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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, 25 Oct 2017 23:49:24 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Oct/25/t1508968195tg5ayvev3gza9yn.htm/, Retrieved Sat, 11 May 2024 09:36:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308051, Retrieved Sat, 11 May 2024 09:36:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact128
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2017-10-25 21:49:24] [882f73a830550adcc53d3c05ef985140] [Current]
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Dataseries X:
2570
2669
2450
2842
3440
2678
2981
2260
2844
2546
2456
2295
2379
2471
2057
2280
2351
2276
2548
2311
2201
2725
2408
2139
1898
2539
2070
2063
2565
2443
2196
2799
2076
2628
2292
2155
2476
2138
1854
2081
1795
1756
2237
1960
1829
2524
2077
2366
2185
2098
1836
1863
2044
2136
2931
3263
3328
3570
2313
1623
1316
1507
1419
1660
1790
1733
2086
1814
2241
1943
1773
2143
2087
1805
1913
2296
2500
2210
2526
2249
2024
2091
2045
1882
1831
1964
1763
1688
2149
1823
2094
2145
1791
1996
2097
1796
1963
2042
1746
2210
2968
3126
3708
3015
1569
1518
1393
1615
1777
1648
1463
1779




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308051&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=308051&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308051&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean2195.6644.223149.6496
Geometric Mean2149.34
Harmonic Mean2105.49
Quadratic Mean2244.55
Winsorized Mean ( 1 / 37 )2195.1243.740350.1852
Winsorized Mean ( 2 / 37 )2193.2643.032550.9675
Winsorized Mean ( 3 / 37 )2191.4442.088352.0676
Winsorized Mean ( 4 / 37 )2190.6941.294653.0503
Winsorized Mean ( 5 / 37 )2185.0639.853954.8268
Winsorized Mean ( 6 / 37 )2181.8538.233457.0666
Winsorized Mean ( 7 / 37 )2182.637.416358.3328
Winsorized Mean ( 8 / 37 )2182.2437.160858.7242
Winsorized Mean ( 9 / 37 )2181.2836.332260.0371
Winsorized Mean ( 10 / 37 )2174.5834.793762.4993
Winsorized Mean ( 11 / 37 )2177.1334.400263.2885
Winsorized Mean ( 12 / 37 )2177.3533.006565.9673
Winsorized Mean ( 13 / 37 )2170.2731.4169.0948
Winsorized Mean ( 14 / 37 )2165.6430.343371.3713
Winsorized Mean ( 15 / 37 )2165.3830.047172.066
Winsorized Mean ( 16 / 37 )2160.9529.007574.4961
Winsorized Mean ( 17 / 37 )2152.7527.69777.725
Winsorized Mean ( 18 / 37 )2152.2727.54978.1251
Winsorized Mean ( 19 / 37 )2151.2526.936379.8642
Winsorized Mean ( 20 / 37 )2151.0726.867480.0624
Winsorized Mean ( 21 / 37 )2150.5126.603880.8347
Winsorized Mean ( 22 / 37 )2148.1526.246581.8453
Winsorized Mean ( 23 / 37 )2149.5925.97182.7688
Winsorized Mean ( 24 / 37 )2146.3825.079985.5815
Winsorized Mean ( 25 / 37 )2143.0324.167388.6748
Winsorized Mean ( 26 / 37 )2143.2623.857789.8352
Winsorized Mean ( 27 / 37 )2140.1223.356291.6298
Winsorized Mean ( 28 / 37 )2139.8823.02592.937
Winsorized Mean ( 29 / 37 )2142.7222.255496.279
Winsorized Mean ( 30 / 37 )2135.7620.8507102.431
Winsorized Mean ( 31 / 37 )2132.9919.2993110.522
Winsorized Mean ( 32 / 37 )2133.8518.3415116.34
Winsorized Mean ( 33 / 37 )2133.8517.3302123.129
Winsorized Mean ( 34 / 37 )2131.4215.0107141.994
Winsorized Mean ( 35 / 37 )2136.1114.3481148.878
Winsorized Mean ( 36 / 37 )2132.2513.717155.445
Winsorized Mean ( 37 / 37 )2132.2513.6448156.268
Trimmed Mean ( 1 / 37 )2189.9142.097352.0202
Trimmed Mean ( 2 / 37 )2184.5140.232954.2965
Trimmed Mean ( 3 / 37 )2179.8938.550956.5457
Trimmed Mean ( 4 / 37 )2175.7437.053558.7189
Trimmed Mean ( 5 / 37 )2171.6435.626960.9549
Trimmed Mean ( 6 / 37 )2168.6334.432162.9827
Trimmed Mean ( 7 / 37 )2166.1133.488364.6827
Trimmed Mean ( 8 / 37 )2163.3632.599666.3616
Trimmed Mean ( 9 / 37 )2160.5531.640868.2838
Trimmed Mean ( 10 / 37 )2157.7530.708670.2653
Trimmed Mean ( 11 / 37 )2155.6629.93172.0209
Trimmed Mean ( 12 / 37 )2153.1729.105373.9786
Trimmed Mean ( 13 / 37 )2150.5528.388875.7533
Trimmed Mean ( 14 / 37 )2148.5227.823477.22
Trimmed Mean ( 15 / 37 )2146.8527.334378.5406
Trimmed Mean ( 16 / 37 )2145.1226.809480.014
Trimmed Mean ( 17 / 37 )2143.7126.351781.3497
Trimmed Mean ( 18 / 37 )2142.9226.004182.4072
Trimmed Mean ( 19 / 37 )2142.1425.612783.6357
Trimmed Mean ( 20 / 37 )2141.3925.233784.8624
Trimmed Mean ( 21 / 37 )2140.6124.79186.3466
Trimmed Mean ( 22 / 37 )2139.8424.388.0591
Trimmed Mean ( 23 / 37 )2139.223.765190.0143
Trimmed Mean ( 24 / 37 )2138.4123.162192.3235
Trimmed Mean ( 25 / 37 )2137.8122.57394.7062
Trimmed Mean ( 26 / 37 )2137.4222.001697.1484
Trimmed Mean ( 27 / 37 )2136.9821.3517100.085
Trimmed Mean ( 28 / 37 )2136.7520.6375103.537
Trimmed Mean ( 29 / 37 )2136.5219.8105107.848
Trimmed Mean ( 30 / 37 )2136.0618.9213112.892
Trimmed Mean ( 31 / 37 )2136.0818.0808118.141
Trimmed Mean ( 32 / 37 )2136.3117.3278123.288
Trimmed Mean ( 33 / 37 )2136.516.5623128.998
Trimmed Mean ( 34 / 37 )2136.715.7923135.301
Trimmed Mean ( 35 / 37 )2137.1215.3028139.656
Trimmed Mean ( 36 / 37 )2137.214.7987144.418
Trimmed Mean ( 37 / 37 )2137.6114.2641149.859
Median2137
Midrange2512
Midmean - Weighted Average at Xnp2131.39
Midmean - Weighted Average at X(n+1)p2136.75
Midmean - Empirical Distribution Function2131.39
Midmean - Empirical Distribution Function - Averaging2136.75
Midmean - Empirical Distribution Function - Interpolation2136.75
Midmean - Closest Observation2131.39
Midmean - True Basic - Statistics Graphics Toolkit2136.75
Midmean - MS Excel (old versions)2136.98
Number of observations112

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 2195.66 & 44.2231 & 49.6496 \tabularnewline
Geometric Mean & 2149.34 &  &  \tabularnewline
Harmonic Mean & 2105.49 &  &  \tabularnewline
Quadratic Mean & 2244.55 &  &  \tabularnewline
Winsorized Mean ( 1 / 37 ) & 2195.12 & 43.7403 & 50.1852 \tabularnewline
Winsorized Mean ( 2 / 37 ) & 2193.26 & 43.0325 & 50.9675 \tabularnewline
Winsorized Mean ( 3 / 37 ) & 2191.44 & 42.0883 & 52.0676 \tabularnewline
Winsorized Mean ( 4 / 37 ) & 2190.69 & 41.2946 & 53.0503 \tabularnewline
Winsorized Mean ( 5 / 37 ) & 2185.06 & 39.8539 & 54.8268 \tabularnewline
Winsorized Mean ( 6 / 37 ) & 2181.85 & 38.2334 & 57.0666 \tabularnewline
Winsorized Mean ( 7 / 37 ) & 2182.6 & 37.4163 & 58.3328 \tabularnewline
Winsorized Mean ( 8 / 37 ) & 2182.24 & 37.1608 & 58.7242 \tabularnewline
Winsorized Mean ( 9 / 37 ) & 2181.28 & 36.3322 & 60.0371 \tabularnewline
Winsorized Mean ( 10 / 37 ) & 2174.58 & 34.7937 & 62.4993 \tabularnewline
Winsorized Mean ( 11 / 37 ) & 2177.13 & 34.4002 & 63.2885 \tabularnewline
Winsorized Mean ( 12 / 37 ) & 2177.35 & 33.0065 & 65.9673 \tabularnewline
Winsorized Mean ( 13 / 37 ) & 2170.27 & 31.41 & 69.0948 \tabularnewline
Winsorized Mean ( 14 / 37 ) & 2165.64 & 30.3433 & 71.3713 \tabularnewline
Winsorized Mean ( 15 / 37 ) & 2165.38 & 30.0471 & 72.066 \tabularnewline
Winsorized Mean ( 16 / 37 ) & 2160.95 & 29.0075 & 74.4961 \tabularnewline
Winsorized Mean ( 17 / 37 ) & 2152.75 & 27.697 & 77.725 \tabularnewline
Winsorized Mean ( 18 / 37 ) & 2152.27 & 27.549 & 78.1251 \tabularnewline
Winsorized Mean ( 19 / 37 ) & 2151.25 & 26.9363 & 79.8642 \tabularnewline
Winsorized Mean ( 20 / 37 ) & 2151.07 & 26.8674 & 80.0624 \tabularnewline
Winsorized Mean ( 21 / 37 ) & 2150.51 & 26.6038 & 80.8347 \tabularnewline
Winsorized Mean ( 22 / 37 ) & 2148.15 & 26.2465 & 81.8453 \tabularnewline
Winsorized Mean ( 23 / 37 ) & 2149.59 & 25.971 & 82.7688 \tabularnewline
Winsorized Mean ( 24 / 37 ) & 2146.38 & 25.0799 & 85.5815 \tabularnewline
Winsorized Mean ( 25 / 37 ) & 2143.03 & 24.1673 & 88.6748 \tabularnewline
Winsorized Mean ( 26 / 37 ) & 2143.26 & 23.8577 & 89.8352 \tabularnewline
Winsorized Mean ( 27 / 37 ) & 2140.12 & 23.3562 & 91.6298 \tabularnewline
Winsorized Mean ( 28 / 37 ) & 2139.88 & 23.025 & 92.937 \tabularnewline
Winsorized Mean ( 29 / 37 ) & 2142.72 & 22.2554 & 96.279 \tabularnewline
Winsorized Mean ( 30 / 37 ) & 2135.76 & 20.8507 & 102.431 \tabularnewline
Winsorized Mean ( 31 / 37 ) & 2132.99 & 19.2993 & 110.522 \tabularnewline
Winsorized Mean ( 32 / 37 ) & 2133.85 & 18.3415 & 116.34 \tabularnewline
Winsorized Mean ( 33 / 37 ) & 2133.85 & 17.3302 & 123.129 \tabularnewline
Winsorized Mean ( 34 / 37 ) & 2131.42 & 15.0107 & 141.994 \tabularnewline
Winsorized Mean ( 35 / 37 ) & 2136.11 & 14.3481 & 148.878 \tabularnewline
Winsorized Mean ( 36 / 37 ) & 2132.25 & 13.717 & 155.445 \tabularnewline
Winsorized Mean ( 37 / 37 ) & 2132.25 & 13.6448 & 156.268 \tabularnewline
Trimmed Mean ( 1 / 37 ) & 2189.91 & 42.0973 & 52.0202 \tabularnewline
Trimmed Mean ( 2 / 37 ) & 2184.51 & 40.2329 & 54.2965 \tabularnewline
Trimmed Mean ( 3 / 37 ) & 2179.89 & 38.5509 & 56.5457 \tabularnewline
Trimmed Mean ( 4 / 37 ) & 2175.74 & 37.0535 & 58.7189 \tabularnewline
Trimmed Mean ( 5 / 37 ) & 2171.64 & 35.6269 & 60.9549 \tabularnewline
Trimmed Mean ( 6 / 37 ) & 2168.63 & 34.4321 & 62.9827 \tabularnewline
Trimmed Mean ( 7 / 37 ) & 2166.11 & 33.4883 & 64.6827 \tabularnewline
Trimmed Mean ( 8 / 37 ) & 2163.36 & 32.5996 & 66.3616 \tabularnewline
Trimmed Mean ( 9 / 37 ) & 2160.55 & 31.6408 & 68.2838 \tabularnewline
Trimmed Mean ( 10 / 37 ) & 2157.75 & 30.7086 & 70.2653 \tabularnewline
Trimmed Mean ( 11 / 37 ) & 2155.66 & 29.931 & 72.0209 \tabularnewline
Trimmed Mean ( 12 / 37 ) & 2153.17 & 29.1053 & 73.9786 \tabularnewline
Trimmed Mean ( 13 / 37 ) & 2150.55 & 28.3888 & 75.7533 \tabularnewline
Trimmed Mean ( 14 / 37 ) & 2148.52 & 27.8234 & 77.22 \tabularnewline
Trimmed Mean ( 15 / 37 ) & 2146.85 & 27.3343 & 78.5406 \tabularnewline
Trimmed Mean ( 16 / 37 ) & 2145.12 & 26.8094 & 80.014 \tabularnewline
Trimmed Mean ( 17 / 37 ) & 2143.71 & 26.3517 & 81.3497 \tabularnewline
Trimmed Mean ( 18 / 37 ) & 2142.92 & 26.0041 & 82.4072 \tabularnewline
Trimmed Mean ( 19 / 37 ) & 2142.14 & 25.6127 & 83.6357 \tabularnewline
Trimmed Mean ( 20 / 37 ) & 2141.39 & 25.2337 & 84.8624 \tabularnewline
Trimmed Mean ( 21 / 37 ) & 2140.61 & 24.791 & 86.3466 \tabularnewline
Trimmed Mean ( 22 / 37 ) & 2139.84 & 24.3 & 88.0591 \tabularnewline
Trimmed Mean ( 23 / 37 ) & 2139.2 & 23.7651 & 90.0143 \tabularnewline
Trimmed Mean ( 24 / 37 ) & 2138.41 & 23.1621 & 92.3235 \tabularnewline
Trimmed Mean ( 25 / 37 ) & 2137.81 & 22.573 & 94.7062 \tabularnewline
Trimmed Mean ( 26 / 37 ) & 2137.42 & 22.0016 & 97.1484 \tabularnewline
Trimmed Mean ( 27 / 37 ) & 2136.98 & 21.3517 & 100.085 \tabularnewline
Trimmed Mean ( 28 / 37 ) & 2136.75 & 20.6375 & 103.537 \tabularnewline
Trimmed Mean ( 29 / 37 ) & 2136.52 & 19.8105 & 107.848 \tabularnewline
Trimmed Mean ( 30 / 37 ) & 2136.06 & 18.9213 & 112.892 \tabularnewline
Trimmed Mean ( 31 / 37 ) & 2136.08 & 18.0808 & 118.141 \tabularnewline
Trimmed Mean ( 32 / 37 ) & 2136.31 & 17.3278 & 123.288 \tabularnewline
Trimmed Mean ( 33 / 37 ) & 2136.5 & 16.5623 & 128.998 \tabularnewline
Trimmed Mean ( 34 / 37 ) & 2136.7 & 15.7923 & 135.301 \tabularnewline
Trimmed Mean ( 35 / 37 ) & 2137.12 & 15.3028 & 139.656 \tabularnewline
Trimmed Mean ( 36 / 37 ) & 2137.2 & 14.7987 & 144.418 \tabularnewline
Trimmed Mean ( 37 / 37 ) & 2137.61 & 14.2641 & 149.859 \tabularnewline
Median & 2137 &  &  \tabularnewline
Midrange & 2512 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 2131.39 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 2136.75 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 2131.39 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 2136.75 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 2136.75 &  &  \tabularnewline
Midmean - Closest Observation & 2131.39 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 2136.75 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 2136.98 &  &  \tabularnewline
Number of observations & 112 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308051&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]2195.66[/C][C]44.2231[/C][C]49.6496[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]2149.34[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]2105.49[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]2244.55[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 37 )[/C][C]2195.12[/C][C]43.7403[/C][C]50.1852[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 37 )[/C][C]2193.26[/C][C]43.0325[/C][C]50.9675[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 37 )[/C][C]2191.44[/C][C]42.0883[/C][C]52.0676[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 37 )[/C][C]2190.69[/C][C]41.2946[/C][C]53.0503[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 37 )[/C][C]2185.06[/C][C]39.8539[/C][C]54.8268[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 37 )[/C][C]2181.85[/C][C]38.2334[/C][C]57.0666[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 37 )[/C][C]2182.6[/C][C]37.4163[/C][C]58.3328[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 37 )[/C][C]2182.24[/C][C]37.1608[/C][C]58.7242[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 37 )[/C][C]2181.28[/C][C]36.3322[/C][C]60.0371[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 37 )[/C][C]2174.58[/C][C]34.7937[/C][C]62.4993[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 37 )[/C][C]2177.13[/C][C]34.4002[/C][C]63.2885[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 37 )[/C][C]2177.35[/C][C]33.0065[/C][C]65.9673[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 37 )[/C][C]2170.27[/C][C]31.41[/C][C]69.0948[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 37 )[/C][C]2165.64[/C][C]30.3433[/C][C]71.3713[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 37 )[/C][C]2165.38[/C][C]30.0471[/C][C]72.066[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 37 )[/C][C]2160.95[/C][C]29.0075[/C][C]74.4961[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 37 )[/C][C]2152.75[/C][C]27.697[/C][C]77.725[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 37 )[/C][C]2152.27[/C][C]27.549[/C][C]78.1251[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 37 )[/C][C]2151.25[/C][C]26.9363[/C][C]79.8642[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 37 )[/C][C]2151.07[/C][C]26.8674[/C][C]80.0624[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 37 )[/C][C]2150.51[/C][C]26.6038[/C][C]80.8347[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 37 )[/C][C]2148.15[/C][C]26.2465[/C][C]81.8453[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 37 )[/C][C]2149.59[/C][C]25.971[/C][C]82.7688[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 37 )[/C][C]2146.38[/C][C]25.0799[/C][C]85.5815[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 37 )[/C][C]2143.03[/C][C]24.1673[/C][C]88.6748[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 37 )[/C][C]2143.26[/C][C]23.8577[/C][C]89.8352[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 37 )[/C][C]2140.12[/C][C]23.3562[/C][C]91.6298[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 37 )[/C][C]2139.88[/C][C]23.025[/C][C]92.937[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 37 )[/C][C]2142.72[/C][C]22.2554[/C][C]96.279[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 37 )[/C][C]2135.76[/C][C]20.8507[/C][C]102.431[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 37 )[/C][C]2132.99[/C][C]19.2993[/C][C]110.522[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 37 )[/C][C]2133.85[/C][C]18.3415[/C][C]116.34[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 37 )[/C][C]2133.85[/C][C]17.3302[/C][C]123.129[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 37 )[/C][C]2131.42[/C][C]15.0107[/C][C]141.994[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 37 )[/C][C]2136.11[/C][C]14.3481[/C][C]148.878[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 37 )[/C][C]2132.25[/C][C]13.717[/C][C]155.445[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 37 )[/C][C]2132.25[/C][C]13.6448[/C][C]156.268[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 37 )[/C][C]2189.91[/C][C]42.0973[/C][C]52.0202[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 37 )[/C][C]2184.51[/C][C]40.2329[/C][C]54.2965[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 37 )[/C][C]2179.89[/C][C]38.5509[/C][C]56.5457[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 37 )[/C][C]2175.74[/C][C]37.0535[/C][C]58.7189[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 37 )[/C][C]2171.64[/C][C]35.6269[/C][C]60.9549[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 37 )[/C][C]2168.63[/C][C]34.4321[/C][C]62.9827[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 37 )[/C][C]2166.11[/C][C]33.4883[/C][C]64.6827[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 37 )[/C][C]2163.36[/C][C]32.5996[/C][C]66.3616[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 37 )[/C][C]2160.55[/C][C]31.6408[/C][C]68.2838[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 37 )[/C][C]2157.75[/C][C]30.7086[/C][C]70.2653[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 37 )[/C][C]2155.66[/C][C]29.931[/C][C]72.0209[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 37 )[/C][C]2153.17[/C][C]29.1053[/C][C]73.9786[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 37 )[/C][C]2150.55[/C][C]28.3888[/C][C]75.7533[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 37 )[/C][C]2148.52[/C][C]27.8234[/C][C]77.22[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 37 )[/C][C]2146.85[/C][C]27.3343[/C][C]78.5406[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 37 )[/C][C]2145.12[/C][C]26.8094[/C][C]80.014[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 37 )[/C][C]2143.71[/C][C]26.3517[/C][C]81.3497[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 37 )[/C][C]2142.92[/C][C]26.0041[/C][C]82.4072[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 37 )[/C][C]2142.14[/C][C]25.6127[/C][C]83.6357[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 37 )[/C][C]2141.39[/C][C]25.2337[/C][C]84.8624[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 37 )[/C][C]2140.61[/C][C]24.791[/C][C]86.3466[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 37 )[/C][C]2139.84[/C][C]24.3[/C][C]88.0591[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 37 )[/C][C]2139.2[/C][C]23.7651[/C][C]90.0143[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 37 )[/C][C]2138.41[/C][C]23.1621[/C][C]92.3235[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 37 )[/C][C]2137.81[/C][C]22.573[/C][C]94.7062[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 37 )[/C][C]2137.42[/C][C]22.0016[/C][C]97.1484[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 37 )[/C][C]2136.98[/C][C]21.3517[/C][C]100.085[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 37 )[/C][C]2136.75[/C][C]20.6375[/C][C]103.537[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 37 )[/C][C]2136.52[/C][C]19.8105[/C][C]107.848[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 37 )[/C][C]2136.06[/C][C]18.9213[/C][C]112.892[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 37 )[/C][C]2136.08[/C][C]18.0808[/C][C]118.141[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 37 )[/C][C]2136.31[/C][C]17.3278[/C][C]123.288[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 37 )[/C][C]2136.5[/C][C]16.5623[/C][C]128.998[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 37 )[/C][C]2136.7[/C][C]15.7923[/C][C]135.301[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 37 )[/C][C]2137.12[/C][C]15.3028[/C][C]139.656[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 37 )[/C][C]2137.2[/C][C]14.7987[/C][C]144.418[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 37 )[/C][C]2137.61[/C][C]14.2641[/C][C]149.859[/C][/ROW]
[ROW][C]Median[/C][C]2137[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]2512[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]2131.39[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]2136.75[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]2131.39[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]2136.75[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]2136.75[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]2131.39[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]2136.75[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]2136.98[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]112[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308051&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308051&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 Mean2195.6644.223149.6496
Geometric Mean2149.34
Harmonic Mean2105.49
Quadratic Mean2244.55
Winsorized Mean ( 1 / 37 )2195.1243.740350.1852
Winsorized Mean ( 2 / 37 )2193.2643.032550.9675
Winsorized Mean ( 3 / 37 )2191.4442.088352.0676
Winsorized Mean ( 4 / 37 )2190.6941.294653.0503
Winsorized Mean ( 5 / 37 )2185.0639.853954.8268
Winsorized Mean ( 6 / 37 )2181.8538.233457.0666
Winsorized Mean ( 7 / 37 )2182.637.416358.3328
Winsorized Mean ( 8 / 37 )2182.2437.160858.7242
Winsorized Mean ( 9 / 37 )2181.2836.332260.0371
Winsorized Mean ( 10 / 37 )2174.5834.793762.4993
Winsorized Mean ( 11 / 37 )2177.1334.400263.2885
Winsorized Mean ( 12 / 37 )2177.3533.006565.9673
Winsorized Mean ( 13 / 37 )2170.2731.4169.0948
Winsorized Mean ( 14 / 37 )2165.6430.343371.3713
Winsorized Mean ( 15 / 37 )2165.3830.047172.066
Winsorized Mean ( 16 / 37 )2160.9529.007574.4961
Winsorized Mean ( 17 / 37 )2152.7527.69777.725
Winsorized Mean ( 18 / 37 )2152.2727.54978.1251
Winsorized Mean ( 19 / 37 )2151.2526.936379.8642
Winsorized Mean ( 20 / 37 )2151.0726.867480.0624
Winsorized Mean ( 21 / 37 )2150.5126.603880.8347
Winsorized Mean ( 22 / 37 )2148.1526.246581.8453
Winsorized Mean ( 23 / 37 )2149.5925.97182.7688
Winsorized Mean ( 24 / 37 )2146.3825.079985.5815
Winsorized Mean ( 25 / 37 )2143.0324.167388.6748
Winsorized Mean ( 26 / 37 )2143.2623.857789.8352
Winsorized Mean ( 27 / 37 )2140.1223.356291.6298
Winsorized Mean ( 28 / 37 )2139.8823.02592.937
Winsorized Mean ( 29 / 37 )2142.7222.255496.279
Winsorized Mean ( 30 / 37 )2135.7620.8507102.431
Winsorized Mean ( 31 / 37 )2132.9919.2993110.522
Winsorized Mean ( 32 / 37 )2133.8518.3415116.34
Winsorized Mean ( 33 / 37 )2133.8517.3302123.129
Winsorized Mean ( 34 / 37 )2131.4215.0107141.994
Winsorized Mean ( 35 / 37 )2136.1114.3481148.878
Winsorized Mean ( 36 / 37 )2132.2513.717155.445
Winsorized Mean ( 37 / 37 )2132.2513.6448156.268
Trimmed Mean ( 1 / 37 )2189.9142.097352.0202
Trimmed Mean ( 2 / 37 )2184.5140.232954.2965
Trimmed Mean ( 3 / 37 )2179.8938.550956.5457
Trimmed Mean ( 4 / 37 )2175.7437.053558.7189
Trimmed Mean ( 5 / 37 )2171.6435.626960.9549
Trimmed Mean ( 6 / 37 )2168.6334.432162.9827
Trimmed Mean ( 7 / 37 )2166.1133.488364.6827
Trimmed Mean ( 8 / 37 )2163.3632.599666.3616
Trimmed Mean ( 9 / 37 )2160.5531.640868.2838
Trimmed Mean ( 10 / 37 )2157.7530.708670.2653
Trimmed Mean ( 11 / 37 )2155.6629.93172.0209
Trimmed Mean ( 12 / 37 )2153.1729.105373.9786
Trimmed Mean ( 13 / 37 )2150.5528.388875.7533
Trimmed Mean ( 14 / 37 )2148.5227.823477.22
Trimmed Mean ( 15 / 37 )2146.8527.334378.5406
Trimmed Mean ( 16 / 37 )2145.1226.809480.014
Trimmed Mean ( 17 / 37 )2143.7126.351781.3497
Trimmed Mean ( 18 / 37 )2142.9226.004182.4072
Trimmed Mean ( 19 / 37 )2142.1425.612783.6357
Trimmed Mean ( 20 / 37 )2141.3925.233784.8624
Trimmed Mean ( 21 / 37 )2140.6124.79186.3466
Trimmed Mean ( 22 / 37 )2139.8424.388.0591
Trimmed Mean ( 23 / 37 )2139.223.765190.0143
Trimmed Mean ( 24 / 37 )2138.4123.162192.3235
Trimmed Mean ( 25 / 37 )2137.8122.57394.7062
Trimmed Mean ( 26 / 37 )2137.4222.001697.1484
Trimmed Mean ( 27 / 37 )2136.9821.3517100.085
Trimmed Mean ( 28 / 37 )2136.7520.6375103.537
Trimmed Mean ( 29 / 37 )2136.5219.8105107.848
Trimmed Mean ( 30 / 37 )2136.0618.9213112.892
Trimmed Mean ( 31 / 37 )2136.0818.0808118.141
Trimmed Mean ( 32 / 37 )2136.3117.3278123.288
Trimmed Mean ( 33 / 37 )2136.516.5623128.998
Trimmed Mean ( 34 / 37 )2136.715.7923135.301
Trimmed Mean ( 35 / 37 )2137.1215.3028139.656
Trimmed Mean ( 36 / 37 )2137.214.7987144.418
Trimmed Mean ( 37 / 37 )2137.6114.2641149.859
Median2137
Midrange2512
Midmean - Weighted Average at Xnp2131.39
Midmean - Weighted Average at X(n+1)p2136.75
Midmean - Empirical Distribution Function2131.39
Midmean - Empirical Distribution Function - Averaging2136.75
Midmean - Empirical Distribution Function - Interpolation2136.75
Midmean - Closest Observation2131.39
Midmean - True Basic - Statistics Graphics Toolkit2136.75
Midmean - MS Excel (old versions)2136.98
Number of observations112



Parameters (Session):
par1 = 0 ; par2 = no ; par3 = 512 ;
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,'Arithmetic Mean',header=TRUE)
a<-table.element(a,signif(arm,6))
a<-table.element(a, signif(armse,6))
a<-table.element(a,signif(armose,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Geometric Mean',header=TRUE)
a<-table.element(a,signif(geo,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Harmonic Mean',header=TRUE)
a<-table.element(a,signif(har,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Quadratic Mean',header=TRUE)
a<-table.element(a,signif(qua,6))
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, mylabel,header=TRUE)
a<-table.element(a,signif(win[j,1],6))
a<-table.element(a,signif(win[j,2],6))
a<-table.element(a,signif(win[j,1]/win[j,2],6))
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, mylabel,header=TRUE)
a<-table.element(a,signif(tri[j,1],6))
a<-table.element(a,signif(tri[j,2],6))
a<-table.element(a,signif(tri[j,1]/tri[j,2],6))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'Median',header=TRUE)
a<-table.element(a,signif(median(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Midrange',header=TRUE)
a<-table.element(a,signif(midr,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Weighted Average at Xnp',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[1],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Weighted Average at X(n+1)p',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[2],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[3],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Averaging',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[4],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Interpolation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[5],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Closest Observation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[6],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'True Basic - Statistics Graphics Toolkit',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[7],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'MS Excel (old versions)',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[8],6))
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,signif(length(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')