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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 computationThu, 15 Oct 2009 16:21:41 -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/2009/Oct/16/t12556453447q1a9f0w3wj61e0.htm/, Retrieved Tue, 30 Apr 2024 01:39:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=46904, Retrieved Tue, 30 Apr 2024 01:39:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact201
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [central tendensy] [2009-10-15 22:21:41] [ea241b681aafed79da4b5b99fad98471] [Current]
- RM D    [Univariate Data Series] [run sequence plot] [2009-10-16 11:01:15] [cd6314e7e707a6546bd4604c9d1f2b69]
-    D    [Central Tendency] [central tendensy] [2009-10-16 11:04:07] [cd6314e7e707a6546bd4604c9d1f2b69]
- RMPD    [Kernel Density Estimation] [kernel-density] [2009-10-16 11:06:13] [cd6314e7e707a6546bd4604c9d1f2b69]
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Dataseries X:
-346091
-347267
-345867
-339554
-336425
-339056
-352054
-350456
-369289
-366864
-360592
-358237
-355622
-359025
-357244
-351422
-350314
-349576
-364289
-363039
-379608
-371003
-366159
-365336
-374131
-370759
-367189
-359434
-361633
-361485
-379519
-385173
-389336
-378830
-367820
-362678
-365995
-363168
-353567
-353311
-343736
-330609
-353062
-362203
-359141
-353594
-343402
-342961
-347221
-343379
-330708
-330631
-318356
-319466
-341849
-346521
-343615
-336812
-335039
-338104
-341810
-343412
-344759
-347629
-337592
-340905
-363038
-369695
-366397




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=46904&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=46904&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=46904&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 Mean-3538271792.98517934963-197.339612214945
Geometric MeanNaN
Harmonic Mean-353207.645753870
Quadratic Mean354135.781935445
Winsorized Mean ( 1 / 23 )-353782.7536231881771.70236736284-199.685206804679
Winsorized Mean ( 2 / 23 )-353944.4347826091652.19702995112-214.22652889836
Winsorized Mean ( 3 / 23 )-353941.5217391301651.11568038986-214.365065962887
Winsorized Mean ( 4 / 23 )-353906.0434782611641.17833430542-215.641430355612
Winsorized Mean ( 5 / 23 )-353879.3768115941507.72391593848-234.710992556832
Winsorized Mean ( 6 / 23 )-353727.8985507251434.94423005549-246.509858112776
Winsorized Mean ( 7 / 23 )-353742.4057971011423.66316622915-248.473384848509
Winsorized Mean ( 8 / 23 )-353709.4782608701386.72088554662-255.068977432645
Winsorized Mean ( 9 / 23 )-353723.3043478261366.47539051508-258.858159322205
Winsorized Mean ( 10 / 23 )-353648.3768115941308.75991559464-270.216387740538
Winsorized Mean ( 11 / 23 )-353627.1739130431279.98363643042-276.274761526819
Winsorized Mean ( 12 / 23 )-353805.6086956521234.11116100725-286.688606241016
Winsorized Mean ( 13 / 23 )-353888.1304347831194.70313739154-296.214280651714
Winsorized Mean ( 14 / 23 )-353847.7536231881186.12306330977-298.322968812198
Winsorized Mean ( 15 / 23 )-354053.840579711145.46154168883-309.092734844424
Winsorized Mean ( 16 / 23 )-353997.9565217391108.52168814706-319.34238211745
Winsorized Mean ( 17 / 23 )-353745.6666666671069.61063970682-330.723773244841
Winsorized Mean ( 18 / 23 )-353455.840579711027.70414586766-343.927619637358
Winsorized Mean ( 19 / 23 )-353476.2173913041014.76317015573-348.333707595102
Winsorized Mean ( 20 / 23 )-3535111009.72031675772-350.107840887214
Winsorized Mean ( 21 / 23 )-353712.782608696950.782328493902-372.022882639183
Winsorized Mean ( 22 / 23 )-353914.608695652881.60865044496-401.441851230732
Winsorized Mean ( 23 / 23 )-353799.275362319845.509399891197-418.445111796329
Trimmed Mean ( 1 / 23 )-353826.4328358211685.64999940654-209.905041355199
Trimmed Mean ( 2 / 23 )-353872.81581.24181651881-223.794233306498
Trimmed Mean ( 3 / 23 )-353833.5714285711534.52776721820-230.581406858477
Trimmed Mean ( 4 / 23 )-353792.8688524591478.40108570210-239.307771263196
Trimmed Mean ( 5 / 23 )-353759.7796610171413.77105073937-250.224235017408
Trimmed Mean ( 6 / 23 )-353730.8245614031379.47445318652-256.424338808380
Trimmed Mean ( 7 / 23 )-353731.4363636361357.90440988047-260.498039324266
Trimmed Mean ( 8 / 23 )-353729.3962264151333.41973308166-265.279857085145
Trimmed Mean ( 9 / 23 )-353732.7647058821311.31933520891-269.753335597335
Trimmed Mean ( 10 / 23 )-353734.2448979591287.46888659672-274.751684161483
Trimmed Mean ( 11 / 23 )-353734.2448979591269.57425613459-278.624305107568
Trimmed Mean ( 12 / 23 )-353763.5333333331251.78888464356-282.6063864867
Trimmed Mean ( 13 / 23 )-353757.9069767441237.48348034835-285.868791458261
Trimmed Mean ( 14 / 23 )-353741.0487804881225.52503479779-288.6444901053
Trimmed Mean ( 15 / 23 )-353727.5641025641209.36003575422-292.491527456471
Trimmed Mean ( 16 / 23 )-3536871194.65521619653-296.057804130338
Trimmed Mean ( 17 / 23 )-353648.6857142861180.73698732160-299.515209154671
Trimmed Mean ( 18 / 23 )-353636.7575757581168.07714388757-302.751200489028
Trimmed Mean ( 19 / 23 )-353659.1290322581157.21443700313-305.612441154934
Trimmed Mean ( 20 / 23 )-353682.0344827591140.6739878288-310.064083389830
Trimmed Mean ( 21 / 23 )-353703.8888888891113.27957715216-317.713444266792
Trimmed Mean ( 22 / 23 )-353703.8888888891087.43354819195-325.26483064366
Trimmed Mean ( 23 / 23 )-353673.8260869571066.77690777276-331.534947475911
Median-353311
Midrange-353846
Midmean - Weighted Average at Xnp-353950.058823529
Midmean - Weighted Average at X(n+1)p-353648.685714286
Midmean - Empirical Distribution Function-353648.685714286
Midmean - Empirical Distribution Function - Averaging-353648.685714286
Midmean - Empirical Distribution Function - Interpolation-353648.685714286
Midmean - Closest Observation-353973.333333333
Midmean - True Basic - Statistics Graphics Toolkit-353648.685714286
Midmean - MS Excel (old versions)-353648.685714286
Number of observations69

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -353827 & 1792.98517934963 & -197.339612214945 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & -353207.645753870 &  &  \tabularnewline
Quadratic Mean & 354135.781935445 &  &  \tabularnewline
Winsorized Mean ( 1 / 23 ) & -353782.753623188 & 1771.70236736284 & -199.685206804679 \tabularnewline
Winsorized Mean ( 2 / 23 ) & -353944.434782609 & 1652.19702995112 & -214.22652889836 \tabularnewline
Winsorized Mean ( 3 / 23 ) & -353941.521739130 & 1651.11568038986 & -214.365065962887 \tabularnewline
Winsorized Mean ( 4 / 23 ) & -353906.043478261 & 1641.17833430542 & -215.641430355612 \tabularnewline
Winsorized Mean ( 5 / 23 ) & -353879.376811594 & 1507.72391593848 & -234.710992556832 \tabularnewline
Winsorized Mean ( 6 / 23 ) & -353727.898550725 & 1434.94423005549 & -246.509858112776 \tabularnewline
Winsorized Mean ( 7 / 23 ) & -353742.405797101 & 1423.66316622915 & -248.473384848509 \tabularnewline
Winsorized Mean ( 8 / 23 ) & -353709.478260870 & 1386.72088554662 & -255.068977432645 \tabularnewline
Winsorized Mean ( 9 / 23 ) & -353723.304347826 & 1366.47539051508 & -258.858159322205 \tabularnewline
Winsorized Mean ( 10 / 23 ) & -353648.376811594 & 1308.75991559464 & -270.216387740538 \tabularnewline
Winsorized Mean ( 11 / 23 ) & -353627.173913043 & 1279.98363643042 & -276.274761526819 \tabularnewline
Winsorized Mean ( 12 / 23 ) & -353805.608695652 & 1234.11116100725 & -286.688606241016 \tabularnewline
Winsorized Mean ( 13 / 23 ) & -353888.130434783 & 1194.70313739154 & -296.214280651714 \tabularnewline
Winsorized Mean ( 14 / 23 ) & -353847.753623188 & 1186.12306330977 & -298.322968812198 \tabularnewline
Winsorized Mean ( 15 / 23 ) & -354053.84057971 & 1145.46154168883 & -309.092734844424 \tabularnewline
Winsorized Mean ( 16 / 23 ) & -353997.956521739 & 1108.52168814706 & -319.34238211745 \tabularnewline
Winsorized Mean ( 17 / 23 ) & -353745.666666667 & 1069.61063970682 & -330.723773244841 \tabularnewline
Winsorized Mean ( 18 / 23 ) & -353455.84057971 & 1027.70414586766 & -343.927619637358 \tabularnewline
Winsorized Mean ( 19 / 23 ) & -353476.217391304 & 1014.76317015573 & -348.333707595102 \tabularnewline
Winsorized Mean ( 20 / 23 ) & -353511 & 1009.72031675772 & -350.107840887214 \tabularnewline
Winsorized Mean ( 21 / 23 ) & -353712.782608696 & 950.782328493902 & -372.022882639183 \tabularnewline
Winsorized Mean ( 22 / 23 ) & -353914.608695652 & 881.60865044496 & -401.441851230732 \tabularnewline
Winsorized Mean ( 23 / 23 ) & -353799.275362319 & 845.509399891197 & -418.445111796329 \tabularnewline
Trimmed Mean ( 1 / 23 ) & -353826.432835821 & 1685.64999940654 & -209.905041355199 \tabularnewline
Trimmed Mean ( 2 / 23 ) & -353872.8 & 1581.24181651881 & -223.794233306498 \tabularnewline
Trimmed Mean ( 3 / 23 ) & -353833.571428571 & 1534.52776721820 & -230.581406858477 \tabularnewline
Trimmed Mean ( 4 / 23 ) & -353792.868852459 & 1478.40108570210 & -239.307771263196 \tabularnewline
Trimmed Mean ( 5 / 23 ) & -353759.779661017 & 1413.77105073937 & -250.224235017408 \tabularnewline
Trimmed Mean ( 6 / 23 ) & -353730.824561403 & 1379.47445318652 & -256.424338808380 \tabularnewline
Trimmed Mean ( 7 / 23 ) & -353731.436363636 & 1357.90440988047 & -260.498039324266 \tabularnewline
Trimmed Mean ( 8 / 23 ) & -353729.396226415 & 1333.41973308166 & -265.279857085145 \tabularnewline
Trimmed Mean ( 9 / 23 ) & -353732.764705882 & 1311.31933520891 & -269.753335597335 \tabularnewline
Trimmed Mean ( 10 / 23 ) & -353734.244897959 & 1287.46888659672 & -274.751684161483 \tabularnewline
Trimmed Mean ( 11 / 23 ) & -353734.244897959 & 1269.57425613459 & -278.624305107568 \tabularnewline
Trimmed Mean ( 12 / 23 ) & -353763.533333333 & 1251.78888464356 & -282.6063864867 \tabularnewline
Trimmed Mean ( 13 / 23 ) & -353757.906976744 & 1237.48348034835 & -285.868791458261 \tabularnewline
Trimmed Mean ( 14 / 23 ) & -353741.048780488 & 1225.52503479779 & -288.6444901053 \tabularnewline
Trimmed Mean ( 15 / 23 ) & -353727.564102564 & 1209.36003575422 & -292.491527456471 \tabularnewline
Trimmed Mean ( 16 / 23 ) & -353687 & 1194.65521619653 & -296.057804130338 \tabularnewline
Trimmed Mean ( 17 / 23 ) & -353648.685714286 & 1180.73698732160 & -299.515209154671 \tabularnewline
Trimmed Mean ( 18 / 23 ) & -353636.757575758 & 1168.07714388757 & -302.751200489028 \tabularnewline
Trimmed Mean ( 19 / 23 ) & -353659.129032258 & 1157.21443700313 & -305.612441154934 \tabularnewline
Trimmed Mean ( 20 / 23 ) & -353682.034482759 & 1140.6739878288 & -310.064083389830 \tabularnewline
Trimmed Mean ( 21 / 23 ) & -353703.888888889 & 1113.27957715216 & -317.713444266792 \tabularnewline
Trimmed Mean ( 22 / 23 ) & -353703.888888889 & 1087.43354819195 & -325.26483064366 \tabularnewline
Trimmed Mean ( 23 / 23 ) & -353673.826086957 & 1066.77690777276 & -331.534947475911 \tabularnewline
Median & -353311 &  &  \tabularnewline
Midrange & -353846 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -353950.058823529 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -353648.685714286 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -353648.685714286 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -353648.685714286 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -353648.685714286 &  &  \tabularnewline
Midmean - Closest Observation & -353973.333333333 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -353648.685714286 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -353648.685714286 &  &  \tabularnewline
Number of observations & 69 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=46904&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]-353827[/C][C]1792.98517934963[/C][C]-197.339612214945[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]-353207.645753870[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]354135.781935445[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 23 )[/C][C]-353782.753623188[/C][C]1771.70236736284[/C][C]-199.685206804679[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 23 )[/C][C]-353944.434782609[/C][C]1652.19702995112[/C][C]-214.22652889836[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 23 )[/C][C]-353941.521739130[/C][C]1651.11568038986[/C][C]-214.365065962887[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 23 )[/C][C]-353906.043478261[/C][C]1641.17833430542[/C][C]-215.641430355612[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 23 )[/C][C]-353879.376811594[/C][C]1507.72391593848[/C][C]-234.710992556832[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 23 )[/C][C]-353727.898550725[/C][C]1434.94423005549[/C][C]-246.509858112776[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 23 )[/C][C]-353742.405797101[/C][C]1423.66316622915[/C][C]-248.473384848509[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 23 )[/C][C]-353709.478260870[/C][C]1386.72088554662[/C][C]-255.068977432645[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 23 )[/C][C]-353723.304347826[/C][C]1366.47539051508[/C][C]-258.858159322205[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 23 )[/C][C]-353648.376811594[/C][C]1308.75991559464[/C][C]-270.216387740538[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 23 )[/C][C]-353627.173913043[/C][C]1279.98363643042[/C][C]-276.274761526819[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 23 )[/C][C]-353805.608695652[/C][C]1234.11116100725[/C][C]-286.688606241016[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 23 )[/C][C]-353888.130434783[/C][C]1194.70313739154[/C][C]-296.214280651714[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 23 )[/C][C]-353847.753623188[/C][C]1186.12306330977[/C][C]-298.322968812198[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 23 )[/C][C]-354053.84057971[/C][C]1145.46154168883[/C][C]-309.092734844424[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 23 )[/C][C]-353997.956521739[/C][C]1108.52168814706[/C][C]-319.34238211745[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 23 )[/C][C]-353745.666666667[/C][C]1069.61063970682[/C][C]-330.723773244841[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 23 )[/C][C]-353455.84057971[/C][C]1027.70414586766[/C][C]-343.927619637358[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 23 )[/C][C]-353476.217391304[/C][C]1014.76317015573[/C][C]-348.333707595102[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 23 )[/C][C]-353511[/C][C]1009.72031675772[/C][C]-350.107840887214[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 23 )[/C][C]-353712.782608696[/C][C]950.782328493902[/C][C]-372.022882639183[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 23 )[/C][C]-353914.608695652[/C][C]881.60865044496[/C][C]-401.441851230732[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 23 )[/C][C]-353799.275362319[/C][C]845.509399891197[/C][C]-418.445111796329[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 23 )[/C][C]-353826.432835821[/C][C]1685.64999940654[/C][C]-209.905041355199[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 23 )[/C][C]-353872.8[/C][C]1581.24181651881[/C][C]-223.794233306498[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 23 )[/C][C]-353833.571428571[/C][C]1534.52776721820[/C][C]-230.581406858477[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 23 )[/C][C]-353792.868852459[/C][C]1478.40108570210[/C][C]-239.307771263196[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 23 )[/C][C]-353759.779661017[/C][C]1413.77105073937[/C][C]-250.224235017408[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 23 )[/C][C]-353730.824561403[/C][C]1379.47445318652[/C][C]-256.424338808380[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 23 )[/C][C]-353731.436363636[/C][C]1357.90440988047[/C][C]-260.498039324266[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 23 )[/C][C]-353729.396226415[/C][C]1333.41973308166[/C][C]-265.279857085145[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 23 )[/C][C]-353732.764705882[/C][C]1311.31933520891[/C][C]-269.753335597335[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 23 )[/C][C]-353734.244897959[/C][C]1287.46888659672[/C][C]-274.751684161483[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 23 )[/C][C]-353734.244897959[/C][C]1269.57425613459[/C][C]-278.624305107568[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 23 )[/C][C]-353763.533333333[/C][C]1251.78888464356[/C][C]-282.6063864867[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 23 )[/C][C]-353757.906976744[/C][C]1237.48348034835[/C][C]-285.868791458261[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 23 )[/C][C]-353741.048780488[/C][C]1225.52503479779[/C][C]-288.6444901053[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 23 )[/C][C]-353727.564102564[/C][C]1209.36003575422[/C][C]-292.491527456471[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 23 )[/C][C]-353687[/C][C]1194.65521619653[/C][C]-296.057804130338[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 23 )[/C][C]-353648.685714286[/C][C]1180.73698732160[/C][C]-299.515209154671[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 23 )[/C][C]-353636.757575758[/C][C]1168.07714388757[/C][C]-302.751200489028[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 23 )[/C][C]-353659.129032258[/C][C]1157.21443700313[/C][C]-305.612441154934[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 23 )[/C][C]-353682.034482759[/C][C]1140.6739878288[/C][C]-310.064083389830[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 23 )[/C][C]-353703.888888889[/C][C]1113.27957715216[/C][C]-317.713444266792[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 23 )[/C][C]-353703.888888889[/C][C]1087.43354819195[/C][C]-325.26483064366[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 23 )[/C][C]-353673.826086957[/C][C]1066.77690777276[/C][C]-331.534947475911[/C][/ROW]
[ROW][C]Median[/C][C]-353311[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-353846[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-353950.058823529[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-353648.685714286[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-353648.685714286[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-353648.685714286[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-353648.685714286[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-353973.333333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-353648.685714286[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-353648.685714286[/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=46904&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=46904&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 Mean-3538271792.98517934963-197.339612214945
Geometric MeanNaN
Harmonic Mean-353207.645753870
Quadratic Mean354135.781935445
Winsorized Mean ( 1 / 23 )-353782.7536231881771.70236736284-199.685206804679
Winsorized Mean ( 2 / 23 )-353944.4347826091652.19702995112-214.22652889836
Winsorized Mean ( 3 / 23 )-353941.5217391301651.11568038986-214.365065962887
Winsorized Mean ( 4 / 23 )-353906.0434782611641.17833430542-215.641430355612
Winsorized Mean ( 5 / 23 )-353879.3768115941507.72391593848-234.710992556832
Winsorized Mean ( 6 / 23 )-353727.8985507251434.94423005549-246.509858112776
Winsorized Mean ( 7 / 23 )-353742.4057971011423.66316622915-248.473384848509
Winsorized Mean ( 8 / 23 )-353709.4782608701386.72088554662-255.068977432645
Winsorized Mean ( 9 / 23 )-353723.3043478261366.47539051508-258.858159322205
Winsorized Mean ( 10 / 23 )-353648.3768115941308.75991559464-270.216387740538
Winsorized Mean ( 11 / 23 )-353627.1739130431279.98363643042-276.274761526819
Winsorized Mean ( 12 / 23 )-353805.6086956521234.11116100725-286.688606241016
Winsorized Mean ( 13 / 23 )-353888.1304347831194.70313739154-296.214280651714
Winsorized Mean ( 14 / 23 )-353847.7536231881186.12306330977-298.322968812198
Winsorized Mean ( 15 / 23 )-354053.840579711145.46154168883-309.092734844424
Winsorized Mean ( 16 / 23 )-353997.9565217391108.52168814706-319.34238211745
Winsorized Mean ( 17 / 23 )-353745.6666666671069.61063970682-330.723773244841
Winsorized Mean ( 18 / 23 )-353455.840579711027.70414586766-343.927619637358
Winsorized Mean ( 19 / 23 )-353476.2173913041014.76317015573-348.333707595102
Winsorized Mean ( 20 / 23 )-3535111009.72031675772-350.107840887214
Winsorized Mean ( 21 / 23 )-353712.782608696950.782328493902-372.022882639183
Winsorized Mean ( 22 / 23 )-353914.608695652881.60865044496-401.441851230732
Winsorized Mean ( 23 / 23 )-353799.275362319845.509399891197-418.445111796329
Trimmed Mean ( 1 / 23 )-353826.4328358211685.64999940654-209.905041355199
Trimmed Mean ( 2 / 23 )-353872.81581.24181651881-223.794233306498
Trimmed Mean ( 3 / 23 )-353833.5714285711534.52776721820-230.581406858477
Trimmed Mean ( 4 / 23 )-353792.8688524591478.40108570210-239.307771263196
Trimmed Mean ( 5 / 23 )-353759.7796610171413.77105073937-250.224235017408
Trimmed Mean ( 6 / 23 )-353730.8245614031379.47445318652-256.424338808380
Trimmed Mean ( 7 / 23 )-353731.4363636361357.90440988047-260.498039324266
Trimmed Mean ( 8 / 23 )-353729.3962264151333.41973308166-265.279857085145
Trimmed Mean ( 9 / 23 )-353732.7647058821311.31933520891-269.753335597335
Trimmed Mean ( 10 / 23 )-353734.2448979591287.46888659672-274.751684161483
Trimmed Mean ( 11 / 23 )-353734.2448979591269.57425613459-278.624305107568
Trimmed Mean ( 12 / 23 )-353763.5333333331251.78888464356-282.6063864867
Trimmed Mean ( 13 / 23 )-353757.9069767441237.48348034835-285.868791458261
Trimmed Mean ( 14 / 23 )-353741.0487804881225.52503479779-288.6444901053
Trimmed Mean ( 15 / 23 )-353727.5641025641209.36003575422-292.491527456471
Trimmed Mean ( 16 / 23 )-3536871194.65521619653-296.057804130338
Trimmed Mean ( 17 / 23 )-353648.6857142861180.73698732160-299.515209154671
Trimmed Mean ( 18 / 23 )-353636.7575757581168.07714388757-302.751200489028
Trimmed Mean ( 19 / 23 )-353659.1290322581157.21443700313-305.612441154934
Trimmed Mean ( 20 / 23 )-353682.0344827591140.6739878288-310.064083389830
Trimmed Mean ( 21 / 23 )-353703.8888888891113.27957715216-317.713444266792
Trimmed Mean ( 22 / 23 )-353703.8888888891087.43354819195-325.26483064366
Trimmed Mean ( 23 / 23 )-353673.8260869571066.77690777276-331.534947475911
Median-353311
Midrange-353846
Midmean - Weighted Average at Xnp-353950.058823529
Midmean - Weighted Average at X(n+1)p-353648.685714286
Midmean - Empirical Distribution Function-353648.685714286
Midmean - Empirical Distribution Function - Averaging-353648.685714286
Midmean - Empirical Distribution Function - Interpolation-353648.685714286
Midmean - Closest Observation-353973.333333333
Midmean - True Basic - Statistics Graphics Toolkit-353648.685714286
Midmean - MS Excel (old versions)-353648.685714286
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')