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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationThu, 08 Oct 2015 16:04:47 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Oct/08/t1444316738mfol8kdnjar9sya.htm/, Retrieved Wed, 15 May 2024 02:40:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=281478, Retrieved Wed, 15 May 2024 02:40:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact64
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Centrummaten eige...] [2015-10-08 15:04:47] [9de61432ca342460988ae3c030b81fa6] [Current]
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Dataseries X:
-12
-12
-8
-6
-2
4
3
5
8
5
3
6
15
12
11
12
14
18
15
16
-1
-5
-6
-5
-2
-9
-9
-12
-16
-19
-30
-26
-22
-31
-33
-31
-27
-29
-33
-27
-22
-23
-23
-15
-15
-24
-18
-14
-7
-12
-12
-15
-16
-17
-13
-8
-13
-13
-11
-16
-34
-35
-38
-32
-37
-39
-31
-30
-29
-36
-41
-42
-33
-43
-41
-34
-32
-36
-37
-30
-32
-30
-21
-19
-6
-11
-11




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ yule.wessa.net

\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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=281478&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=281478&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281478&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 time1 seconds
R Server'George Udny Yule' @ yule.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-16.24137931034481.73135351924972-9.38074121187164
Geometric MeanNaN
Harmonic Mean-21.0484902288574
Quadratic Mean22.838010260171
Winsorized Mean ( 1 / 29 )-16.25287356321841.72417891780562-9.42644257818883
Winsorized Mean ( 2 / 29 )-16.25287356321841.71531915545769-9.4751309174774
Winsorized Mean ( 3 / 29 )-16.25287356321841.71531915545769-9.4751309174774
Winsorized Mean ( 4 / 29 )-16.20689655172411.69074860015674-9.58563357687933
Winsorized Mean ( 5 / 29 )-16.2643678160921.658530778668-9.80649139906479
Winsorized Mean ( 6 / 29 )-16.19540229885061.64821427191451-9.82602964603536
Winsorized Mean ( 7 / 29 )-16.27586206896551.63239472907227-9.97054314076077
Winsorized Mean ( 8 / 29 )-16.45977011494251.5670699598962-10.5035324115541
Winsorized Mean ( 9 / 29 )-16.66666666666671.53046813413876-10.8899142000402
Winsorized Mean ( 10 / 29 )-16.66666666666671.49423436749587-11.1539842940419
Winsorized Mean ( 11 / 29 )-16.54022988505751.4765207409481-11.2021656224326
Winsorized Mean ( 12 / 29 )-16.67816091954021.4534103221462-11.4751909116155
Winsorized Mean ( 13 / 29 )-16.67816091954021.40848369435398-11.8412168961529
Winsorized Mean ( 14 / 29 )-16.67816091954021.40848369435398-11.8412168961529
Winsorized Mean ( 15 / 29 )-17.3678160919541.30183130758784-13.341064998763
Winsorized Mean ( 16 / 29 )-17.3678160919541.24987194666507-13.8956763837248
Winsorized Mean ( 17 / 29 )-17.3678160919541.24987194666507-13.8956763837248
Winsorized Mean ( 18 / 29 )-17.98850574712641.16512797140702-15.439081533167
Winsorized Mean ( 19 / 29 )-17.77011494252871.13505315710474-15.6557557073858
Winsorized Mean ( 20 / 29 )-181.10550129782229-16.2822061226503
Winsorized Mean ( 21 / 29 )-181.10550129782229-16.2822061226503
Winsorized Mean ( 22 / 29 )-17.74712643678161.07139153243453-16.5645573065662
Winsorized Mean ( 23 / 29 )-18.01149425287361.03822868670657-17.3482918392565
Winsorized Mean ( 24 / 29 )-18.28735632183911.00478779618588-18.200217390435
Winsorized Mean ( 25 / 29 )-18.28735632183911.00478779618588-18.200217390435
Winsorized Mean ( 26 / 29 )-18.28735632183910.929326764217226-19.678069142066
Winsorized Mean ( 27 / 29 )-18.28735632183910.929326764217226-19.678069142066
Winsorized Mean ( 28 / 29 )-18.28735632183910.770844707238513-23.7237878785625
Winsorized Mean ( 29 / 29 )-18.28735632183910.770844707238513-23.7237878785625
Trimmed Mean ( 1 / 29 )-16.32941176470591.69604815309513-9.62791754167252
Trimmed Mean ( 2 / 29 )-16.40963855421691.66351278926626-9.86444989187901
Trimmed Mean ( 3 / 29 )-16.49382716049381.63120831688763-10.1114167882397
Trimmed Mean ( 4 / 29 )-16.58227848101271.59362243186744-10.4053997668577
Trimmed Mean ( 5 / 29 )-16.68831168831171.55830627118418-10.7092629972091
Trimmed Mean ( 6 / 29 )-16.78666666666671.52649788594541-10.9968489450414
Trimmed Mean ( 7 / 29 )-16.90410958904111.49162609107356-11.3326722361599
Trimmed Mean ( 8 / 29 )-17.01408450704231.45426493532343-11.6994394169714
Trimmed Mean ( 9 / 29 )-17.10144927536231.42474552064879-12.0031605837755
Trimmed Mean ( 10 / 29 )-17.16417910447761.39725728220519-12.2841937008112
Trimmed Mean ( 11 / 29 )-17.23076923076921.3713709505541-12.5646304698281
Trimmed Mean ( 12 / 29 )-17.31746031746031.34324758673734-12.8922325924466
Trimmed Mean ( 13 / 29 )-17.39344262295081.31350253171934-13.2420320501273
Trimmed Mean ( 14 / 29 )-17.47457627118641.28547974388872-13.5938169031928
Trimmed Mean ( 15 / 29 )-17.56140350877191.25081866521307-14.0399276067571
Trimmed Mean ( 16 / 29 )-17.58181818181821.22836589299141-14.3131767839968
Trimmed Mean ( 17 / 29 )-17.60377358490571.20934304955046-14.5564764203584
Trimmed Mean ( 18 / 29 )-17.62745098039221.18485898368812-14.8772564693927
Trimmed Mean ( 19 / 29 )-17.59183673469391.16894276297779-15.0493568135707
Trimmed Mean ( 20 / 29 )-17.57446808510641.1532621474781-15.2389186825714
Trimmed Mean ( 21 / 29 )-17.53333333333331.13733695690211-15.4161290784842
Trimmed Mean ( 22 / 29 )-17.48837209302331.11536738333352-15.6794723912003
Trimmed Mean ( 23 / 29 )-17.46341463414631.09271286979879-15.9817049078611
Trimmed Mean ( 24 / 29 )-17.41025641025641.06832568482188-16.2967685394171
Trimmed Mean ( 25 / 29 )-17.32432432432431.04123256111563-16.638285212443
Trimmed Mean ( 26 / 29 )-17.22857142857141.00258968398332-17.1840701174201
Trimmed Mean ( 27 / 29 )-17.12121212121210.968008710279627-17.6870434526011
Trimmed Mean ( 28 / 29 )-170.91698430469325-18.5390305079288
Trimmed Mean ( 29 / 29 )-16.86206896551720.891564377506751-18.9129011778957
Median-16
Midrange-12.5
Midmean - Weighted Average at Xnp-17.8541666666667
Midmean - Weighted Average at X(n+1)p-17.8541666666667
Midmean - Empirical Distribution Function-17.8541666666667
Midmean - Empirical Distribution Function - Averaging-17.8541666666667
Midmean - Empirical Distribution Function - Interpolation-16.9777777777778
Midmean - Closest Observation-17.8541666666667
Midmean - True Basic - Statistics Graphics Toolkit-17.8541666666667
Midmean - MS Excel (old versions)-17.8541666666667
Number of observations87

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -16.2413793103448 & 1.73135351924972 & -9.38074121187164 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & -21.0484902288574 &  &  \tabularnewline
Quadratic Mean & 22.838010260171 &  &  \tabularnewline
Winsorized Mean ( 1 / 29 ) & -16.2528735632184 & 1.72417891780562 & -9.42644257818883 \tabularnewline
Winsorized Mean ( 2 / 29 ) & -16.2528735632184 & 1.71531915545769 & -9.4751309174774 \tabularnewline
Winsorized Mean ( 3 / 29 ) & -16.2528735632184 & 1.71531915545769 & -9.4751309174774 \tabularnewline
Winsorized Mean ( 4 / 29 ) & -16.2068965517241 & 1.69074860015674 & -9.58563357687933 \tabularnewline
Winsorized Mean ( 5 / 29 ) & -16.264367816092 & 1.658530778668 & -9.80649139906479 \tabularnewline
Winsorized Mean ( 6 / 29 ) & -16.1954022988506 & 1.64821427191451 & -9.82602964603536 \tabularnewline
Winsorized Mean ( 7 / 29 ) & -16.2758620689655 & 1.63239472907227 & -9.97054314076077 \tabularnewline
Winsorized Mean ( 8 / 29 ) & -16.4597701149425 & 1.5670699598962 & -10.5035324115541 \tabularnewline
Winsorized Mean ( 9 / 29 ) & -16.6666666666667 & 1.53046813413876 & -10.8899142000402 \tabularnewline
Winsorized Mean ( 10 / 29 ) & -16.6666666666667 & 1.49423436749587 & -11.1539842940419 \tabularnewline
Winsorized Mean ( 11 / 29 ) & -16.5402298850575 & 1.4765207409481 & -11.2021656224326 \tabularnewline
Winsorized Mean ( 12 / 29 ) & -16.6781609195402 & 1.4534103221462 & -11.4751909116155 \tabularnewline
Winsorized Mean ( 13 / 29 ) & -16.6781609195402 & 1.40848369435398 & -11.8412168961529 \tabularnewline
Winsorized Mean ( 14 / 29 ) & -16.6781609195402 & 1.40848369435398 & -11.8412168961529 \tabularnewline
Winsorized Mean ( 15 / 29 ) & -17.367816091954 & 1.30183130758784 & -13.341064998763 \tabularnewline
Winsorized Mean ( 16 / 29 ) & -17.367816091954 & 1.24987194666507 & -13.8956763837248 \tabularnewline
Winsorized Mean ( 17 / 29 ) & -17.367816091954 & 1.24987194666507 & -13.8956763837248 \tabularnewline
Winsorized Mean ( 18 / 29 ) & -17.9885057471264 & 1.16512797140702 & -15.439081533167 \tabularnewline
Winsorized Mean ( 19 / 29 ) & -17.7701149425287 & 1.13505315710474 & -15.6557557073858 \tabularnewline
Winsorized Mean ( 20 / 29 ) & -18 & 1.10550129782229 & -16.2822061226503 \tabularnewline
Winsorized Mean ( 21 / 29 ) & -18 & 1.10550129782229 & -16.2822061226503 \tabularnewline
Winsorized Mean ( 22 / 29 ) & -17.7471264367816 & 1.07139153243453 & -16.5645573065662 \tabularnewline
Winsorized Mean ( 23 / 29 ) & -18.0114942528736 & 1.03822868670657 & -17.3482918392565 \tabularnewline
Winsorized Mean ( 24 / 29 ) & -18.2873563218391 & 1.00478779618588 & -18.200217390435 \tabularnewline
Winsorized Mean ( 25 / 29 ) & -18.2873563218391 & 1.00478779618588 & -18.200217390435 \tabularnewline
Winsorized Mean ( 26 / 29 ) & -18.2873563218391 & 0.929326764217226 & -19.678069142066 \tabularnewline
Winsorized Mean ( 27 / 29 ) & -18.2873563218391 & 0.929326764217226 & -19.678069142066 \tabularnewline
Winsorized Mean ( 28 / 29 ) & -18.2873563218391 & 0.770844707238513 & -23.7237878785625 \tabularnewline
Winsorized Mean ( 29 / 29 ) & -18.2873563218391 & 0.770844707238513 & -23.7237878785625 \tabularnewline
Trimmed Mean ( 1 / 29 ) & -16.3294117647059 & 1.69604815309513 & -9.62791754167252 \tabularnewline
Trimmed Mean ( 2 / 29 ) & -16.4096385542169 & 1.66351278926626 & -9.86444989187901 \tabularnewline
Trimmed Mean ( 3 / 29 ) & -16.4938271604938 & 1.63120831688763 & -10.1114167882397 \tabularnewline
Trimmed Mean ( 4 / 29 ) & -16.5822784810127 & 1.59362243186744 & -10.4053997668577 \tabularnewline
Trimmed Mean ( 5 / 29 ) & -16.6883116883117 & 1.55830627118418 & -10.7092629972091 \tabularnewline
Trimmed Mean ( 6 / 29 ) & -16.7866666666667 & 1.52649788594541 & -10.9968489450414 \tabularnewline
Trimmed Mean ( 7 / 29 ) & -16.9041095890411 & 1.49162609107356 & -11.3326722361599 \tabularnewline
Trimmed Mean ( 8 / 29 ) & -17.0140845070423 & 1.45426493532343 & -11.6994394169714 \tabularnewline
Trimmed Mean ( 9 / 29 ) & -17.1014492753623 & 1.42474552064879 & -12.0031605837755 \tabularnewline
Trimmed Mean ( 10 / 29 ) & -17.1641791044776 & 1.39725728220519 & -12.2841937008112 \tabularnewline
Trimmed Mean ( 11 / 29 ) & -17.2307692307692 & 1.3713709505541 & -12.5646304698281 \tabularnewline
Trimmed Mean ( 12 / 29 ) & -17.3174603174603 & 1.34324758673734 & -12.8922325924466 \tabularnewline
Trimmed Mean ( 13 / 29 ) & -17.3934426229508 & 1.31350253171934 & -13.2420320501273 \tabularnewline
Trimmed Mean ( 14 / 29 ) & -17.4745762711864 & 1.28547974388872 & -13.5938169031928 \tabularnewline
Trimmed Mean ( 15 / 29 ) & -17.5614035087719 & 1.25081866521307 & -14.0399276067571 \tabularnewline
Trimmed Mean ( 16 / 29 ) & -17.5818181818182 & 1.22836589299141 & -14.3131767839968 \tabularnewline
Trimmed Mean ( 17 / 29 ) & -17.6037735849057 & 1.20934304955046 & -14.5564764203584 \tabularnewline
Trimmed Mean ( 18 / 29 ) & -17.6274509803922 & 1.18485898368812 & -14.8772564693927 \tabularnewline
Trimmed Mean ( 19 / 29 ) & -17.5918367346939 & 1.16894276297779 & -15.0493568135707 \tabularnewline
Trimmed Mean ( 20 / 29 ) & -17.5744680851064 & 1.1532621474781 & -15.2389186825714 \tabularnewline
Trimmed Mean ( 21 / 29 ) & -17.5333333333333 & 1.13733695690211 & -15.4161290784842 \tabularnewline
Trimmed Mean ( 22 / 29 ) & -17.4883720930233 & 1.11536738333352 & -15.6794723912003 \tabularnewline
Trimmed Mean ( 23 / 29 ) & -17.4634146341463 & 1.09271286979879 & -15.9817049078611 \tabularnewline
Trimmed Mean ( 24 / 29 ) & -17.4102564102564 & 1.06832568482188 & -16.2967685394171 \tabularnewline
Trimmed Mean ( 25 / 29 ) & -17.3243243243243 & 1.04123256111563 & -16.638285212443 \tabularnewline
Trimmed Mean ( 26 / 29 ) & -17.2285714285714 & 1.00258968398332 & -17.1840701174201 \tabularnewline
Trimmed Mean ( 27 / 29 ) & -17.1212121212121 & 0.968008710279627 & -17.6870434526011 \tabularnewline
Trimmed Mean ( 28 / 29 ) & -17 & 0.91698430469325 & -18.5390305079288 \tabularnewline
Trimmed Mean ( 29 / 29 ) & -16.8620689655172 & 0.891564377506751 & -18.9129011778957 \tabularnewline
Median & -16 &  &  \tabularnewline
Midrange & -12.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -17.8541666666667 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -17.8541666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -17.8541666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -17.8541666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -16.9777777777778 &  &  \tabularnewline
Midmean - Closest Observation & -17.8541666666667 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -17.8541666666667 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -17.8541666666667 &  &  \tabularnewline
Number of observations & 87 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=281478&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]-16.2413793103448[/C][C]1.73135351924972[/C][C]-9.38074121187164[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]-21.0484902288574[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]22.838010260171[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 29 )[/C][C]-16.2528735632184[/C][C]1.72417891780562[/C][C]-9.42644257818883[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 29 )[/C][C]-16.2528735632184[/C][C]1.71531915545769[/C][C]-9.4751309174774[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 29 )[/C][C]-16.2528735632184[/C][C]1.71531915545769[/C][C]-9.4751309174774[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 29 )[/C][C]-16.2068965517241[/C][C]1.69074860015674[/C][C]-9.58563357687933[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 29 )[/C][C]-16.264367816092[/C][C]1.658530778668[/C][C]-9.80649139906479[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 29 )[/C][C]-16.1954022988506[/C][C]1.64821427191451[/C][C]-9.82602964603536[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 29 )[/C][C]-16.2758620689655[/C][C]1.63239472907227[/C][C]-9.97054314076077[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 29 )[/C][C]-16.4597701149425[/C][C]1.5670699598962[/C][C]-10.5035324115541[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 29 )[/C][C]-16.6666666666667[/C][C]1.53046813413876[/C][C]-10.8899142000402[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 29 )[/C][C]-16.6666666666667[/C][C]1.49423436749587[/C][C]-11.1539842940419[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 29 )[/C][C]-16.5402298850575[/C][C]1.4765207409481[/C][C]-11.2021656224326[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 29 )[/C][C]-16.6781609195402[/C][C]1.4534103221462[/C][C]-11.4751909116155[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 29 )[/C][C]-16.6781609195402[/C][C]1.40848369435398[/C][C]-11.8412168961529[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 29 )[/C][C]-16.6781609195402[/C][C]1.40848369435398[/C][C]-11.8412168961529[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 29 )[/C][C]-17.367816091954[/C][C]1.30183130758784[/C][C]-13.341064998763[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 29 )[/C][C]-17.367816091954[/C][C]1.24987194666507[/C][C]-13.8956763837248[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 29 )[/C][C]-17.367816091954[/C][C]1.24987194666507[/C][C]-13.8956763837248[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 29 )[/C][C]-17.9885057471264[/C][C]1.16512797140702[/C][C]-15.439081533167[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 29 )[/C][C]-17.7701149425287[/C][C]1.13505315710474[/C][C]-15.6557557073858[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 29 )[/C][C]-18[/C][C]1.10550129782229[/C][C]-16.2822061226503[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 29 )[/C][C]-18[/C][C]1.10550129782229[/C][C]-16.2822061226503[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 29 )[/C][C]-17.7471264367816[/C][C]1.07139153243453[/C][C]-16.5645573065662[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 29 )[/C][C]-18.0114942528736[/C][C]1.03822868670657[/C][C]-17.3482918392565[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 29 )[/C][C]-18.2873563218391[/C][C]1.00478779618588[/C][C]-18.200217390435[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 29 )[/C][C]-18.2873563218391[/C][C]1.00478779618588[/C][C]-18.200217390435[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 29 )[/C][C]-18.2873563218391[/C][C]0.929326764217226[/C][C]-19.678069142066[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 29 )[/C][C]-18.2873563218391[/C][C]0.929326764217226[/C][C]-19.678069142066[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 29 )[/C][C]-18.2873563218391[/C][C]0.770844707238513[/C][C]-23.7237878785625[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 29 )[/C][C]-18.2873563218391[/C][C]0.770844707238513[/C][C]-23.7237878785625[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 29 )[/C][C]-16.3294117647059[/C][C]1.69604815309513[/C][C]-9.62791754167252[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 29 )[/C][C]-16.4096385542169[/C][C]1.66351278926626[/C][C]-9.86444989187901[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 29 )[/C][C]-16.4938271604938[/C][C]1.63120831688763[/C][C]-10.1114167882397[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 29 )[/C][C]-16.5822784810127[/C][C]1.59362243186744[/C][C]-10.4053997668577[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 29 )[/C][C]-16.6883116883117[/C][C]1.55830627118418[/C][C]-10.7092629972091[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 29 )[/C][C]-16.7866666666667[/C][C]1.52649788594541[/C][C]-10.9968489450414[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 29 )[/C][C]-16.9041095890411[/C][C]1.49162609107356[/C][C]-11.3326722361599[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 29 )[/C][C]-17.0140845070423[/C][C]1.45426493532343[/C][C]-11.6994394169714[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 29 )[/C][C]-17.1014492753623[/C][C]1.42474552064879[/C][C]-12.0031605837755[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 29 )[/C][C]-17.1641791044776[/C][C]1.39725728220519[/C][C]-12.2841937008112[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 29 )[/C][C]-17.2307692307692[/C][C]1.3713709505541[/C][C]-12.5646304698281[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 29 )[/C][C]-17.3174603174603[/C][C]1.34324758673734[/C][C]-12.8922325924466[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 29 )[/C][C]-17.3934426229508[/C][C]1.31350253171934[/C][C]-13.2420320501273[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 29 )[/C][C]-17.4745762711864[/C][C]1.28547974388872[/C][C]-13.5938169031928[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 29 )[/C][C]-17.5614035087719[/C][C]1.25081866521307[/C][C]-14.0399276067571[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 29 )[/C][C]-17.5818181818182[/C][C]1.22836589299141[/C][C]-14.3131767839968[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 29 )[/C][C]-17.6037735849057[/C][C]1.20934304955046[/C][C]-14.5564764203584[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 29 )[/C][C]-17.6274509803922[/C][C]1.18485898368812[/C][C]-14.8772564693927[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 29 )[/C][C]-17.5918367346939[/C][C]1.16894276297779[/C][C]-15.0493568135707[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 29 )[/C][C]-17.5744680851064[/C][C]1.1532621474781[/C][C]-15.2389186825714[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 29 )[/C][C]-17.5333333333333[/C][C]1.13733695690211[/C][C]-15.4161290784842[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 29 )[/C][C]-17.4883720930233[/C][C]1.11536738333352[/C][C]-15.6794723912003[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 29 )[/C][C]-17.4634146341463[/C][C]1.09271286979879[/C][C]-15.9817049078611[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 29 )[/C][C]-17.4102564102564[/C][C]1.06832568482188[/C][C]-16.2967685394171[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 29 )[/C][C]-17.3243243243243[/C][C]1.04123256111563[/C][C]-16.638285212443[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 29 )[/C][C]-17.2285714285714[/C][C]1.00258968398332[/C][C]-17.1840701174201[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 29 )[/C][C]-17.1212121212121[/C][C]0.968008710279627[/C][C]-17.6870434526011[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 29 )[/C][C]-17[/C][C]0.91698430469325[/C][C]-18.5390305079288[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 29 )[/C][C]-16.8620689655172[/C][C]0.891564377506751[/C][C]-18.9129011778957[/C][/ROW]
[ROW][C]Median[/C][C]-16[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-12.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-17.8541666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-17.8541666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-17.8541666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-17.8541666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-16.9777777777778[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-17.8541666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-17.8541666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-17.8541666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]87[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=281478&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281478&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-16.24137931034481.73135351924972-9.38074121187164
Geometric MeanNaN
Harmonic Mean-21.0484902288574
Quadratic Mean22.838010260171
Winsorized Mean ( 1 / 29 )-16.25287356321841.72417891780562-9.42644257818883
Winsorized Mean ( 2 / 29 )-16.25287356321841.71531915545769-9.4751309174774
Winsorized Mean ( 3 / 29 )-16.25287356321841.71531915545769-9.4751309174774
Winsorized Mean ( 4 / 29 )-16.20689655172411.69074860015674-9.58563357687933
Winsorized Mean ( 5 / 29 )-16.2643678160921.658530778668-9.80649139906479
Winsorized Mean ( 6 / 29 )-16.19540229885061.64821427191451-9.82602964603536
Winsorized Mean ( 7 / 29 )-16.27586206896551.63239472907227-9.97054314076077
Winsorized Mean ( 8 / 29 )-16.45977011494251.5670699598962-10.5035324115541
Winsorized Mean ( 9 / 29 )-16.66666666666671.53046813413876-10.8899142000402
Winsorized Mean ( 10 / 29 )-16.66666666666671.49423436749587-11.1539842940419
Winsorized Mean ( 11 / 29 )-16.54022988505751.4765207409481-11.2021656224326
Winsorized Mean ( 12 / 29 )-16.67816091954021.4534103221462-11.4751909116155
Winsorized Mean ( 13 / 29 )-16.67816091954021.40848369435398-11.8412168961529
Winsorized Mean ( 14 / 29 )-16.67816091954021.40848369435398-11.8412168961529
Winsorized Mean ( 15 / 29 )-17.3678160919541.30183130758784-13.341064998763
Winsorized Mean ( 16 / 29 )-17.3678160919541.24987194666507-13.8956763837248
Winsorized Mean ( 17 / 29 )-17.3678160919541.24987194666507-13.8956763837248
Winsorized Mean ( 18 / 29 )-17.98850574712641.16512797140702-15.439081533167
Winsorized Mean ( 19 / 29 )-17.77011494252871.13505315710474-15.6557557073858
Winsorized Mean ( 20 / 29 )-181.10550129782229-16.2822061226503
Winsorized Mean ( 21 / 29 )-181.10550129782229-16.2822061226503
Winsorized Mean ( 22 / 29 )-17.74712643678161.07139153243453-16.5645573065662
Winsorized Mean ( 23 / 29 )-18.01149425287361.03822868670657-17.3482918392565
Winsorized Mean ( 24 / 29 )-18.28735632183911.00478779618588-18.200217390435
Winsorized Mean ( 25 / 29 )-18.28735632183911.00478779618588-18.200217390435
Winsorized Mean ( 26 / 29 )-18.28735632183910.929326764217226-19.678069142066
Winsorized Mean ( 27 / 29 )-18.28735632183910.929326764217226-19.678069142066
Winsorized Mean ( 28 / 29 )-18.28735632183910.770844707238513-23.7237878785625
Winsorized Mean ( 29 / 29 )-18.28735632183910.770844707238513-23.7237878785625
Trimmed Mean ( 1 / 29 )-16.32941176470591.69604815309513-9.62791754167252
Trimmed Mean ( 2 / 29 )-16.40963855421691.66351278926626-9.86444989187901
Trimmed Mean ( 3 / 29 )-16.49382716049381.63120831688763-10.1114167882397
Trimmed Mean ( 4 / 29 )-16.58227848101271.59362243186744-10.4053997668577
Trimmed Mean ( 5 / 29 )-16.68831168831171.55830627118418-10.7092629972091
Trimmed Mean ( 6 / 29 )-16.78666666666671.52649788594541-10.9968489450414
Trimmed Mean ( 7 / 29 )-16.90410958904111.49162609107356-11.3326722361599
Trimmed Mean ( 8 / 29 )-17.01408450704231.45426493532343-11.6994394169714
Trimmed Mean ( 9 / 29 )-17.10144927536231.42474552064879-12.0031605837755
Trimmed Mean ( 10 / 29 )-17.16417910447761.39725728220519-12.2841937008112
Trimmed Mean ( 11 / 29 )-17.23076923076921.3713709505541-12.5646304698281
Trimmed Mean ( 12 / 29 )-17.31746031746031.34324758673734-12.8922325924466
Trimmed Mean ( 13 / 29 )-17.39344262295081.31350253171934-13.2420320501273
Trimmed Mean ( 14 / 29 )-17.47457627118641.28547974388872-13.5938169031928
Trimmed Mean ( 15 / 29 )-17.56140350877191.25081866521307-14.0399276067571
Trimmed Mean ( 16 / 29 )-17.58181818181821.22836589299141-14.3131767839968
Trimmed Mean ( 17 / 29 )-17.60377358490571.20934304955046-14.5564764203584
Trimmed Mean ( 18 / 29 )-17.62745098039221.18485898368812-14.8772564693927
Trimmed Mean ( 19 / 29 )-17.59183673469391.16894276297779-15.0493568135707
Trimmed Mean ( 20 / 29 )-17.57446808510641.1532621474781-15.2389186825714
Trimmed Mean ( 21 / 29 )-17.53333333333331.13733695690211-15.4161290784842
Trimmed Mean ( 22 / 29 )-17.48837209302331.11536738333352-15.6794723912003
Trimmed Mean ( 23 / 29 )-17.46341463414631.09271286979879-15.9817049078611
Trimmed Mean ( 24 / 29 )-17.41025641025641.06832568482188-16.2967685394171
Trimmed Mean ( 25 / 29 )-17.32432432432431.04123256111563-16.638285212443
Trimmed Mean ( 26 / 29 )-17.22857142857141.00258968398332-17.1840701174201
Trimmed Mean ( 27 / 29 )-17.12121212121210.968008710279627-17.6870434526011
Trimmed Mean ( 28 / 29 )-170.91698430469325-18.5390305079288
Trimmed Mean ( 29 / 29 )-16.86206896551720.891564377506751-18.9129011778957
Median-16
Midrange-12.5
Midmean - Weighted Average at Xnp-17.8541666666667
Midmean - Weighted Average at X(n+1)p-17.8541666666667
Midmean - Empirical Distribution Function-17.8541666666667
Midmean - Empirical Distribution Function - Averaging-17.8541666666667
Midmean - Empirical Distribution Function - Interpolation-16.9777777777778
Midmean - Closest Observation-17.8541666666667
Midmean - True Basic - Statistics Graphics Toolkit-17.8541666666667
Midmean - MS Excel (old versions)-17.8541666666667
Number of observations87



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')