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 computationMon, 20 Oct 2008 11:40:10 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/20/t1224524459zpcr40jksj886wy.htm/, Retrieved Sun, 19 May 2024 13:01:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17764, Retrieved Sun, 19 May 2024 13:01:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsniet werkende werkzoekende vrouwen central tendency
Estimated Impact168
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Aantal niet werke...] [2008-10-13 17:14:43] [b635de6fc42b001d22cbe6e730fec936]
- RMP     [Central Tendency] [Aantal niet werke...] [2008-10-20 17:40:10] [f4b2017b314c03698059f43b95818e67] [Current]
- RMP       [Histogram] [aantal niet werke...] [2008-10-21 07:20:00] [b635de6fc42b001d22cbe6e730fec936]
- RMPD        [Back to Back Histogram] [Histogram kolom 2...] [2008-10-21 07:33:55] [b635de6fc42b001d22cbe6e730fec936]
- RMPD      [Partial Correlation] [Partial correlati...] [2008-11-11 13:34:38] [b635de6fc42b001d22cbe6e730fec936]
-    D        [Partial Correlation] [Partial correlati...] [2008-11-11 13:46:47] [b635de6fc42b001d22cbe6e730fec936]
- RMPD        [Hierarchical Clustering] [Hierarchical Clus...] [2008-11-11 16:30:28] [b635de6fc42b001d22cbe6e730fec936]
F RM D        [Box-Cox Linearity Plot] [Box-Cox Linearity...] [2008-11-11 16:41:49] [b635de6fc42b001d22cbe6e730fec936]
- RM D        [Box-Cox Linearity Plot] [Box-Cox Linearity...] [2008-11-11 16:54:12] [b635de6fc42b001d22cbe6e730fec936]
Feedback Forum

Post a new message
Dataseries X:
308.347
298.427
289.231
291.975
294.912
293.488
290.555
284.736
281.818
287.854
316.263
325.412
326.011
328.282
317.480
317.539
313.737
312.276
309.391
302.950
300.316
304.035
333.476
337.698
335.932
323.931
313.927
314.485
313.218
309.664
302.963
298.989
298.423
301.631
329.765
335.083
327.616
309.119
295.916
291.413
291.542
284.678
276.475
272.566
264.981
263.290
296.806
303.598
286.994
276.427
266.424
267.153
268.381
262.522
255.542
253.158
243.803
250.741
280.445
285.257




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=17764&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=17764&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17764&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 Mean296.984453.0100294047989498.6649663709308
Geometric Mean296.06669776339
Harmonic Mean295.131202472463
Quadratic Mean297.88306411384
Winsorized Mean ( 1 / 20 )297.070652.9707825519696999.997440002142
Winsorized Mean ( 2 / 20 )297.1229166666672.94370517843855100.935011713460
Winsorized Mean ( 3 / 20 )297.1617666666672.89678072302156102.583452142247
Winsorized Mean ( 4 / 20 )297.37972.73862886590010108.587075708874
Winsorized Mean ( 5 / 20 )297.3201166666672.70049499386986110.098377275864
Winsorized Mean ( 6 / 20 )297.4226166666672.65200406675938112.150135964951
Winsorized Mean ( 7 / 20 )297.4037166666672.58177117740538115.193677607614
Winsorized Mean ( 8 / 20 )297.421052.54715995778094116.765752810872
Winsorized Mean ( 9 / 20 )297.38312.46933752188834120.43031678091
Winsorized Mean ( 10 / 20 )297.0152666666672.14843550381410138.247234389572
Winsorized Mean ( 11 / 20 )297.71232.01486719800418147.757777929433
Winsorized Mean ( 12 / 20 )297.47851.97326246997801150.754653537456
Winsorized Mean ( 13 / 20 )297.9534333333331.76116541896993169.179697786481
Winsorized Mean ( 14 / 20 )298.14361.68720915488163176.708145008208
Winsorized Mean ( 15 / 20 )298.81111.56615229121102190.793131470596
Winsorized Mean ( 16 / 20 )298.6881666666671.54154934172589193.758421207758
Winsorized Mean ( 17 / 20 )298.5688833333331.47662589429083202.196700252723
Winsorized Mean ( 18 / 20 )298.3063833333331.27673170847246233.648448890049
Winsorized Mean ( 19 / 20 )298.4922666666671.22315674071398244.03435531282
Winsorized Mean ( 20 / 20 )298.86061.14276971576816261.523031172653
Trimmed Mean ( 1 / 20 )297.1994137931032.88857611385577102.88785965082
Trimmed Mean ( 2 / 20 )297.3373752.78709790688685106.683505543629
Trimmed Mean ( 3 / 20 )297.4565185185192.67946753875158111.013294326794
Trimmed Mean ( 4 / 20 )297.5698846153852.56829515432688115.862806544668
Trimmed Mean ( 5 / 20 )297.626942.49308601837734119.380935036375
Trimmed Mean ( 6 / 20 )297.7036458333332.41053394045668123.501121820725
Trimmed Mean ( 7 / 20 )297.7647391304352.32016866962136128.337539864733
Trimmed Mean ( 8 / 20 )297.8350681818182.22455987556085133.884941220891
Trimmed Mean ( 9 / 20 )297.9092.10920927959593141.242029836448
Trimmed Mean ( 10 / 20 )297.996651.97928643401722150.557617572903
Trimmed Mean ( 11 / 20 )298.1516052631581.90116435893542156.825791448201
Trimmed Mean ( 12 / 20 )298.2181666666671.83358830066872162.641835442506
Trimmed Mean ( 13 / 20 )298.3269411764711.75032322960498170.441056903415
Trimmed Mean ( 14 / 20 )298.38081251.69690624767017175.838124769517
Trimmed Mean ( 15 / 20 )298.41471.64016039736376181.942388366188
Trimmed Mean ( 16 / 20 )298.3580714285711.59233038511692187.371963894707
Trimmed Mean ( 17 / 20 )298.3104615384621.52437270652632195.693914133533
Trimmed Mean ( 18 / 20 )298.2724583333331.44020247668082207.104530899538
Trimmed Mean ( 19 / 20 )298.2673181818181.38637283046416215.142212561940
Trimmed Mean ( 20 / 20 )298.23181.31367199623202227.021509825446
Median298.425
Midrange290.7505
Midmean - Weighted Average at Xnp297.879322580645
Midmean - Weighted Average at X(n+1)p298.4147
Midmean - Empirical Distribution Function297.879322580645
Midmean - Empirical Distribution Function - Averaging298.4147
Midmean - Empirical Distribution Function - Interpolation298.4147
Midmean - Closest Observation297.879322580645
Midmean - True Basic - Statistics Graphics Toolkit298.4147
Midmean - MS Excel (old versions)298.3808125
Number of observations60

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 296.98445 & 3.01002940479894 & 98.6649663709308 \tabularnewline
Geometric Mean & 296.06669776339 &  &  \tabularnewline
Harmonic Mean & 295.131202472463 &  &  \tabularnewline
Quadratic Mean & 297.88306411384 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & 297.07065 & 2.97078255196969 & 99.997440002142 \tabularnewline
Winsorized Mean ( 2 / 20 ) & 297.122916666667 & 2.94370517843855 & 100.935011713460 \tabularnewline
Winsorized Mean ( 3 / 20 ) & 297.161766666667 & 2.89678072302156 & 102.583452142247 \tabularnewline
Winsorized Mean ( 4 / 20 ) & 297.3797 & 2.73862886590010 & 108.587075708874 \tabularnewline
Winsorized Mean ( 5 / 20 ) & 297.320116666667 & 2.70049499386986 & 110.098377275864 \tabularnewline
Winsorized Mean ( 6 / 20 ) & 297.422616666667 & 2.65200406675938 & 112.150135964951 \tabularnewline
Winsorized Mean ( 7 / 20 ) & 297.403716666667 & 2.58177117740538 & 115.193677607614 \tabularnewline
Winsorized Mean ( 8 / 20 ) & 297.42105 & 2.54715995778094 & 116.765752810872 \tabularnewline
Winsorized Mean ( 9 / 20 ) & 297.3831 & 2.46933752188834 & 120.43031678091 \tabularnewline
Winsorized Mean ( 10 / 20 ) & 297.015266666667 & 2.14843550381410 & 138.247234389572 \tabularnewline
Winsorized Mean ( 11 / 20 ) & 297.7123 & 2.01486719800418 & 147.757777929433 \tabularnewline
Winsorized Mean ( 12 / 20 ) & 297.4785 & 1.97326246997801 & 150.754653537456 \tabularnewline
Winsorized Mean ( 13 / 20 ) & 297.953433333333 & 1.76116541896993 & 169.179697786481 \tabularnewline
Winsorized Mean ( 14 / 20 ) & 298.1436 & 1.68720915488163 & 176.708145008208 \tabularnewline
Winsorized Mean ( 15 / 20 ) & 298.8111 & 1.56615229121102 & 190.793131470596 \tabularnewline
Winsorized Mean ( 16 / 20 ) & 298.688166666667 & 1.54154934172589 & 193.758421207758 \tabularnewline
Winsorized Mean ( 17 / 20 ) & 298.568883333333 & 1.47662589429083 & 202.196700252723 \tabularnewline
Winsorized Mean ( 18 / 20 ) & 298.306383333333 & 1.27673170847246 & 233.648448890049 \tabularnewline
Winsorized Mean ( 19 / 20 ) & 298.492266666667 & 1.22315674071398 & 244.03435531282 \tabularnewline
Winsorized Mean ( 20 / 20 ) & 298.8606 & 1.14276971576816 & 261.523031172653 \tabularnewline
Trimmed Mean ( 1 / 20 ) & 297.199413793103 & 2.88857611385577 & 102.88785965082 \tabularnewline
Trimmed Mean ( 2 / 20 ) & 297.337375 & 2.78709790688685 & 106.683505543629 \tabularnewline
Trimmed Mean ( 3 / 20 ) & 297.456518518519 & 2.67946753875158 & 111.013294326794 \tabularnewline
Trimmed Mean ( 4 / 20 ) & 297.569884615385 & 2.56829515432688 & 115.862806544668 \tabularnewline
Trimmed Mean ( 5 / 20 ) & 297.62694 & 2.49308601837734 & 119.380935036375 \tabularnewline
Trimmed Mean ( 6 / 20 ) & 297.703645833333 & 2.41053394045668 & 123.501121820725 \tabularnewline
Trimmed Mean ( 7 / 20 ) & 297.764739130435 & 2.32016866962136 & 128.337539864733 \tabularnewline
Trimmed Mean ( 8 / 20 ) & 297.835068181818 & 2.22455987556085 & 133.884941220891 \tabularnewline
Trimmed Mean ( 9 / 20 ) & 297.909 & 2.10920927959593 & 141.242029836448 \tabularnewline
Trimmed Mean ( 10 / 20 ) & 297.99665 & 1.97928643401722 & 150.557617572903 \tabularnewline
Trimmed Mean ( 11 / 20 ) & 298.151605263158 & 1.90116435893542 & 156.825791448201 \tabularnewline
Trimmed Mean ( 12 / 20 ) & 298.218166666667 & 1.83358830066872 & 162.641835442506 \tabularnewline
Trimmed Mean ( 13 / 20 ) & 298.326941176471 & 1.75032322960498 & 170.441056903415 \tabularnewline
Trimmed Mean ( 14 / 20 ) & 298.3808125 & 1.69690624767017 & 175.838124769517 \tabularnewline
Trimmed Mean ( 15 / 20 ) & 298.4147 & 1.64016039736376 & 181.942388366188 \tabularnewline
Trimmed Mean ( 16 / 20 ) & 298.358071428571 & 1.59233038511692 & 187.371963894707 \tabularnewline
Trimmed Mean ( 17 / 20 ) & 298.310461538462 & 1.52437270652632 & 195.693914133533 \tabularnewline
Trimmed Mean ( 18 / 20 ) & 298.272458333333 & 1.44020247668082 & 207.104530899538 \tabularnewline
Trimmed Mean ( 19 / 20 ) & 298.267318181818 & 1.38637283046416 & 215.142212561940 \tabularnewline
Trimmed Mean ( 20 / 20 ) & 298.2318 & 1.31367199623202 & 227.021509825446 \tabularnewline
Median & 298.425 &  &  \tabularnewline
Midrange & 290.7505 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 297.879322580645 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 298.4147 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 297.879322580645 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 298.4147 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 298.4147 &  &  \tabularnewline
Midmean - Closest Observation & 297.879322580645 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 298.4147 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 298.3808125 &  &  \tabularnewline
Number of observations & 60 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17764&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]296.98445[/C][C]3.01002940479894[/C][C]98.6649663709308[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]296.06669776339[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]295.131202472463[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]297.88306411384[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]297.07065[/C][C]2.97078255196969[/C][C]99.997440002142[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]297.122916666667[/C][C]2.94370517843855[/C][C]100.935011713460[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]297.161766666667[/C][C]2.89678072302156[/C][C]102.583452142247[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]297.3797[/C][C]2.73862886590010[/C][C]108.587075708874[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]297.320116666667[/C][C]2.70049499386986[/C][C]110.098377275864[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]297.422616666667[/C][C]2.65200406675938[/C][C]112.150135964951[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]297.403716666667[/C][C]2.58177117740538[/C][C]115.193677607614[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]297.42105[/C][C]2.54715995778094[/C][C]116.765752810872[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]297.3831[/C][C]2.46933752188834[/C][C]120.43031678091[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]297.015266666667[/C][C]2.14843550381410[/C][C]138.247234389572[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]297.7123[/C][C]2.01486719800418[/C][C]147.757777929433[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]297.4785[/C][C]1.97326246997801[/C][C]150.754653537456[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]297.953433333333[/C][C]1.76116541896993[/C][C]169.179697786481[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]298.1436[/C][C]1.68720915488163[/C][C]176.708145008208[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]298.8111[/C][C]1.56615229121102[/C][C]190.793131470596[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]298.688166666667[/C][C]1.54154934172589[/C][C]193.758421207758[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]298.568883333333[/C][C]1.47662589429083[/C][C]202.196700252723[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]298.306383333333[/C][C]1.27673170847246[/C][C]233.648448890049[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]298.492266666667[/C][C]1.22315674071398[/C][C]244.03435531282[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]298.8606[/C][C]1.14276971576816[/C][C]261.523031172653[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]297.199413793103[/C][C]2.88857611385577[/C][C]102.88785965082[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]297.337375[/C][C]2.78709790688685[/C][C]106.683505543629[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]297.456518518519[/C][C]2.67946753875158[/C][C]111.013294326794[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]297.569884615385[/C][C]2.56829515432688[/C][C]115.862806544668[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]297.62694[/C][C]2.49308601837734[/C][C]119.380935036375[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]297.703645833333[/C][C]2.41053394045668[/C][C]123.501121820725[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]297.764739130435[/C][C]2.32016866962136[/C][C]128.337539864733[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]297.835068181818[/C][C]2.22455987556085[/C][C]133.884941220891[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]297.909[/C][C]2.10920927959593[/C][C]141.242029836448[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]297.99665[/C][C]1.97928643401722[/C][C]150.557617572903[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]298.151605263158[/C][C]1.90116435893542[/C][C]156.825791448201[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]298.218166666667[/C][C]1.83358830066872[/C][C]162.641835442506[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]298.326941176471[/C][C]1.75032322960498[/C][C]170.441056903415[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]298.3808125[/C][C]1.69690624767017[/C][C]175.838124769517[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]298.4147[/C][C]1.64016039736376[/C][C]181.942388366188[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]298.358071428571[/C][C]1.59233038511692[/C][C]187.371963894707[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]298.310461538462[/C][C]1.52437270652632[/C][C]195.693914133533[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]298.272458333333[/C][C]1.44020247668082[/C][C]207.104530899538[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]298.267318181818[/C][C]1.38637283046416[/C][C]215.142212561940[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]298.2318[/C][C]1.31367199623202[/C][C]227.021509825446[/C][/ROW]
[ROW][C]Median[/C][C]298.425[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]290.7505[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]297.879322580645[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]298.4147[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]297.879322580645[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]298.4147[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]298.4147[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]297.879322580645[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]298.4147[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]298.3808125[/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=17764&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17764&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 Mean296.984453.0100294047989498.6649663709308
Geometric Mean296.06669776339
Harmonic Mean295.131202472463
Quadratic Mean297.88306411384
Winsorized Mean ( 1 / 20 )297.070652.9707825519696999.997440002142
Winsorized Mean ( 2 / 20 )297.1229166666672.94370517843855100.935011713460
Winsorized Mean ( 3 / 20 )297.1617666666672.89678072302156102.583452142247
Winsorized Mean ( 4 / 20 )297.37972.73862886590010108.587075708874
Winsorized Mean ( 5 / 20 )297.3201166666672.70049499386986110.098377275864
Winsorized Mean ( 6 / 20 )297.4226166666672.65200406675938112.150135964951
Winsorized Mean ( 7 / 20 )297.4037166666672.58177117740538115.193677607614
Winsorized Mean ( 8 / 20 )297.421052.54715995778094116.765752810872
Winsorized Mean ( 9 / 20 )297.38312.46933752188834120.43031678091
Winsorized Mean ( 10 / 20 )297.0152666666672.14843550381410138.247234389572
Winsorized Mean ( 11 / 20 )297.71232.01486719800418147.757777929433
Winsorized Mean ( 12 / 20 )297.47851.97326246997801150.754653537456
Winsorized Mean ( 13 / 20 )297.9534333333331.76116541896993169.179697786481
Winsorized Mean ( 14 / 20 )298.14361.68720915488163176.708145008208
Winsorized Mean ( 15 / 20 )298.81111.56615229121102190.793131470596
Winsorized Mean ( 16 / 20 )298.6881666666671.54154934172589193.758421207758
Winsorized Mean ( 17 / 20 )298.5688833333331.47662589429083202.196700252723
Winsorized Mean ( 18 / 20 )298.3063833333331.27673170847246233.648448890049
Winsorized Mean ( 19 / 20 )298.4922666666671.22315674071398244.03435531282
Winsorized Mean ( 20 / 20 )298.86061.14276971576816261.523031172653
Trimmed Mean ( 1 / 20 )297.1994137931032.88857611385577102.88785965082
Trimmed Mean ( 2 / 20 )297.3373752.78709790688685106.683505543629
Trimmed Mean ( 3 / 20 )297.4565185185192.67946753875158111.013294326794
Trimmed Mean ( 4 / 20 )297.5698846153852.56829515432688115.862806544668
Trimmed Mean ( 5 / 20 )297.626942.49308601837734119.380935036375
Trimmed Mean ( 6 / 20 )297.7036458333332.41053394045668123.501121820725
Trimmed Mean ( 7 / 20 )297.7647391304352.32016866962136128.337539864733
Trimmed Mean ( 8 / 20 )297.8350681818182.22455987556085133.884941220891
Trimmed Mean ( 9 / 20 )297.9092.10920927959593141.242029836448
Trimmed Mean ( 10 / 20 )297.996651.97928643401722150.557617572903
Trimmed Mean ( 11 / 20 )298.1516052631581.90116435893542156.825791448201
Trimmed Mean ( 12 / 20 )298.2181666666671.83358830066872162.641835442506
Trimmed Mean ( 13 / 20 )298.3269411764711.75032322960498170.441056903415
Trimmed Mean ( 14 / 20 )298.38081251.69690624767017175.838124769517
Trimmed Mean ( 15 / 20 )298.41471.64016039736376181.942388366188
Trimmed Mean ( 16 / 20 )298.3580714285711.59233038511692187.371963894707
Trimmed Mean ( 17 / 20 )298.3104615384621.52437270652632195.693914133533
Trimmed Mean ( 18 / 20 )298.2724583333331.44020247668082207.104530899538
Trimmed Mean ( 19 / 20 )298.2673181818181.38637283046416215.142212561940
Trimmed Mean ( 20 / 20 )298.23181.31367199623202227.021509825446
Median298.425
Midrange290.7505
Midmean - Weighted Average at Xnp297.879322580645
Midmean - Weighted Average at X(n+1)p298.4147
Midmean - Empirical Distribution Function297.879322580645
Midmean - Empirical Distribution Function - Averaging298.4147
Midmean - Empirical Distribution Function - Interpolation298.4147
Midmean - Closest Observation297.879322580645
Midmean - True Basic - Statistics Graphics Toolkit298.4147
Midmean - MS Excel (old versions)298.3808125
Number of observations60



Parameters (Session):
par1 = grey ; par2 = grey ; par3 = TRUE ; par4 = Female ; par5 = Male ;
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')