 0.68653341634388 & 152.729088915732 \tabularnewline
Winsorized Mean ( 19 / 23 ) & 104.908695652174 & 0.654734671374254 & 160.230854174831 \tabularnewline
Winsorized Mean ( 20 / 23 ) & 104.821739130435 & 0.609168614206074 & 172.073440236327 \tabularnewline
Winsorized Mean ( 21 / 23 ) & 104.943478260870 & 0.558311141779608 & 187.965939433635 \tabularnewline
Winsorized Mean ( 22 / 23 ) & 104.879710144928 & 0.531836319639072 & 197.2029857158 \tabularnewline
Winsorized Mean ( 23 / 23 ) & 105.013043478261 & 0.504995982374429 & 207.948275121918 \tabularnewline
Trimmed Mean ( 1 / 23 ) & 104.656716417910 & 1.01207817570734 & 103.407739569887 \tabularnewline
Trimmed Mean ( 2 / 23 ) & 104.735384615385 & 0.975444747600448 & 107.371929443497 \tabularnewline
Trimmed Mean ( 3 / 23 ) & 104.811111111111 & 0.946530331129238 & 110.731909653723 \tabularnewline
Trimmed Mean ( 4 / 23 ) & 104.893442622951 & 0.911735476127115 & 115.048109204348 \tabularnewline
Trimmed Mean ( 5 / 23 ) & 104.942372881356 & 0.883464579536343 & 118.785037127840 \tabularnewline
Trimmed Mean ( 6 / 23 ) & 104.957894736842 & 0.863942656277586 & 121.487107939626 \tabularnewline
Trimmed Mean ( 7 / 23 ) & 104.947272727273 & 0.851909538776831 & 123.190629932323 \tabularnewline
Trimmed Mean ( 8 / 23 ) & 104.933962264151 & 0.840540911077311 & 124.840993319003 \tabularnewline
Trimmed Mean ( 9 / 23 ) & 104.921568627451 & 0.831847995755871 & 126.130698352062 \tabularnewline
Trimmed Mean ( 10 / 23 ) & 104.908163265306 & 0.822064126462227 & 127.615547118910 \tabularnewline
Trimmed Mean ( 11 / 23 ) & 104.908163265306 & 0.812030775983479 & 129.192348822307 \tabularnewline
Trimmed Mean ( 12 / 23 ) & 104.882222222222 & 0.80371164793045 & 130.497327607847 \tabularnewline
Trimmed Mean ( 13 / 23 ) & 104.872093023256 & 0.796033394274075 & 131.743333605862 \tabularnewline
Trimmed Mean ( 14 / 23 ) & 104.860975609756 & 0.785958154170487 & 133.418013482446 \tabularnewline
Trimmed Mean ( 15 / 23 ) & 104.856410256410 & 0.773487770816818 & 135.563113228901 \tabularnewline
Trimmed Mean ( 16 / 23 ) & 104.843243243243 & 0.75930207938334 & 138.078435565975 \tabularnewline
Trimmed Mean ( 17 / 23 ) & 104.831428571429 & 0.739529391903118 & 141.754242250810 \tabularnewline
Trimmed Mean ( 18 / 23 ) & 104.803030303030 & 0.71949957420551 & 145.661003925897 \tabularnewline
Trimmed Mean ( 19 / 23 ) & 104.796774193548 & 0.698823648604402 & 149.961688335583 \tabularnewline
Trimmed Mean ( 20 / 23 ) & 104.782758620690 & 0.676998391291124 & 154.775491298961 \tabularnewline
Trimmed Mean ( 21 / 23 ) & 104.777777777778 & 0.657746592007321 & 159.298092990517 \tabularnewline
Trimmed Mean ( 22 / 23 ) & 104.777777777778 & 0.643456292221935 & 162.835889623469 \tabularnewline
Trimmed Mean ( 23 / 23 ) & 104.739130434783 & 0.627648196141717 & 166.875538046051 \tabularnewline
Median & 104.5 &  &  \tabularnewline
Midrange & 101.65 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 104.605882352941 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 104.831428571429 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 104.831428571429 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 104.831428571429 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 104.831428571429 &  &  \tabularnewline
Midmean - Closest Observation & 104.429729729730 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 104.831428571429 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 104.831428571429 &  &  \tabularnewline
Number of observations & 69 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33484&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]104.569565217391[/C][C]1.07360668115957[/C][C]97.4002556545654[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]104.185078938795[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]103.79039043635[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]104.943665356946[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 23 )[/C][C]104.582608695652[/C][C]1.0425658486091[/C][C]100.312712942954[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 23 )[/C][C]104.597101449275[/C][C]1.01917458832822[/C][C]102.629228247192[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 23 )[/C][C]104.592753623188[/C][C]1.01838035418135[/C][C]102.704999358779[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 23 )[/C][C]104.726086956522[/C][C]0.982148097616547[/C][C]106.629628678881[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 23 )[/C][C]104.878260869565[/C][C]0.936220270779617[/C][C]112.023061391557[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 23 )[/C][C]105.008695652174[/C][C]0.893332170183571[/C][C]117.547200422208[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 23 )[/C][C]105.018840579710[/C][C]0.877567540657516[/C][C]119.670379445695[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 23 )[/C][C]105.007246376812[/C][C]0.852208201431608[/C][C]123.217831276925[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 23 )[/C][C]105.007246376812[/C][C]0.843657240717412[/C][C]124.466716231248[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 23 )[/C][C]104.949275362319[/C][C]0.829418656474801[/C][C]126.533535920659[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 23 )[/C][C]105.044927536232[/C][C]0.80451500916105[/C][C]130.569257677085[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 23 )[/C][C]104.957971014493[/C][C]0.785293223392041[/C][C]133.654497311375[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 23 )[/C][C]104.957971014493[/C][C]0.779521039574007[/C][C]134.644179805397[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 23 )[/C][C]104.897101449275[/C][C]0.770137361709912[/C][C]136.205703897258[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 23 )[/C][C]104.962318840580[/C][C]0.75384239221385[/C][C]139.236423852910[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 23 )[/C][C]104.939130434783[/C][C]0.750306039836825[/C][C]139.861769548869[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 23 )[/C][C]105.062318840580[/C][C]0.71775112179941[/C][C]146.377087613862[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 23 )[/C][C]104.853623188406[/C][C]0.68653341634388[/C][C]152.729088915732[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 23 )[/C][C]104.908695652174[/C][C]0.654734671374254[/C][C]160.230854174831[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 23 )[/C][C]104.821739130435[/C][C]0.609168614206074[/C][C]172.073440236327[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 23 )[/C][C]104.943478260870[/C][C]0.558311141779608[/C][C]187.965939433635[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 23 )[/C][C]104.879710144928[/C][C]0.531836319639072[/C][C]197.2029857158[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 23 )[/C][C]105.013043478261[/C][C]0.504995982374429[/C][C]207.948275121918[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 23 )[/C][C]104.656716417910[/C][C]1.01207817570734[/C][C]103.407739569887[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 23 )[/C][C]104.735384615385[/C][C]0.975444747600448[/C][C]107.371929443497[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 23 )[/C][C]104.811111111111[/C][C]0.946530331129238[/C][C]110.731909653723[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 23 )[/C][C]104.893442622951[/C][C]0.911735476127115[/C][C]115.048109204348[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 23 )[/C][C]104.942372881356[/C][C]0.883464579536343[/C][C]118.785037127840[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 23 )[/C][C]104.957894736842[/C][C]0.863942656277586[/C][C]121.487107939626[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 23 )[/C][C]104.947272727273[/C][C]0.851909538776831[/C][C]123.190629932323[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 23 )[/C][C]104.933962264151[/C][C]0.840540911077311[/C][C]124.840993319003[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 23 )[/C][C]104.921568627451[/C][C]0.831847995755871[/C][C]126.130698352062[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 23 )[/C][C]104.908163265306[/C][C]0.822064126462227[/C][C]127.615547118910[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 23 )[/C][C]104.908163265306[/C][C]0.812030775983479[/C][C]129.192348822307[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 23 )[/C][C]104.882222222222[/C][C]0.80371164793045[/C][C]130.497327607847[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 23 )[/C][C]104.872093023256[/C][C]0.796033394274075[/C][C]131.743333605862[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 23 )[/C][C]104.860975609756[/C][C]0.785958154170487[/C][C]133.418013482446[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 23 )[/C][C]104.856410256410[/C][C]0.773487770816818[/C][C]135.563113228901[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 23 )[/C][C]104.843243243243[/C][C]0.75930207938334[/C][C]138.078435565975[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 23 )[/C][C]104.831428571429[/C][C]0.739529391903118[/C][C]141.754242250810[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 23 )[/C][C]104.803030303030[/C][C]0.71949957420551[/C][C]145.661003925897[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 23 )[/C][C]104.796774193548[/C][C]0.698823648604402[/C][C]149.961688335583[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 23 )[/C][C]104.782758620690[/C][C]0.676998391291124[/C][C]154.775491298961[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 23 )[/C][C]104.777777777778[/C][C]0.657746592007321[/C][C]159.298092990517[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 23 )[/C][C]104.777777777778[/C][C]0.643456292221935[/C][C]162.835889623469[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 23 )[/C][C]104.739130434783[/C][C]0.627648196141717[/C][C]166.875538046051[/C][/ROW]
[ROW][C]Median[/C][C]104.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]101.65[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]104.605882352941[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]104.831428571429[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]104.831428571429[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]104.831428571429[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]104.831428571429[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]104.429729729730[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]104.831428571429[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]104.831428571429[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]69[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33484&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33484&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 Mean104.5695652173911.0736066811595797.4002556545654
Geometric Mean104.185078938795
Harmonic Mean103.79039043635
Quadratic Mean104.943665356946
Winsorized Mean ( 1 / 23 )104.5826086956521.0425658486091100.312712942954
Winsorized Mean ( 2 / 23 )104.5971014492751.01917458832822102.629228247192
Winsorized Mean ( 3 / 23 )104.5927536231881.01838035418135102.704999358779
Winsorized Mean ( 4 / 23 )104.7260869565220.982148097616547106.629628678881
Winsorized Mean ( 5 / 23 )104.8782608695650.936220270779617112.023061391557
Winsorized Mean ( 6 / 23 )105.0086956521740.893332170183571117.547200422208
Winsorized Mean ( 7 / 23 )105.0188405797100.877567540657516119.670379445695
Winsorized Mean ( 8 / 23 )105.0072463768120.852208201431608123.217831276925
Winsorized Mean ( 9 / 23 )105.0072463768120.843657240717412124.466716231248
Winsorized Mean ( 10 / 23 )104.9492753623190.829418656474801126.533535920659
Winsorized Mean ( 11 / 23 )105.0449275362320.80451500916105130.569257677085
Winsorized Mean ( 12 / 23 )104.9579710144930.785293223392041133.654497311375
Winsorized Mean ( 13 / 23 )104.9579710144930.779521039574007134.644179805397
Winsorized Mean ( 14 / 23 )104.8971014492750.770137361709912136.205703897258
Winsorized Mean ( 15 / 23 )104.9623188405800.75384239221385139.236423852910
Winsorized Mean ( 16 / 23 )104.9391304347830.750306039836825139.861769548869
Winsorized Mean ( 17 / 23 )105.0623188405800.71775112179941146.377087613862
Winsorized Mean ( 18 / 23 )104.8536231884060.68653341634388152.729088915732
Winsorized Mean ( 19 / 23 )104.9086956521740.654734671374254160.230854174831
Winsorized Mean ( 20 / 23 )104.8217391304350.609168614206074172.073440236327
Winsorized Mean ( 21 / 23 )104.9434782608700.558311141779608187.965939433635
Winsorized Mean ( 22 / 23 )104.8797101449280.531836319639072197.2029857158
Winsorized Mean ( 23 / 23 )105.0130434782610.504995982374429207.948275121918
Trimmed Mean ( 1 / 23 )104.6567164179101.01207817570734103.407739569887
Trimmed Mean ( 2 / 23 )104.7353846153850.975444747600448107.371929443497
Trimmed Mean ( 3 / 23 )104.8111111111110.946530331129238110.731909653723
Trimmed Mean ( 4 / 23 )104.8934426229510.911735476127115115.048109204348
Trimmed Mean ( 5 / 23 )104.9423728813560.883464579536343118.785037127840
Trimmed Mean ( 6 / 23 )104.9578947368420.863942656277586121.487107939626
Trimmed Mean ( 7 / 23 )104.9472727272730.851909538776831123.190629932323
Trimmed Mean ( 8 / 23 )104.9339622641510.840540911077311124.840993319003
Trimmed Mean ( 9 / 23 )104.9215686274510.831847995755871126.130698352062
Trimmed Mean ( 10 / 23 )104.9081632653060.822064126462227127.615547118910
Trimmed Mean ( 11 / 23 )104.9081632653060.812030775983479129.192348822307
Trimmed Mean ( 12 / 23 )104.8822222222220.80371164793045130.497327607847
Trimmed Mean ( 13 / 23 )104.8720930232560.796033394274075131.743333605862
Trimmed Mean ( 14 / 23 )104.8609756097560.785958154170487133.418013482446
Trimmed Mean ( 15 / 23 )104.8564102564100.773487770816818135.563113228901
Trimmed Mean ( 16 / 23 )104.8432432432430.75930207938334138.078435565975
Trimmed Mean ( 17 / 23 )104.8314285714290.739529391903118141.754242250810
Trimmed Mean ( 18 / 23 )104.8030303030300.71949957420551145.661003925897
Trimmed Mean ( 19 / 23 )104.7967741935480.698823648604402149.961688335583
Trimmed Mean ( 20 / 23 )104.7827586206900.676998391291124154.775491298961
Trimmed Mean ( 21 / 23 )104.7777777777780.657746592007321159.298092990517
Trimmed Mean ( 22 / 23 )104.7777777777780.643456292221935162.835889623469
Trimmed Mean ( 23 / 23 )104.7391304347830.627648196141717166.875538046051
Median104.5
Midrange101.65
Midmean - Weighted Average at Xnp104.605882352941
Midmean - Weighted Average at X(n+1)p104.831428571429
Midmean - Empirical Distribution Function104.831428571429
Midmean - Empirical Distribution Function - Averaging104.831428571429
Midmean - Empirical Distribution Function - Interpolation104.831428571429
Midmean - Closest Observation104.429729729730
Midmean - True Basic - Statistics Graphics Toolkit104.831428571429
Midmean - MS Excel (old versions)104.831428571429
Number of observations69



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
geomean <- function(x) {
return(exp(mean(log(x))))
}
harmean <- function(x) {
return(1/mean(1/x))
}
quamean <- function(x) {
return(sqrt(mean(x*x)))
}
winmean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
win <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n
win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn
}
return(win)
}
trimean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
tri <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
tri[j,1] <- mean(x,trim=j/n)
tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2)
}
return(tri)
}
midrange <- function(x) {
return((max(x)+min(x))/2)
}
q1 <- function(data,n,p,i,f) {
np <- n*p;
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q2 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q3 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
q4 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- (data[i]+data[i+1])/2
} else {
qvalue <- data[i+1]
}
}
q5 <- function(data,n,p,i,f) {
np <- (n-1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i+1]
} else {
qvalue <- data[i+1] + f*(data[i+2]-data[i+1])
}
}
q6 <- function(data,n,p,i,f) {
np <- n*p+0.5
i <<- floor(np)
f <<- np - i
qvalue <- data[i]
}
q7 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- f*data[i] + (1-f)*data[i+1]
}
}
q8 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
if (f == 0.5) {
qvalue <- (data[i]+data[i+1])/2
} else {
if (f < 0.5) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
}
}
midmean <- function(x,def) {
x <-sort(x[!is.na(x)])
n<-length(x)
if (def==1) {
qvalue1 <- q1(x,n,0.25,i,f)
qvalue3 <- q1(x,n,0.75,i,f)
}
if (def==2) {
qvalue1 <- q2(x,n,0.25,i,f)
qvalue3 <- q2(x,n,0.75,i,f)
}
if (def==3) {
qvalue1 <- q3(x,n,0.25,i,f)
qvalue3 <- q3(x,n,0.75,i,f)
}
if (def==4) {
qvalue1 <- q4(x,n,0.25,i,f)
qvalue3 <- q4(x,n,0.75,i,f)
}
if (def==5) {
qvalue1 <- q5(x,n,0.25,i,f)
qvalue3 <- q5(x,n,0.75,i,f)
}
if (def==6) {
qvalue1 <- q6(x,n,0.25,i,f)
qvalue3 <- q6(x,n,0.75,i,f)
}
if (def==7) {
qvalue1 <- q7(x,n,0.25,i,f)
qvalue3 <- q7(x,n,0.75,i,f)
}
if (def==8) {
qvalue1 <- q8(x,n,0.25,i,f)
qvalue3 <- q8(x,n,0.75,i,f)
}
midm <- 0
myn <- 0
roundno4 <- round(n/4)
round3no4 <- round(3*n/4)
for (i in 1:n) {
if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){
midm = midm + x[i]
myn = myn + 1
}
}
midm = midm / myn
return(midm)
}
(arm <- mean(x))
sqrtn <- sqrt(length(x))
(armse <- sd(x) / sqrtn)
(armose <- arm / armse)
(geo <- geomean(x))
(har <- harmean(x))
(qua <- quamean(x))
(win <- winmean(x))
(tri <- trimean(x))
(midr <- midrange(x))
midm <- array(NA,dim=8)
for (j in 1:8) midm[j] <- midmean(x,j)
midm
bitmap(file='test1.png')
lb <- win[,1] - 2*win[,2]
ub <- win[,1] + 2*win[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
bitmap(file='test2.png')
lb <- tri[,1] - 2*tri[,2]
ub <- tri[,1] + 2*tri[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Measure',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.element(a,'S.E.',header=TRUE)
a<-table.element(a,'Value/S.E.',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE)
a<-table.element(a,arm)
a<-table.element(a,hyperlink('arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean'))
a<-table.element(a,armose)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE)
a<-table.element(a,geo)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE)
a<-table.element(a,har)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE)
a<-table.element(a,qua)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
for (j in 1:length(win[,1])) {
a<-table.row.start(a)
mylabel <- paste('Winsorized Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(win[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE)
a<-table.element(a,win[j,1])
a<-table.element(a,win[j,2])
a<-table.element(a,win[j,1]/win[j,2])
a<-table.row.end(a)
}
for (j in 1:length(tri[,1])) {
a<-table.row.start(a)
mylabel <- paste('Trimmed Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(tri[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE)
a<-table.element(a,tri[j,1])
a<-table.element(a,tri[j,2])
a<-table.element(a,tri[j,1]/tri[j,2])
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,hyperlink('median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE)
a<-table.element(a,median(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE)
a<-table.element(a,midr)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_1.htm','Weighted Average at Xnp',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[2])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_3.htm','Empirical Distribution Function',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[3])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[4])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[5])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_6.htm','Closest Observation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[6])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[7])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_8.htm','MS Excel (old versions)',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[8])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')