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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 computationWed, 21 Oct 2009 09:47:30 -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/21/t1256140202upg6wb2gfkdcveb.htm/, Retrieved Thu, 02 May 2024 05:33:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=49449, Retrieved Thu, 02 May 2024 05:33:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact99
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
F RMPD  [Univariate Explorative Data Analysis] [Colombia Coffee] [2008-01-07 14:21:11] [74be16979710d4c4e7c6647856088456]
F RMPD    [Univariate Data Series] [] [2009-10-14 08:30:28] [74be16979710d4c4e7c6647856088456]
- RMPD        [Central Tendency] [WS3P2] [2009-10-21 15:47:30] [dd4f17965cad1d38de7a1c062d32d75d] [Current]
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Post a new message
Dataseries X:
10689
10773
6718
6519
9354
9224
13355
12006
8888
5602
1913
4426
5848
3683
2094
2893
1957
4288
9278
8979
2578
4292
3510
5027
8047
6601
4550
7264
2227
2081
4189
6650
2579
2388
3056
1938
3700
4365
4161
4264
4606
6012
5586
7659
10776
5846
9714
10095
10433
10942
3646
7629
8813
8516
9939
10231
5604
10880
13297
7982
13076
14680
2716
7200
3236
4846
5788
8372




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=49449&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=49449&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49449&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 Mean6618.73529411765405.0350674819416.3411413615755
Geometric Mean5740.53269949587
Harmonic Mean4884.26038411593
Quadratic Mean7402.650544787
Winsorized Mean ( 1 / 22 )6599.61764705882399.61600204577616.5148983355847
Winsorized Mean ( 2 / 22 )6598.4705882353399.08997253342416.5337919826654
Winsorized Mean ( 3 / 22 )6594.19117647059395.73638766716916.6630903348129
Winsorized Mean ( 4 / 22 )6532.01470588235381.14774711764517.1377497447628
Winsorized Mean ( 5 / 22 )6463.55882352941363.84899905029317.7643990787398
Winsorized Mean ( 6 / 22 )6472.29411764706360.41126582702917.9580793702306
Winsorized Mean ( 7 / 22 )6481.14705882353355.20978187778318.2459700984628
Winsorized Mean ( 8 / 22 )6480.91176470588355.1268082357318.2495706164878
Winsorized Mean ( 9 / 22 )6487.92647058824350.1841653414918.5271840154777
Winsorized Mean ( 10 / 22 )6476.30882352941339.39303441208419.0820322366016
Winsorized Mean ( 11 / 22 )6470329.65114652023719.6268087288536
Winsorized Mean ( 12 / 22 )6477.76470588235320.73576322978820.1965775211710
Winsorized Mean ( 13 / 22 )6500.32352941176307.99065114796321.1055871507246
Winsorized Mean ( 14 / 22 )6482296.32968286724221.8742852126089
Winsorized Mean ( 15 / 22 )6410.75282.5142528473522.6917754958859
Winsorized Mean ( 16 / 22 )6396.86764705882279.17004323474422.9138756183804
Winsorized Mean ( 17 / 22 )6498.61764705882261.04822551497624.8943184127716
Winsorized Mean ( 18 / 22 )6441.17647058824250.08777382871525.7556631896759
Winsorized Mean ( 19 / 22 )6436.70588235294243.4471953017226.4398440671108
Winsorized Mean ( 20 / 22 )6421.70588235294239.20384026762926.8461654928622
Winsorized Mean ( 21 / 22 )6331.22058823529225.55943800402228.0689677375522
Winsorized Mean ( 22 / 22 )6308.25215.68270477115529.2478249783320
Trimmed Mean ( 1 / 22 )6567.89393939394392.27053609290416.7432762215881
Trimmed Mean ( 2 / 22 )6534.1875383.3577068305917.0446227728703
Trimmed Mean ( 3 / 22 )6498.93548387097372.86037573637617.4299440401410
Trimmed Mean ( 4 / 22 )6462.95361.62626665839417.8719042168061
Trimmed Mean ( 5 / 22 )6442.70689655172353.48985906951518.2260020514047
Trimmed Mean ( 6 / 22 )6437.64285714286348.97076723156818.4475132636855
Trimmed Mean ( 7 / 22 )6430.37037037037344.13689349576718.6855012987716
Trimmed Mean ( 8 / 22 )6420.88461538462339.24840586987818.9267937720167
Trimmed Mean ( 9 / 22 )6410.68332.89767434404419.2572087282733
Trimmed Mean ( 10 / 22 )6398.52083333333325.85765992189419.6359380806547
Trimmed Mean ( 11 / 22 )6387.02173913043319.25150306885020.0062385853607
Trimmed Mean ( 12 / 22 )6375.36363636364312.78238504123220.3827451329243
Trimmed Mean ( 13 / 22 )6361.54761904762306.15101486881320.7791165473469
Trimmed Mean ( 14 / 22 )6343.4300.06165776643021.1403217832574
Trimmed Mean ( 15 / 22 )6325.68421052632294.33832563287321.4912013137437
Trimmed Mean ( 16 / 22 )6314.97222222222289.56764838950421.8082795413935
Trimmed Mean ( 17 / 22 )6304.73529411765283.26637032591422.2572672035290
Trimmed Mean ( 18 / 22 )6280.5278.41101911475422.5583743774571
Trimmed Mean ( 19 / 22 )6260.26666666667273.80679039686522.8638108557966
Trimmed Mean ( 20 / 22 )6237.71428571429268.05130035512123.2705988646592
Trimmed Mean ( 21 / 22 )6213.65384615385259.79636962174623.9174005980172
Trimmed Mean ( 22 / 22 )6197.79166666667251.34280663320424.6587191003695
Median5930
Midrange8296.5
Midmean - Weighted Average at Xnp6230.31428571429
Midmean - Weighted Average at X(n+1)p6304.73529411765
Midmean - Empirical Distribution Function6230.31428571429
Midmean - Empirical Distribution Function - Averaging6304.73529411765
Midmean - Empirical Distribution Function - Interpolation6304.73529411765
Midmean - Closest Observation6230.31428571429
Midmean - True Basic - Statistics Graphics Toolkit6304.73529411765
Midmean - MS Excel (old versions)6314.97222222222
Number of observations68

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 6618.73529411765 & 405.03506748194 & 16.3411413615755 \tabularnewline
Geometric Mean & 5740.53269949587 &  &  \tabularnewline
Harmonic Mean & 4884.26038411593 &  &  \tabularnewline
Quadratic Mean & 7402.650544787 &  &  \tabularnewline
Winsorized Mean ( 1 / 22 ) & 6599.61764705882 & 399.616002045776 & 16.5148983355847 \tabularnewline
Winsorized Mean ( 2 / 22 ) & 6598.4705882353 & 399.089972533424 & 16.5337919826654 \tabularnewline
Winsorized Mean ( 3 / 22 ) & 6594.19117647059 & 395.736387667169 & 16.6630903348129 \tabularnewline
Winsorized Mean ( 4 / 22 ) & 6532.01470588235 & 381.147747117645 & 17.1377497447628 \tabularnewline
Winsorized Mean ( 5 / 22 ) & 6463.55882352941 & 363.848999050293 & 17.7643990787398 \tabularnewline
Winsorized Mean ( 6 / 22 ) & 6472.29411764706 & 360.411265827029 & 17.9580793702306 \tabularnewline
Winsorized Mean ( 7 / 22 ) & 6481.14705882353 & 355.209781877783 & 18.2459700984628 \tabularnewline
Winsorized Mean ( 8 / 22 ) & 6480.91176470588 & 355.12680823573 & 18.2495706164878 \tabularnewline
Winsorized Mean ( 9 / 22 ) & 6487.92647058824 & 350.18416534149 & 18.5271840154777 \tabularnewline
Winsorized Mean ( 10 / 22 ) & 6476.30882352941 & 339.393034412084 & 19.0820322366016 \tabularnewline
Winsorized Mean ( 11 / 22 ) & 6470 & 329.651146520237 & 19.6268087288536 \tabularnewline
Winsorized Mean ( 12 / 22 ) & 6477.76470588235 & 320.735763229788 & 20.1965775211710 \tabularnewline
Winsorized Mean ( 13 / 22 ) & 6500.32352941176 & 307.990651147963 & 21.1055871507246 \tabularnewline
Winsorized Mean ( 14 / 22 ) & 6482 & 296.329682867242 & 21.8742852126089 \tabularnewline
Winsorized Mean ( 15 / 22 ) & 6410.75 & 282.51425284735 & 22.6917754958859 \tabularnewline
Winsorized Mean ( 16 / 22 ) & 6396.86764705882 & 279.170043234744 & 22.9138756183804 \tabularnewline
Winsorized Mean ( 17 / 22 ) & 6498.61764705882 & 261.048225514976 & 24.8943184127716 \tabularnewline
Winsorized Mean ( 18 / 22 ) & 6441.17647058824 & 250.087773828715 & 25.7556631896759 \tabularnewline
Winsorized Mean ( 19 / 22 ) & 6436.70588235294 & 243.44719530172 & 26.4398440671108 \tabularnewline
Winsorized Mean ( 20 / 22 ) & 6421.70588235294 & 239.203840267629 & 26.8461654928622 \tabularnewline
Winsorized Mean ( 21 / 22 ) & 6331.22058823529 & 225.559438004022 & 28.0689677375522 \tabularnewline
Winsorized Mean ( 22 / 22 ) & 6308.25 & 215.682704771155 & 29.2478249783320 \tabularnewline
Trimmed Mean ( 1 / 22 ) & 6567.89393939394 & 392.270536092904 & 16.7432762215881 \tabularnewline
Trimmed Mean ( 2 / 22 ) & 6534.1875 & 383.35770683059 & 17.0446227728703 \tabularnewline
Trimmed Mean ( 3 / 22 ) & 6498.93548387097 & 372.860375736376 & 17.4299440401410 \tabularnewline
Trimmed Mean ( 4 / 22 ) & 6462.95 & 361.626266658394 & 17.8719042168061 \tabularnewline
Trimmed Mean ( 5 / 22 ) & 6442.70689655172 & 353.489859069515 & 18.2260020514047 \tabularnewline
Trimmed Mean ( 6 / 22 ) & 6437.64285714286 & 348.970767231568 & 18.4475132636855 \tabularnewline
Trimmed Mean ( 7 / 22 ) & 6430.37037037037 & 344.136893495767 & 18.6855012987716 \tabularnewline
Trimmed Mean ( 8 / 22 ) & 6420.88461538462 & 339.248405869878 & 18.9267937720167 \tabularnewline
Trimmed Mean ( 9 / 22 ) & 6410.68 & 332.897674344044 & 19.2572087282733 \tabularnewline
Trimmed Mean ( 10 / 22 ) & 6398.52083333333 & 325.857659921894 & 19.6359380806547 \tabularnewline
Trimmed Mean ( 11 / 22 ) & 6387.02173913043 & 319.251503068850 & 20.0062385853607 \tabularnewline
Trimmed Mean ( 12 / 22 ) & 6375.36363636364 & 312.782385041232 & 20.3827451329243 \tabularnewline
Trimmed Mean ( 13 / 22 ) & 6361.54761904762 & 306.151014868813 & 20.7791165473469 \tabularnewline
Trimmed Mean ( 14 / 22 ) & 6343.4 & 300.061657766430 & 21.1403217832574 \tabularnewline
Trimmed Mean ( 15 / 22 ) & 6325.68421052632 & 294.338325632873 & 21.4912013137437 \tabularnewline
Trimmed Mean ( 16 / 22 ) & 6314.97222222222 & 289.567648389504 & 21.8082795413935 \tabularnewline
Trimmed Mean ( 17 / 22 ) & 6304.73529411765 & 283.266370325914 & 22.2572672035290 \tabularnewline
Trimmed Mean ( 18 / 22 ) & 6280.5 & 278.411019114754 & 22.5583743774571 \tabularnewline
Trimmed Mean ( 19 / 22 ) & 6260.26666666667 & 273.806790396865 & 22.8638108557966 \tabularnewline
Trimmed Mean ( 20 / 22 ) & 6237.71428571429 & 268.051300355121 & 23.2705988646592 \tabularnewline
Trimmed Mean ( 21 / 22 ) & 6213.65384615385 & 259.796369621746 & 23.9174005980172 \tabularnewline
Trimmed Mean ( 22 / 22 ) & 6197.79166666667 & 251.342806633204 & 24.6587191003695 \tabularnewline
Median & 5930 &  &  \tabularnewline
Midrange & 8296.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 6230.31428571429 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 6304.73529411765 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 6230.31428571429 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 6304.73529411765 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 6304.73529411765 &  &  \tabularnewline
Midmean - Closest Observation & 6230.31428571429 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 6304.73529411765 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 6314.97222222222 &  &  \tabularnewline
Number of observations & 68 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49449&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]6618.73529411765[/C][C]405.03506748194[/C][C]16.3411413615755[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]5740.53269949587[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]4884.26038411593[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]7402.650544787[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 22 )[/C][C]6599.61764705882[/C][C]399.616002045776[/C][C]16.5148983355847[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 22 )[/C][C]6598.4705882353[/C][C]399.089972533424[/C][C]16.5337919826654[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 22 )[/C][C]6594.19117647059[/C][C]395.736387667169[/C][C]16.6630903348129[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 22 )[/C][C]6532.01470588235[/C][C]381.147747117645[/C][C]17.1377497447628[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 22 )[/C][C]6463.55882352941[/C][C]363.848999050293[/C][C]17.7643990787398[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 22 )[/C][C]6472.29411764706[/C][C]360.411265827029[/C][C]17.9580793702306[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 22 )[/C][C]6481.14705882353[/C][C]355.209781877783[/C][C]18.2459700984628[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 22 )[/C][C]6480.91176470588[/C][C]355.12680823573[/C][C]18.2495706164878[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 22 )[/C][C]6487.92647058824[/C][C]350.18416534149[/C][C]18.5271840154777[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 22 )[/C][C]6476.30882352941[/C][C]339.393034412084[/C][C]19.0820322366016[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 22 )[/C][C]6470[/C][C]329.651146520237[/C][C]19.6268087288536[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 22 )[/C][C]6477.76470588235[/C][C]320.735763229788[/C][C]20.1965775211710[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 22 )[/C][C]6500.32352941176[/C][C]307.990651147963[/C][C]21.1055871507246[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 22 )[/C][C]6482[/C][C]296.329682867242[/C][C]21.8742852126089[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 22 )[/C][C]6410.75[/C][C]282.51425284735[/C][C]22.6917754958859[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 22 )[/C][C]6396.86764705882[/C][C]279.170043234744[/C][C]22.9138756183804[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 22 )[/C][C]6498.61764705882[/C][C]261.048225514976[/C][C]24.8943184127716[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 22 )[/C][C]6441.17647058824[/C][C]250.087773828715[/C][C]25.7556631896759[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 22 )[/C][C]6436.70588235294[/C][C]243.44719530172[/C][C]26.4398440671108[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 22 )[/C][C]6421.70588235294[/C][C]239.203840267629[/C][C]26.8461654928622[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 22 )[/C][C]6331.22058823529[/C][C]225.559438004022[/C][C]28.0689677375522[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 22 )[/C][C]6308.25[/C][C]215.682704771155[/C][C]29.2478249783320[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 22 )[/C][C]6567.89393939394[/C][C]392.270536092904[/C][C]16.7432762215881[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 22 )[/C][C]6534.1875[/C][C]383.35770683059[/C][C]17.0446227728703[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 22 )[/C][C]6498.93548387097[/C][C]372.860375736376[/C][C]17.4299440401410[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 22 )[/C][C]6462.95[/C][C]361.626266658394[/C][C]17.8719042168061[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 22 )[/C][C]6442.70689655172[/C][C]353.489859069515[/C][C]18.2260020514047[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 22 )[/C][C]6437.64285714286[/C][C]348.970767231568[/C][C]18.4475132636855[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 22 )[/C][C]6430.37037037037[/C][C]344.136893495767[/C][C]18.6855012987716[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 22 )[/C][C]6420.88461538462[/C][C]339.248405869878[/C][C]18.9267937720167[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 22 )[/C][C]6410.68[/C][C]332.897674344044[/C][C]19.2572087282733[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 22 )[/C][C]6398.52083333333[/C][C]325.857659921894[/C][C]19.6359380806547[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 22 )[/C][C]6387.02173913043[/C][C]319.251503068850[/C][C]20.0062385853607[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 22 )[/C][C]6375.36363636364[/C][C]312.782385041232[/C][C]20.3827451329243[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 22 )[/C][C]6361.54761904762[/C][C]306.151014868813[/C][C]20.7791165473469[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 22 )[/C][C]6343.4[/C][C]300.061657766430[/C][C]21.1403217832574[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 22 )[/C][C]6325.68421052632[/C][C]294.338325632873[/C][C]21.4912013137437[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 22 )[/C][C]6314.97222222222[/C][C]289.567648389504[/C][C]21.8082795413935[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 22 )[/C][C]6304.73529411765[/C][C]283.266370325914[/C][C]22.2572672035290[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 22 )[/C][C]6280.5[/C][C]278.411019114754[/C][C]22.5583743774571[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 22 )[/C][C]6260.26666666667[/C][C]273.806790396865[/C][C]22.8638108557966[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 22 )[/C][C]6237.71428571429[/C][C]268.051300355121[/C][C]23.2705988646592[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 22 )[/C][C]6213.65384615385[/C][C]259.796369621746[/C][C]23.9174005980172[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 22 )[/C][C]6197.79166666667[/C][C]251.342806633204[/C][C]24.6587191003695[/C][/ROW]
[ROW][C]Median[/C][C]5930[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]8296.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]6230.31428571429[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]6304.73529411765[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]6230.31428571429[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]6304.73529411765[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]6304.73529411765[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]6230.31428571429[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]6304.73529411765[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]6314.97222222222[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]68[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=49449&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49449&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 Mean6618.73529411765405.0350674819416.3411413615755
Geometric Mean5740.53269949587
Harmonic Mean4884.26038411593
Quadratic Mean7402.650544787
Winsorized Mean ( 1 / 22 )6599.61764705882399.61600204577616.5148983355847
Winsorized Mean ( 2 / 22 )6598.4705882353399.08997253342416.5337919826654
Winsorized Mean ( 3 / 22 )6594.19117647059395.73638766716916.6630903348129
Winsorized Mean ( 4 / 22 )6532.01470588235381.14774711764517.1377497447628
Winsorized Mean ( 5 / 22 )6463.55882352941363.84899905029317.7643990787398
Winsorized Mean ( 6 / 22 )6472.29411764706360.41126582702917.9580793702306
Winsorized Mean ( 7 / 22 )6481.14705882353355.20978187778318.2459700984628
Winsorized Mean ( 8 / 22 )6480.91176470588355.1268082357318.2495706164878
Winsorized Mean ( 9 / 22 )6487.92647058824350.1841653414918.5271840154777
Winsorized Mean ( 10 / 22 )6476.30882352941339.39303441208419.0820322366016
Winsorized Mean ( 11 / 22 )6470329.65114652023719.6268087288536
Winsorized Mean ( 12 / 22 )6477.76470588235320.73576322978820.1965775211710
Winsorized Mean ( 13 / 22 )6500.32352941176307.99065114796321.1055871507246
Winsorized Mean ( 14 / 22 )6482296.32968286724221.8742852126089
Winsorized Mean ( 15 / 22 )6410.75282.5142528473522.6917754958859
Winsorized Mean ( 16 / 22 )6396.86764705882279.17004323474422.9138756183804
Winsorized Mean ( 17 / 22 )6498.61764705882261.04822551497624.8943184127716
Winsorized Mean ( 18 / 22 )6441.17647058824250.08777382871525.7556631896759
Winsorized Mean ( 19 / 22 )6436.70588235294243.4471953017226.4398440671108
Winsorized Mean ( 20 / 22 )6421.70588235294239.20384026762926.8461654928622
Winsorized Mean ( 21 / 22 )6331.22058823529225.55943800402228.0689677375522
Winsorized Mean ( 22 / 22 )6308.25215.68270477115529.2478249783320
Trimmed Mean ( 1 / 22 )6567.89393939394392.27053609290416.7432762215881
Trimmed Mean ( 2 / 22 )6534.1875383.3577068305917.0446227728703
Trimmed Mean ( 3 / 22 )6498.93548387097372.86037573637617.4299440401410
Trimmed Mean ( 4 / 22 )6462.95361.62626665839417.8719042168061
Trimmed Mean ( 5 / 22 )6442.70689655172353.48985906951518.2260020514047
Trimmed Mean ( 6 / 22 )6437.64285714286348.97076723156818.4475132636855
Trimmed Mean ( 7 / 22 )6430.37037037037344.13689349576718.6855012987716
Trimmed Mean ( 8 / 22 )6420.88461538462339.24840586987818.9267937720167
Trimmed Mean ( 9 / 22 )6410.68332.89767434404419.2572087282733
Trimmed Mean ( 10 / 22 )6398.52083333333325.85765992189419.6359380806547
Trimmed Mean ( 11 / 22 )6387.02173913043319.25150306885020.0062385853607
Trimmed Mean ( 12 / 22 )6375.36363636364312.78238504123220.3827451329243
Trimmed Mean ( 13 / 22 )6361.54761904762306.15101486881320.7791165473469
Trimmed Mean ( 14 / 22 )6343.4300.06165776643021.1403217832574
Trimmed Mean ( 15 / 22 )6325.68421052632294.33832563287321.4912013137437
Trimmed Mean ( 16 / 22 )6314.97222222222289.56764838950421.8082795413935
Trimmed Mean ( 17 / 22 )6304.73529411765283.26637032591422.2572672035290
Trimmed Mean ( 18 / 22 )6280.5278.41101911475422.5583743774571
Trimmed Mean ( 19 / 22 )6260.26666666667273.80679039686522.8638108557966
Trimmed Mean ( 20 / 22 )6237.71428571429268.05130035512123.2705988646592
Trimmed Mean ( 21 / 22 )6213.65384615385259.79636962174623.9174005980172
Trimmed Mean ( 22 / 22 )6197.79166666667251.34280663320424.6587191003695
Median5930
Midrange8296.5
Midmean - Weighted Average at Xnp6230.31428571429
Midmean - Weighted Average at X(n+1)p6304.73529411765
Midmean - Empirical Distribution Function6230.31428571429
Midmean - Empirical Distribution Function - Averaging6304.73529411765
Midmean - Empirical Distribution Function - Interpolation6304.73529411765
Midmean - Closest Observation6230.31428571429
Midmean - True Basic - Statistics Graphics Toolkit6304.73529411765
Midmean - MS Excel (old versions)6314.97222222222
Number of observations68



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')