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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 computationWed, 25 Feb 2015 19:10:22 +0000
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/Feb/25/t1424891507nkomsb3tve37c79.htm/, Retrieved Sat, 18 May 2024 01:37:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=277512, Retrieved Sat, 18 May 2024 01:37:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2015-02-25 19:10:22] [bad5dfd772bc354c7f8aa9414b1d4071] [Current]
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Dataseries X:
1329
1385
1681
1591
1598
1557
1190
932
1664
1717
1567
1355
1430
1863
1868
1711
1873
2095
1379
1021
1999
2094
2026
1390
1744
2117
1823
1963
1816
1966
1309
1250
2184
2295
1870
1222
1640
2194
2179
1976
1850
2077
1658
1156
2400
2218
1802
1444
1804
1541
2206
1972
1815
1749
1492
1307
1916
2035
1855
1086
1951
1733
1868
1532
1894
1586
1247
1212
2119
1931
1649
1296
1625
1454
1562
1612
1648
1412
1219
1207
1614
1537
1497
1141
1135
1368
1203
1201
1190
1347
607
914
1606
1518
1120
910




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=277512&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=277512&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=277512&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'Gertrude Mary Cox' @ cox.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean1613.6562537.150278115547143.4359130497248
Geometric Mean1569.3948183587
Harmonic Mean1520.1378075298
Quadratic Mean1653.78356919822
Winsorized Mean ( 1 / 32 )1615.7187536.143848519119144.7024546693009
Winsorized Mean ( 2 / 32 )1614.1979166666735.825667131163245.0570232441685
Winsorized Mean ( 3 / 32 )1614.3854166666735.645102422474545.2905254004484
Winsorized Mean ( 4 / 32 )1617.5937534.849688444468746.4163044836845
Winsorized Mean ( 5 / 32 )1620.4583333333334.175209404852247.4161932451323
Winsorized Mean ( 6 / 32 )1622.2708333333333.77972530857148.0249859498327
Winsorized Mean ( 7 / 32 )1618.9895833333332.879313121079149.2403712136977
Winsorized Mean ( 8 / 32 )1619.3229166666732.775510670850249.4064892818545
Winsorized Mean ( 9 / 32 )1618.6666666666732.235984533288450.2130364591519
Winsorized Mean ( 10 / 32 )1622.1041666666731.697969797621751.1737558279955
Winsorized Mean ( 11 / 32 )1620.1562531.396147126890951.6036647252278
Winsorized Mean ( 12 / 32 )1616.2812530.415376215566253.140268216469
Winsorized Mean ( 13 / 32 )1615.3333333333330.200919537915953.4862301561829
Winsorized Mean ( 14 / 32 )1611.9791666666729.563743127553954.5255436604128
Winsorized Mean ( 15 / 32 )1609.1666666666728.963784353802455.5578872915968
Winsorized Mean ( 16 / 32 )1609.6666666666728.707293477971956.0716971769498
Winsorized Mean ( 17 / 32 )1609.1354166666728.490621032129556.4794784519443
Winsorized Mean ( 18 / 32 )1613.2604166666727.755314983309758.1243778943522
Winsorized Mean ( 19 / 32 )1611.4791666666727.360146692045258.8987765601123
Winsorized Mean ( 20 / 32 )1616.8958333333325.516147618536363.3675528730181
Winsorized Mean ( 21 / 32 )1616.0208333333324.777177968099365.222150618362
Winsorized Mean ( 22 / 32 )1611.437524.08408066208366.9088234095223
Winsorized Mean ( 23 / 32 )1611.1979166666722.841298488067270.5388057298229
Winsorized Mean ( 24 / 32 )1614.9479166666722.171715078354172.8382044852864
Winsorized Mean ( 25 / 32 )1616.5104166666721.844837575097373.9996537447116
Winsorized Mean ( 26 / 32 )1620.0312521.404774087933875.6855103139461
Winsorized Mean ( 27 / 32 )1621.7187520.852104016462677.7724276034524
Winsorized Mean ( 28 / 32 )1621.1354166666720.354827328384579.6437813258194
Winsorized Mean ( 29 / 32 )1621.1354166666719.988316871558381.1041483424454
Winsorized Mean ( 30 / 32 )1619.5729166666718.149100702623389.2370891100169
Winsorized Mean ( 31 / 32 )1623.12517.188482029361594.4309682046013
Winsorized Mean ( 32 / 32 )1627.4583333333316.601514652063898.0307139102524
Trimmed Mean ( 1 / 32 )161635.399307317950645.6506107728425
Trimmed Mean ( 2 / 32 )1616.2934782608734.552651120931746.7776979718274
Trimmed Mean ( 3 / 32 )1617.4111111111133.779470951879647.8814814303986
Trimmed Mean ( 4 / 32 )1618.5113636363632.972511564815649.086687268417
Trimmed Mean ( 5 / 32 )1618.7674418604732.318709029435350.0876269651155
Trimmed Mean ( 6 / 32 )1618.3809523809531.758433201157850.9590930424727
Trimmed Mean ( 7 / 32 )1617.6219512195131.208763893578151.8322980280669
Trimmed Mean ( 8 / 32 )1617.387530.773038574138952.5585894322188
Trimmed Mean ( 9 / 32 )1617.0897435897430.284334581508853.3969052295809
Trimmed Mean ( 10 / 32 )1616.8684210526329.816228608896654.2277979640318
Trimmed Mean ( 11 / 32 )1616.1891891891929.36271575515855.0422243863897
Trimmed Mean ( 12 / 32 )1615.7083333333328.87915595155455.9472145253743
Trimmed Mean ( 13 / 32 )1615.6428571428628.472674312231156.7436286253173
Trimmed Mean ( 14 / 32 )1615.6764705882428.019891664220657.6617672170139
Trimmed Mean ( 15 / 32 )1616.0606060606127.579162422037258.5971604695757
Trimmed Mean ( 16 / 32 )1616.7527.141265878585459.5679658875316
Trimmed Mean ( 17 / 32 )1617.4354838709726.648351709739560.6955169868845
Trimmed Mean ( 18 / 32 )1618.2166666666726.080201071833662.0477066955718
Trimmed Mean ( 19 / 32 )1618.672413793125.508362956499863.4565384126562
Trimmed Mean ( 20 / 32 )1619.3214285714324.868173306442565.1162193787639
Trimmed Mean ( 21 / 32 )1619.5370370370424.393906872348966.3910477936941
Trimmed Mean ( 22 / 32 )1619.8461538461523.920862875436167.7168780357645
Trimmed Mean ( 23 / 32 )1620.5823.436254663513669.1484208235277
Trimmed Mean ( 24 / 32 )1621.3958333333323.033619808327770.3925760182568
Trimmed Mean ( 25 / 32 )1621.9565217391322.627031769272671.6822488375051
Trimmed Mean ( 26 / 32 )1622.4318181818222.146814510136173.2580217095901
Trimmed Mean ( 27 / 32 )1622.6428571428621.593725737033975.1441820139439
Trimmed Mean ( 28 / 32 )1622.72520.96725125046277.393311150609
Trimmed Mean ( 29 / 32 )1622.8684210526320.228958688817980.225010393131
Trimmed Mean ( 30 / 32 )1623.0277777777819.30402072236284.0771879144142
Trimmed Mean ( 31 / 32 )1623.3529411764718.52415113621187.6344038244832
Trimmed Mean ( 32 / 32 )1623.37517.692190618206991.7565854354632
Median1613
Midrange1503.5
Midmean - Weighted Average at Xnp1615.42857142857
Midmean - Weighted Average at X(n+1)p1621.39583333333
Midmean - Empirical Distribution Function1615.42857142857
Midmean - Empirical Distribution Function - Averaging1621.39583333333
Midmean - Empirical Distribution Function - Interpolation1621.39583333333
Midmean - Closest Observation1615.42857142857
Midmean - True Basic - Statistics Graphics Toolkit1621.39583333333
Midmean - MS Excel (old versions)1620.58
Number of observations96

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 1613.65625 & 37.1502781155471 & 43.4359130497248 \tabularnewline
Geometric Mean & 1569.3948183587 &  &  \tabularnewline
Harmonic Mean & 1520.1378075298 &  &  \tabularnewline
Quadratic Mean & 1653.78356919822 &  &  \tabularnewline
Winsorized Mean ( 1 / 32 ) & 1615.71875 & 36.1438485191191 & 44.7024546693009 \tabularnewline
Winsorized Mean ( 2 / 32 ) & 1614.19791666667 & 35.8256671311632 & 45.0570232441685 \tabularnewline
Winsorized Mean ( 3 / 32 ) & 1614.38541666667 & 35.6451024224745 & 45.2905254004484 \tabularnewline
Winsorized Mean ( 4 / 32 ) & 1617.59375 & 34.8496884444687 & 46.4163044836845 \tabularnewline
Winsorized Mean ( 5 / 32 ) & 1620.45833333333 & 34.1752094048522 & 47.4161932451323 \tabularnewline
Winsorized Mean ( 6 / 32 ) & 1622.27083333333 & 33.779725308571 & 48.0249859498327 \tabularnewline
Winsorized Mean ( 7 / 32 ) & 1618.98958333333 & 32.8793131210791 & 49.2403712136977 \tabularnewline
Winsorized Mean ( 8 / 32 ) & 1619.32291666667 & 32.7755106708502 & 49.4064892818545 \tabularnewline
Winsorized Mean ( 9 / 32 ) & 1618.66666666667 & 32.2359845332884 & 50.2130364591519 \tabularnewline
Winsorized Mean ( 10 / 32 ) & 1622.10416666667 & 31.6979697976217 & 51.1737558279955 \tabularnewline
Winsorized Mean ( 11 / 32 ) & 1620.15625 & 31.3961471268909 & 51.6036647252278 \tabularnewline
Winsorized Mean ( 12 / 32 ) & 1616.28125 & 30.4153762155662 & 53.140268216469 \tabularnewline
Winsorized Mean ( 13 / 32 ) & 1615.33333333333 & 30.2009195379159 & 53.4862301561829 \tabularnewline
Winsorized Mean ( 14 / 32 ) & 1611.97916666667 & 29.5637431275539 & 54.5255436604128 \tabularnewline
Winsorized Mean ( 15 / 32 ) & 1609.16666666667 & 28.9637843538024 & 55.5578872915968 \tabularnewline
Winsorized Mean ( 16 / 32 ) & 1609.66666666667 & 28.7072934779719 & 56.0716971769498 \tabularnewline
Winsorized Mean ( 17 / 32 ) & 1609.13541666667 & 28.4906210321295 & 56.4794784519443 \tabularnewline
Winsorized Mean ( 18 / 32 ) & 1613.26041666667 & 27.7553149833097 & 58.1243778943522 \tabularnewline
Winsorized Mean ( 19 / 32 ) & 1611.47916666667 & 27.3601466920452 & 58.8987765601123 \tabularnewline
Winsorized Mean ( 20 / 32 ) & 1616.89583333333 & 25.5161476185363 & 63.3675528730181 \tabularnewline
Winsorized Mean ( 21 / 32 ) & 1616.02083333333 & 24.7771779680993 & 65.222150618362 \tabularnewline
Winsorized Mean ( 22 / 32 ) & 1611.4375 & 24.084080662083 & 66.9088234095223 \tabularnewline
Winsorized Mean ( 23 / 32 ) & 1611.19791666667 & 22.8412984880672 & 70.5388057298229 \tabularnewline
Winsorized Mean ( 24 / 32 ) & 1614.94791666667 & 22.1717150783541 & 72.8382044852864 \tabularnewline
Winsorized Mean ( 25 / 32 ) & 1616.51041666667 & 21.8448375750973 & 73.9996537447116 \tabularnewline
Winsorized Mean ( 26 / 32 ) & 1620.03125 & 21.4047740879338 & 75.6855103139461 \tabularnewline
Winsorized Mean ( 27 / 32 ) & 1621.71875 & 20.8521040164626 & 77.7724276034524 \tabularnewline
Winsorized Mean ( 28 / 32 ) & 1621.13541666667 & 20.3548273283845 & 79.6437813258194 \tabularnewline
Winsorized Mean ( 29 / 32 ) & 1621.13541666667 & 19.9883168715583 & 81.1041483424454 \tabularnewline
Winsorized Mean ( 30 / 32 ) & 1619.57291666667 & 18.1491007026233 & 89.2370891100169 \tabularnewline
Winsorized Mean ( 31 / 32 ) & 1623.125 & 17.1884820293615 & 94.4309682046013 \tabularnewline
Winsorized Mean ( 32 / 32 ) & 1627.45833333333 & 16.6015146520638 & 98.0307139102524 \tabularnewline
Trimmed Mean ( 1 / 32 ) & 1616 & 35.3993073179506 & 45.6506107728425 \tabularnewline
Trimmed Mean ( 2 / 32 ) & 1616.29347826087 & 34.5526511209317 & 46.7776979718274 \tabularnewline
Trimmed Mean ( 3 / 32 ) & 1617.41111111111 & 33.7794709518796 & 47.8814814303986 \tabularnewline
Trimmed Mean ( 4 / 32 ) & 1618.51136363636 & 32.9725115648156 & 49.086687268417 \tabularnewline
Trimmed Mean ( 5 / 32 ) & 1618.76744186047 & 32.3187090294353 & 50.0876269651155 \tabularnewline
Trimmed Mean ( 6 / 32 ) & 1618.38095238095 & 31.7584332011578 & 50.9590930424727 \tabularnewline
Trimmed Mean ( 7 / 32 ) & 1617.62195121951 & 31.2087638935781 & 51.8322980280669 \tabularnewline
Trimmed Mean ( 8 / 32 ) & 1617.3875 & 30.7730385741389 & 52.5585894322188 \tabularnewline
Trimmed Mean ( 9 / 32 ) & 1617.08974358974 & 30.2843345815088 & 53.3969052295809 \tabularnewline
Trimmed Mean ( 10 / 32 ) & 1616.86842105263 & 29.8162286088966 & 54.2277979640318 \tabularnewline
Trimmed Mean ( 11 / 32 ) & 1616.18918918919 & 29.362715755158 & 55.0422243863897 \tabularnewline
Trimmed Mean ( 12 / 32 ) & 1615.70833333333 & 28.879155951554 & 55.9472145253743 \tabularnewline
Trimmed Mean ( 13 / 32 ) & 1615.64285714286 & 28.4726743122311 & 56.7436286253173 \tabularnewline
Trimmed Mean ( 14 / 32 ) & 1615.67647058824 & 28.0198916642206 & 57.6617672170139 \tabularnewline
Trimmed Mean ( 15 / 32 ) & 1616.06060606061 & 27.5791624220372 & 58.5971604695757 \tabularnewline
Trimmed Mean ( 16 / 32 ) & 1616.75 & 27.1412658785854 & 59.5679658875316 \tabularnewline
Trimmed Mean ( 17 / 32 ) & 1617.43548387097 & 26.6483517097395 & 60.6955169868845 \tabularnewline
Trimmed Mean ( 18 / 32 ) & 1618.21666666667 & 26.0802010718336 & 62.0477066955718 \tabularnewline
Trimmed Mean ( 19 / 32 ) & 1618.6724137931 & 25.5083629564998 & 63.4565384126562 \tabularnewline
Trimmed Mean ( 20 / 32 ) & 1619.32142857143 & 24.8681733064425 & 65.1162193787639 \tabularnewline
Trimmed Mean ( 21 / 32 ) & 1619.53703703704 & 24.3939068723489 & 66.3910477936941 \tabularnewline
Trimmed Mean ( 22 / 32 ) & 1619.84615384615 & 23.9208628754361 & 67.7168780357645 \tabularnewline
Trimmed Mean ( 23 / 32 ) & 1620.58 & 23.4362546635136 & 69.1484208235277 \tabularnewline
Trimmed Mean ( 24 / 32 ) & 1621.39583333333 & 23.0336198083277 & 70.3925760182568 \tabularnewline
Trimmed Mean ( 25 / 32 ) & 1621.95652173913 & 22.6270317692726 & 71.6822488375051 \tabularnewline
Trimmed Mean ( 26 / 32 ) & 1622.43181818182 & 22.1468145101361 & 73.2580217095901 \tabularnewline
Trimmed Mean ( 27 / 32 ) & 1622.64285714286 & 21.5937257370339 & 75.1441820139439 \tabularnewline
Trimmed Mean ( 28 / 32 ) & 1622.725 & 20.967251250462 & 77.393311150609 \tabularnewline
Trimmed Mean ( 29 / 32 ) & 1622.86842105263 & 20.2289586888179 & 80.225010393131 \tabularnewline
Trimmed Mean ( 30 / 32 ) & 1623.02777777778 & 19.304020722362 & 84.0771879144142 \tabularnewline
Trimmed Mean ( 31 / 32 ) & 1623.35294117647 & 18.524151136211 & 87.6344038244832 \tabularnewline
Trimmed Mean ( 32 / 32 ) & 1623.375 & 17.6921906182069 & 91.7565854354632 \tabularnewline
Median & 1613 &  &  \tabularnewline
Midrange & 1503.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 1615.42857142857 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 1621.39583333333 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 1615.42857142857 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 1621.39583333333 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 1621.39583333333 &  &  \tabularnewline
Midmean - Closest Observation & 1615.42857142857 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 1621.39583333333 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 1620.58 &  &  \tabularnewline
Number of observations & 96 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=277512&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]1613.65625[/C][C]37.1502781155471[/C][C]43.4359130497248[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]1569.3948183587[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]1520.1378075298[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]1653.78356919822[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 32 )[/C][C]1615.71875[/C][C]36.1438485191191[/C][C]44.7024546693009[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 32 )[/C][C]1614.19791666667[/C][C]35.8256671311632[/C][C]45.0570232441685[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 32 )[/C][C]1614.38541666667[/C][C]35.6451024224745[/C][C]45.2905254004484[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 32 )[/C][C]1617.59375[/C][C]34.8496884444687[/C][C]46.4163044836845[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 32 )[/C][C]1620.45833333333[/C][C]34.1752094048522[/C][C]47.4161932451323[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 32 )[/C][C]1622.27083333333[/C][C]33.779725308571[/C][C]48.0249859498327[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 32 )[/C][C]1618.98958333333[/C][C]32.8793131210791[/C][C]49.2403712136977[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 32 )[/C][C]1619.32291666667[/C][C]32.7755106708502[/C][C]49.4064892818545[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 32 )[/C][C]1618.66666666667[/C][C]32.2359845332884[/C][C]50.2130364591519[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 32 )[/C][C]1622.10416666667[/C][C]31.6979697976217[/C][C]51.1737558279955[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 32 )[/C][C]1620.15625[/C][C]31.3961471268909[/C][C]51.6036647252278[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 32 )[/C][C]1616.28125[/C][C]30.4153762155662[/C][C]53.140268216469[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 32 )[/C][C]1615.33333333333[/C][C]30.2009195379159[/C][C]53.4862301561829[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 32 )[/C][C]1611.97916666667[/C][C]29.5637431275539[/C][C]54.5255436604128[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 32 )[/C][C]1609.16666666667[/C][C]28.9637843538024[/C][C]55.5578872915968[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 32 )[/C][C]1609.66666666667[/C][C]28.7072934779719[/C][C]56.0716971769498[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 32 )[/C][C]1609.13541666667[/C][C]28.4906210321295[/C][C]56.4794784519443[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 32 )[/C][C]1613.26041666667[/C][C]27.7553149833097[/C][C]58.1243778943522[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 32 )[/C][C]1611.47916666667[/C][C]27.3601466920452[/C][C]58.8987765601123[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 32 )[/C][C]1616.89583333333[/C][C]25.5161476185363[/C][C]63.3675528730181[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 32 )[/C][C]1616.02083333333[/C][C]24.7771779680993[/C][C]65.222150618362[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 32 )[/C][C]1611.4375[/C][C]24.084080662083[/C][C]66.9088234095223[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 32 )[/C][C]1611.19791666667[/C][C]22.8412984880672[/C][C]70.5388057298229[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 32 )[/C][C]1614.94791666667[/C][C]22.1717150783541[/C][C]72.8382044852864[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 32 )[/C][C]1616.51041666667[/C][C]21.8448375750973[/C][C]73.9996537447116[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 32 )[/C][C]1620.03125[/C][C]21.4047740879338[/C][C]75.6855103139461[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 32 )[/C][C]1621.71875[/C][C]20.8521040164626[/C][C]77.7724276034524[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 32 )[/C][C]1621.13541666667[/C][C]20.3548273283845[/C][C]79.6437813258194[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 32 )[/C][C]1621.13541666667[/C][C]19.9883168715583[/C][C]81.1041483424454[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 32 )[/C][C]1619.57291666667[/C][C]18.1491007026233[/C][C]89.2370891100169[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 32 )[/C][C]1623.125[/C][C]17.1884820293615[/C][C]94.4309682046013[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 32 )[/C][C]1627.45833333333[/C][C]16.6015146520638[/C][C]98.0307139102524[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 32 )[/C][C]1616[/C][C]35.3993073179506[/C][C]45.6506107728425[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 32 )[/C][C]1616.29347826087[/C][C]34.5526511209317[/C][C]46.7776979718274[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 32 )[/C][C]1617.41111111111[/C][C]33.7794709518796[/C][C]47.8814814303986[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 32 )[/C][C]1618.51136363636[/C][C]32.9725115648156[/C][C]49.086687268417[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 32 )[/C][C]1618.76744186047[/C][C]32.3187090294353[/C][C]50.0876269651155[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 32 )[/C][C]1618.38095238095[/C][C]31.7584332011578[/C][C]50.9590930424727[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 32 )[/C][C]1617.62195121951[/C][C]31.2087638935781[/C][C]51.8322980280669[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 32 )[/C][C]1617.3875[/C][C]30.7730385741389[/C][C]52.5585894322188[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 32 )[/C][C]1617.08974358974[/C][C]30.2843345815088[/C][C]53.3969052295809[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 32 )[/C][C]1616.86842105263[/C][C]29.8162286088966[/C][C]54.2277979640318[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 32 )[/C][C]1616.18918918919[/C][C]29.362715755158[/C][C]55.0422243863897[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 32 )[/C][C]1615.70833333333[/C][C]28.879155951554[/C][C]55.9472145253743[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 32 )[/C][C]1615.64285714286[/C][C]28.4726743122311[/C][C]56.7436286253173[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 32 )[/C][C]1615.67647058824[/C][C]28.0198916642206[/C][C]57.6617672170139[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 32 )[/C][C]1616.06060606061[/C][C]27.5791624220372[/C][C]58.5971604695757[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 32 )[/C][C]1616.75[/C][C]27.1412658785854[/C][C]59.5679658875316[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 32 )[/C][C]1617.43548387097[/C][C]26.6483517097395[/C][C]60.6955169868845[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 32 )[/C][C]1618.21666666667[/C][C]26.0802010718336[/C][C]62.0477066955718[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 32 )[/C][C]1618.6724137931[/C][C]25.5083629564998[/C][C]63.4565384126562[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 32 )[/C][C]1619.32142857143[/C][C]24.8681733064425[/C][C]65.1162193787639[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 32 )[/C][C]1619.53703703704[/C][C]24.3939068723489[/C][C]66.3910477936941[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 32 )[/C][C]1619.84615384615[/C][C]23.9208628754361[/C][C]67.7168780357645[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 32 )[/C][C]1620.58[/C][C]23.4362546635136[/C][C]69.1484208235277[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 32 )[/C][C]1621.39583333333[/C][C]23.0336198083277[/C][C]70.3925760182568[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 32 )[/C][C]1621.95652173913[/C][C]22.6270317692726[/C][C]71.6822488375051[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 32 )[/C][C]1622.43181818182[/C][C]22.1468145101361[/C][C]73.2580217095901[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 32 )[/C][C]1622.64285714286[/C][C]21.5937257370339[/C][C]75.1441820139439[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 32 )[/C][C]1622.725[/C][C]20.967251250462[/C][C]77.393311150609[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 32 )[/C][C]1622.86842105263[/C][C]20.2289586888179[/C][C]80.225010393131[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 32 )[/C][C]1623.02777777778[/C][C]19.304020722362[/C][C]84.0771879144142[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 32 )[/C][C]1623.35294117647[/C][C]18.524151136211[/C][C]87.6344038244832[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 32 )[/C][C]1623.375[/C][C]17.6921906182069[/C][C]91.7565854354632[/C][/ROW]
[ROW][C]Median[/C][C]1613[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]1503.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]1615.42857142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]1621.39583333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]1615.42857142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]1621.39583333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]1621.39583333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]1615.42857142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]1621.39583333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]1620.58[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]96[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=277512&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=277512&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 Mean1613.6562537.150278115547143.4359130497248
Geometric Mean1569.3948183587
Harmonic Mean1520.1378075298
Quadratic Mean1653.78356919822
Winsorized Mean ( 1 / 32 )1615.7187536.143848519119144.7024546693009
Winsorized Mean ( 2 / 32 )1614.1979166666735.825667131163245.0570232441685
Winsorized Mean ( 3 / 32 )1614.3854166666735.645102422474545.2905254004484
Winsorized Mean ( 4 / 32 )1617.5937534.849688444468746.4163044836845
Winsorized Mean ( 5 / 32 )1620.4583333333334.175209404852247.4161932451323
Winsorized Mean ( 6 / 32 )1622.2708333333333.77972530857148.0249859498327
Winsorized Mean ( 7 / 32 )1618.9895833333332.879313121079149.2403712136977
Winsorized Mean ( 8 / 32 )1619.3229166666732.775510670850249.4064892818545
Winsorized Mean ( 9 / 32 )1618.6666666666732.235984533288450.2130364591519
Winsorized Mean ( 10 / 32 )1622.1041666666731.697969797621751.1737558279955
Winsorized Mean ( 11 / 32 )1620.1562531.396147126890951.6036647252278
Winsorized Mean ( 12 / 32 )1616.2812530.415376215566253.140268216469
Winsorized Mean ( 13 / 32 )1615.3333333333330.200919537915953.4862301561829
Winsorized Mean ( 14 / 32 )1611.9791666666729.563743127553954.5255436604128
Winsorized Mean ( 15 / 32 )1609.1666666666728.963784353802455.5578872915968
Winsorized Mean ( 16 / 32 )1609.6666666666728.707293477971956.0716971769498
Winsorized Mean ( 17 / 32 )1609.1354166666728.490621032129556.4794784519443
Winsorized Mean ( 18 / 32 )1613.2604166666727.755314983309758.1243778943522
Winsorized Mean ( 19 / 32 )1611.4791666666727.360146692045258.8987765601123
Winsorized Mean ( 20 / 32 )1616.8958333333325.516147618536363.3675528730181
Winsorized Mean ( 21 / 32 )1616.0208333333324.777177968099365.222150618362
Winsorized Mean ( 22 / 32 )1611.437524.08408066208366.9088234095223
Winsorized Mean ( 23 / 32 )1611.1979166666722.841298488067270.5388057298229
Winsorized Mean ( 24 / 32 )1614.9479166666722.171715078354172.8382044852864
Winsorized Mean ( 25 / 32 )1616.5104166666721.844837575097373.9996537447116
Winsorized Mean ( 26 / 32 )1620.0312521.404774087933875.6855103139461
Winsorized Mean ( 27 / 32 )1621.7187520.852104016462677.7724276034524
Winsorized Mean ( 28 / 32 )1621.1354166666720.354827328384579.6437813258194
Winsorized Mean ( 29 / 32 )1621.1354166666719.988316871558381.1041483424454
Winsorized Mean ( 30 / 32 )1619.5729166666718.149100702623389.2370891100169
Winsorized Mean ( 31 / 32 )1623.12517.188482029361594.4309682046013
Winsorized Mean ( 32 / 32 )1627.4583333333316.601514652063898.0307139102524
Trimmed Mean ( 1 / 32 )161635.399307317950645.6506107728425
Trimmed Mean ( 2 / 32 )1616.2934782608734.552651120931746.7776979718274
Trimmed Mean ( 3 / 32 )1617.4111111111133.779470951879647.8814814303986
Trimmed Mean ( 4 / 32 )1618.5113636363632.972511564815649.086687268417
Trimmed Mean ( 5 / 32 )1618.7674418604732.318709029435350.0876269651155
Trimmed Mean ( 6 / 32 )1618.3809523809531.758433201157850.9590930424727
Trimmed Mean ( 7 / 32 )1617.6219512195131.208763893578151.8322980280669
Trimmed Mean ( 8 / 32 )1617.387530.773038574138952.5585894322188
Trimmed Mean ( 9 / 32 )1617.0897435897430.284334581508853.3969052295809
Trimmed Mean ( 10 / 32 )1616.8684210526329.816228608896654.2277979640318
Trimmed Mean ( 11 / 32 )1616.1891891891929.36271575515855.0422243863897
Trimmed Mean ( 12 / 32 )1615.7083333333328.87915595155455.9472145253743
Trimmed Mean ( 13 / 32 )1615.6428571428628.472674312231156.7436286253173
Trimmed Mean ( 14 / 32 )1615.6764705882428.019891664220657.6617672170139
Trimmed Mean ( 15 / 32 )1616.0606060606127.579162422037258.5971604695757
Trimmed Mean ( 16 / 32 )1616.7527.141265878585459.5679658875316
Trimmed Mean ( 17 / 32 )1617.4354838709726.648351709739560.6955169868845
Trimmed Mean ( 18 / 32 )1618.2166666666726.080201071833662.0477066955718
Trimmed Mean ( 19 / 32 )1618.672413793125.508362956499863.4565384126562
Trimmed Mean ( 20 / 32 )1619.3214285714324.868173306442565.1162193787639
Trimmed Mean ( 21 / 32 )1619.5370370370424.393906872348966.3910477936941
Trimmed Mean ( 22 / 32 )1619.8461538461523.920862875436167.7168780357645
Trimmed Mean ( 23 / 32 )1620.5823.436254663513669.1484208235277
Trimmed Mean ( 24 / 32 )1621.3958333333323.033619808327770.3925760182568
Trimmed Mean ( 25 / 32 )1621.9565217391322.627031769272671.6822488375051
Trimmed Mean ( 26 / 32 )1622.4318181818222.146814510136173.2580217095901
Trimmed Mean ( 27 / 32 )1622.6428571428621.593725737033975.1441820139439
Trimmed Mean ( 28 / 32 )1622.72520.96725125046277.393311150609
Trimmed Mean ( 29 / 32 )1622.8684210526320.228958688817980.225010393131
Trimmed Mean ( 30 / 32 )1623.0277777777819.30402072236284.0771879144142
Trimmed Mean ( 31 / 32 )1623.3529411764718.52415113621187.6344038244832
Trimmed Mean ( 32 / 32 )1623.37517.692190618206991.7565854354632
Median1613
Midrange1503.5
Midmean - Weighted Average at Xnp1615.42857142857
Midmean - Weighted Average at X(n+1)p1621.39583333333
Midmean - Empirical Distribution Function1615.42857142857
Midmean - Empirical Distribution Function - Averaging1621.39583333333
Midmean - Empirical Distribution Function - Interpolation1621.39583333333
Midmean - Closest Observation1615.42857142857
Midmean - True Basic - Statistics Graphics Toolkit1621.39583333333
Midmean - MS Excel (old versions)1620.58
Number of observations96



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')