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Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSun, 18 Dec 2016 18:38:09 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/18/t1482082718w53jo8dp3aitu2w.htm/, Retrieved Fri, 01 Nov 2024 03:41:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301201, Retrieved Fri, 01 Nov 2024 03:41:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact66
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [central tendency ...] [2016-12-18 17:38:09] [afe7f6443461a2cd6ee0b843643e84a9] [Current]
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Dataseries X:
2119.9
2108.7
2092
2104.2
2110.1
2114
2138.8
2165.5
2155.1
2135.2
2163.1
2175.2
2183.3
2201.5
2212.3
2223.8
2241.9
2269.2
2261.4
2273.4
2299.3
2315.5
2338.7
2333
2311
2303.6
2310.5
2295.8
2265.5
2271.1
2231.9
2245
2249.7
2300.5
2280.4
2290.7
2261.5
2259.1
2249.8
2271.2
2259
2259.4
2250.2
2243.3
2234.3
2216.5
2197.6
2211.7
2206.7
2214.6
2229.8
2219.5
2213.8
2214.1
2224.1
2229.6
2251.7
2262.9
2268.9
2293.7
2312.4
2342
2327.4
2366.2
2371.8
2364.4
2370.5
2412.8
2447.3
2443.5
2459.3
2480.7
2504.4
2505.5
2534
2538.7
2538.1
2522
2566.4
2572.8
2557.3
2541
2540.7
2508.5
2567.1
2553.6
2522.4
2520.6
2499.4
2470.8
2479.3
2481.8
2470.3
2491
2479.1
2456.6
2456.1
2482.2
2444.7
2425.3
2389.3
2367.7
2339.3
2342.4
2343.6
2346.3
2363.5
2338.7
2369.4
2356
2348.6
2349.7
2371.9
2364.9
2394.1
2399.2




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=301201&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=301201&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301201&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 Mean2332.311.7649198.243
Geometric Mean2328.9
Harmonic Mean2325.52
Quadratic Mean2335.71
Winsorized Mean ( 1 / 38 )2332.3511.738198.701
Winsorized Mean ( 2 / 38 )2332.4211.7229198.963
Winsorized Mean ( 3 / 38 )2332.2211.6767199.732
Winsorized Mean ( 4 / 38 )2332.2311.6334200.477
Winsorized Mean ( 5 / 38 )2331.9411.5044202.699
Winsorized Mean ( 6 / 38 )2332.7111.3788205.005
Winsorized Mean ( 7 / 38 )2332.8111.3271205.949
Winsorized Mean ( 8 / 38 )2333.8911.1585209.159
Winsorized Mean ( 9 / 38 )2334.1911.023211.758
Winsorized Mean ( 10 / 38 )2333.410.8404215.25
Winsorized Mean ( 11 / 38 )2334.2810.7133217.886
Winsorized Mean ( 12 / 38 )2334.9810.5849220.594
Winsorized Mean ( 13 / 38 )2335.2210.1871229.233
Winsorized Mean ( 14 / 38 )2335.3310.0789231.704
Winsorized Mean ( 15 / 38 )2335.869.98139234.022
Winsorized Mean ( 16 / 38 )2335.869.80395238.257
Winsorized Mean ( 17 / 38 )2334.729.61797242.745
Winsorized Mean ( 18 / 38 )2333.599.40185248.205
Winsorized Mean ( 19 / 38 )2333.579.38741248.585
Winsorized Mean ( 20 / 38 )2333.479.35187249.519
Winsorized Mean ( 21 / 38 )2333.569.27934251.479
Winsorized Mean ( 22 / 38 )2334.099.21218253.37
Winsorized Mean ( 23 / 38 )2333.298.89719262.251
Winsorized Mean ( 24 / 38 )2333.258.87665262.853
Winsorized Mean ( 25 / 38 )2332.078.43598276.443
Winsorized Mean ( 26 / 38 )2331.518.35214279.151
Winsorized Mean ( 27 / 38 )2331.888.28545281.443
Winsorized Mean ( 28 / 38 )2330.347.95025293.115
Winsorized Mean ( 29 / 38 )2331.597.67057303.965
Winsorized Mean ( 30 / 38 )2331.647.59407307.034
Winsorized Mean ( 31 / 38 )2327.236.93665335.497
Winsorized Mean ( 32 / 38 )2325.086.38507364.142
Winsorized Mean ( 33 / 38 )2321.245.92947391.475
Winsorized Mean ( 34 / 38 )2319.865.74772403.614
Winsorized Mean ( 35 / 38 )2318.865.53857418.675
Winsorized Mean ( 36 / 38 )2315.734.72122490.493
Winsorized Mean ( 37 / 38 )2315.734.71459491.183
Winsorized Mean ( 38 / 38 )2315.44.66041496.823
Trimmed Mean ( 1 / 38 )2332.2911.5914201.209
Trimmed Mean ( 2 / 38 )2332.2311.4282204.077
Trimmed Mean ( 3 / 38 )2332.1411.2551207.207
Trimmed Mean ( 4 / 38 )2332.1111.0807210.466
Trimmed Mean ( 5 / 38 )2332.0810.8995213.962
Trimmed Mean ( 6 / 38 )2332.1110.7312217.321
Trimmed Mean ( 7 / 38 )2331.9910.5714220.596
Trimmed Mean ( 8 / 38 )2331.8610.4022224.17
Trimmed Mean ( 9 / 38 )2331.5610.2434227.615
Trimmed Mean ( 10 / 38 )2331.210.0877231.093
Trimmed Mean ( 11 / 38 )2330.939.94178234.458
Trimmed Mean ( 12 / 38 )2330.559.79531237.925
Trimmed Mean ( 13 / 38 )2330.079.64705241.532
Trimmed Mean ( 14 / 38 )2329.559.53494244.317
Trimmed Mean ( 15 / 38 )2328.999.42001247.239
Trimmed Mean ( 16 / 38 )2328.369.29922250.382
Trimmed Mean ( 17 / 38 )2327.79.18221253.501
Trimmed Mean ( 18 / 38 )2327.19.0707256.551
Trimmed Mean ( 19 / 38 )2326.568.96843259.417
Trimmed Mean ( 20 / 38 )23268.84872262.863
Trimmed Mean ( 21 / 38 )2325.428.71131266.942
Trimmed Mean ( 22 / 38 )2324.798.55767271.662
Trimmed Mean ( 23 / 38 )2324.098.38315277.234
Trimmed Mean ( 24 / 38 )2323.418.21978282.661
Trimmed Mean ( 25 / 38 )2322.698.02606289.393
Trimmed Mean ( 26 / 38 )2322.017.8584295.481
Trimmed Mean ( 27 / 38 )2321.327.66753302.747
Trimmed Mean ( 28 / 38 )2320.577.4438311.745
Trimmed Mean ( 29 / 38 )2319.877.22595321.047
Trimmed Mean ( 30 / 38 )2319.036.99999331.291
Trimmed Mean ( 31 / 38 )2319.036.73052344.555
Trimmed Mean ( 32 / 38 )2317.486.5216355.354
Trimmed Mean ( 33 / 38 )2316.936.35987364.304
Trimmed Mean ( 34 / 38 )2316.616.23909371.306
Trimmed Mean ( 35 / 38 )2316.376.11484378.811
Trimmed Mean ( 36 / 38 )2316.185.99054386.64
Trimmed Mean ( 37 / 38 )2316.225.97727387.504
Trimmed Mean ( 38 / 38 )2316.265.94695389.486
Median2313.95
Midrange2332.4
Midmean - Weighted Average at Xnp2318.42
Midmean - Weighted Average at X(n+1)p2319.87
Midmean - Empirical Distribution Function2318.42
Midmean - Empirical Distribution Function - Averaging2319.87
Midmean - Empirical Distribution Function - Interpolation2319.87
Midmean - Closest Observation2318.42
Midmean - True Basic - Statistics Graphics Toolkit2319.87
Midmean - MS Excel (old versions)2320.57
Number of observations116

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 2332.3 & 11.7649 & 198.243 \tabularnewline
Geometric Mean & 2328.9 &  &  \tabularnewline
Harmonic Mean & 2325.52 &  &  \tabularnewline
Quadratic Mean & 2335.71 &  &  \tabularnewline
Winsorized Mean ( 1 / 38 ) & 2332.35 & 11.738 & 198.701 \tabularnewline
Winsorized Mean ( 2 / 38 ) & 2332.42 & 11.7229 & 198.963 \tabularnewline
Winsorized Mean ( 3 / 38 ) & 2332.22 & 11.6767 & 199.732 \tabularnewline
Winsorized Mean ( 4 / 38 ) & 2332.23 & 11.6334 & 200.477 \tabularnewline
Winsorized Mean ( 5 / 38 ) & 2331.94 & 11.5044 & 202.699 \tabularnewline
Winsorized Mean ( 6 / 38 ) & 2332.71 & 11.3788 & 205.005 \tabularnewline
Winsorized Mean ( 7 / 38 ) & 2332.81 & 11.3271 & 205.949 \tabularnewline
Winsorized Mean ( 8 / 38 ) & 2333.89 & 11.1585 & 209.159 \tabularnewline
Winsorized Mean ( 9 / 38 ) & 2334.19 & 11.023 & 211.758 \tabularnewline
Winsorized Mean ( 10 / 38 ) & 2333.4 & 10.8404 & 215.25 \tabularnewline
Winsorized Mean ( 11 / 38 ) & 2334.28 & 10.7133 & 217.886 \tabularnewline
Winsorized Mean ( 12 / 38 ) & 2334.98 & 10.5849 & 220.594 \tabularnewline
Winsorized Mean ( 13 / 38 ) & 2335.22 & 10.1871 & 229.233 \tabularnewline
Winsorized Mean ( 14 / 38 ) & 2335.33 & 10.0789 & 231.704 \tabularnewline
Winsorized Mean ( 15 / 38 ) & 2335.86 & 9.98139 & 234.022 \tabularnewline
Winsorized Mean ( 16 / 38 ) & 2335.86 & 9.80395 & 238.257 \tabularnewline
Winsorized Mean ( 17 / 38 ) & 2334.72 & 9.61797 & 242.745 \tabularnewline
Winsorized Mean ( 18 / 38 ) & 2333.59 & 9.40185 & 248.205 \tabularnewline
Winsorized Mean ( 19 / 38 ) & 2333.57 & 9.38741 & 248.585 \tabularnewline
Winsorized Mean ( 20 / 38 ) & 2333.47 & 9.35187 & 249.519 \tabularnewline
Winsorized Mean ( 21 / 38 ) & 2333.56 & 9.27934 & 251.479 \tabularnewline
Winsorized Mean ( 22 / 38 ) & 2334.09 & 9.21218 & 253.37 \tabularnewline
Winsorized Mean ( 23 / 38 ) & 2333.29 & 8.89719 & 262.251 \tabularnewline
Winsorized Mean ( 24 / 38 ) & 2333.25 & 8.87665 & 262.853 \tabularnewline
Winsorized Mean ( 25 / 38 ) & 2332.07 & 8.43598 & 276.443 \tabularnewline
Winsorized Mean ( 26 / 38 ) & 2331.51 & 8.35214 & 279.151 \tabularnewline
Winsorized Mean ( 27 / 38 ) & 2331.88 & 8.28545 & 281.443 \tabularnewline
Winsorized Mean ( 28 / 38 ) & 2330.34 & 7.95025 & 293.115 \tabularnewline
Winsorized Mean ( 29 / 38 ) & 2331.59 & 7.67057 & 303.965 \tabularnewline
Winsorized Mean ( 30 / 38 ) & 2331.64 & 7.59407 & 307.034 \tabularnewline
Winsorized Mean ( 31 / 38 ) & 2327.23 & 6.93665 & 335.497 \tabularnewline
Winsorized Mean ( 32 / 38 ) & 2325.08 & 6.38507 & 364.142 \tabularnewline
Winsorized Mean ( 33 / 38 ) & 2321.24 & 5.92947 & 391.475 \tabularnewline
Winsorized Mean ( 34 / 38 ) & 2319.86 & 5.74772 & 403.614 \tabularnewline
Winsorized Mean ( 35 / 38 ) & 2318.86 & 5.53857 & 418.675 \tabularnewline
Winsorized Mean ( 36 / 38 ) & 2315.73 & 4.72122 & 490.493 \tabularnewline
Winsorized Mean ( 37 / 38 ) & 2315.73 & 4.71459 & 491.183 \tabularnewline
Winsorized Mean ( 38 / 38 ) & 2315.4 & 4.66041 & 496.823 \tabularnewline
Trimmed Mean ( 1 / 38 ) & 2332.29 & 11.5914 & 201.209 \tabularnewline
Trimmed Mean ( 2 / 38 ) & 2332.23 & 11.4282 & 204.077 \tabularnewline
Trimmed Mean ( 3 / 38 ) & 2332.14 & 11.2551 & 207.207 \tabularnewline
Trimmed Mean ( 4 / 38 ) & 2332.11 & 11.0807 & 210.466 \tabularnewline
Trimmed Mean ( 5 / 38 ) & 2332.08 & 10.8995 & 213.962 \tabularnewline
Trimmed Mean ( 6 / 38 ) & 2332.11 & 10.7312 & 217.321 \tabularnewline
Trimmed Mean ( 7 / 38 ) & 2331.99 & 10.5714 & 220.596 \tabularnewline
Trimmed Mean ( 8 / 38 ) & 2331.86 & 10.4022 & 224.17 \tabularnewline
Trimmed Mean ( 9 / 38 ) & 2331.56 & 10.2434 & 227.615 \tabularnewline
Trimmed Mean ( 10 / 38 ) & 2331.2 & 10.0877 & 231.093 \tabularnewline
Trimmed Mean ( 11 / 38 ) & 2330.93 & 9.94178 & 234.458 \tabularnewline
Trimmed Mean ( 12 / 38 ) & 2330.55 & 9.79531 & 237.925 \tabularnewline
Trimmed Mean ( 13 / 38 ) & 2330.07 & 9.64705 & 241.532 \tabularnewline
Trimmed Mean ( 14 / 38 ) & 2329.55 & 9.53494 & 244.317 \tabularnewline
Trimmed Mean ( 15 / 38 ) & 2328.99 & 9.42001 & 247.239 \tabularnewline
Trimmed Mean ( 16 / 38 ) & 2328.36 & 9.29922 & 250.382 \tabularnewline
Trimmed Mean ( 17 / 38 ) & 2327.7 & 9.18221 & 253.501 \tabularnewline
Trimmed Mean ( 18 / 38 ) & 2327.1 & 9.0707 & 256.551 \tabularnewline
Trimmed Mean ( 19 / 38 ) & 2326.56 & 8.96843 & 259.417 \tabularnewline
Trimmed Mean ( 20 / 38 ) & 2326 & 8.84872 & 262.863 \tabularnewline
Trimmed Mean ( 21 / 38 ) & 2325.42 & 8.71131 & 266.942 \tabularnewline
Trimmed Mean ( 22 / 38 ) & 2324.79 & 8.55767 & 271.662 \tabularnewline
Trimmed Mean ( 23 / 38 ) & 2324.09 & 8.38315 & 277.234 \tabularnewline
Trimmed Mean ( 24 / 38 ) & 2323.41 & 8.21978 & 282.661 \tabularnewline
Trimmed Mean ( 25 / 38 ) & 2322.69 & 8.02606 & 289.393 \tabularnewline
Trimmed Mean ( 26 / 38 ) & 2322.01 & 7.8584 & 295.481 \tabularnewline
Trimmed Mean ( 27 / 38 ) & 2321.32 & 7.66753 & 302.747 \tabularnewline
Trimmed Mean ( 28 / 38 ) & 2320.57 & 7.4438 & 311.745 \tabularnewline
Trimmed Mean ( 29 / 38 ) & 2319.87 & 7.22595 & 321.047 \tabularnewline
Trimmed Mean ( 30 / 38 ) & 2319.03 & 6.99999 & 331.291 \tabularnewline
Trimmed Mean ( 31 / 38 ) & 2319.03 & 6.73052 & 344.555 \tabularnewline
Trimmed Mean ( 32 / 38 ) & 2317.48 & 6.5216 & 355.354 \tabularnewline
Trimmed Mean ( 33 / 38 ) & 2316.93 & 6.35987 & 364.304 \tabularnewline
Trimmed Mean ( 34 / 38 ) & 2316.61 & 6.23909 & 371.306 \tabularnewline
Trimmed Mean ( 35 / 38 ) & 2316.37 & 6.11484 & 378.811 \tabularnewline
Trimmed Mean ( 36 / 38 ) & 2316.18 & 5.99054 & 386.64 \tabularnewline
Trimmed Mean ( 37 / 38 ) & 2316.22 & 5.97727 & 387.504 \tabularnewline
Trimmed Mean ( 38 / 38 ) & 2316.26 & 5.94695 & 389.486 \tabularnewline
Median & 2313.95 &  &  \tabularnewline
Midrange & 2332.4 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 2318.42 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 2319.87 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 2318.42 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 2319.87 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 2319.87 &  &  \tabularnewline
Midmean - Closest Observation & 2318.42 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 2319.87 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 2320.57 &  &  \tabularnewline
Number of observations & 116 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301201&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]2332.3[/C][C]11.7649[/C][C]198.243[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]2328.9[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]2325.52[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]2335.71[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 38 )[/C][C]2332.35[/C][C]11.738[/C][C]198.701[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 38 )[/C][C]2332.42[/C][C]11.7229[/C][C]198.963[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 38 )[/C][C]2332.22[/C][C]11.6767[/C][C]199.732[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 38 )[/C][C]2332.23[/C][C]11.6334[/C][C]200.477[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 38 )[/C][C]2331.94[/C][C]11.5044[/C][C]202.699[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 38 )[/C][C]2332.71[/C][C]11.3788[/C][C]205.005[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 38 )[/C][C]2332.81[/C][C]11.3271[/C][C]205.949[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 38 )[/C][C]2333.89[/C][C]11.1585[/C][C]209.159[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 38 )[/C][C]2334.19[/C][C]11.023[/C][C]211.758[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 38 )[/C][C]2333.4[/C][C]10.8404[/C][C]215.25[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 38 )[/C][C]2334.28[/C][C]10.7133[/C][C]217.886[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 38 )[/C][C]2334.98[/C][C]10.5849[/C][C]220.594[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 38 )[/C][C]2335.22[/C][C]10.1871[/C][C]229.233[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 38 )[/C][C]2335.33[/C][C]10.0789[/C][C]231.704[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 38 )[/C][C]2335.86[/C][C]9.98139[/C][C]234.022[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 38 )[/C][C]2335.86[/C][C]9.80395[/C][C]238.257[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 38 )[/C][C]2334.72[/C][C]9.61797[/C][C]242.745[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 38 )[/C][C]2333.59[/C][C]9.40185[/C][C]248.205[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 38 )[/C][C]2333.57[/C][C]9.38741[/C][C]248.585[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 38 )[/C][C]2333.47[/C][C]9.35187[/C][C]249.519[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 38 )[/C][C]2333.56[/C][C]9.27934[/C][C]251.479[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 38 )[/C][C]2334.09[/C][C]9.21218[/C][C]253.37[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 38 )[/C][C]2333.29[/C][C]8.89719[/C][C]262.251[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 38 )[/C][C]2333.25[/C][C]8.87665[/C][C]262.853[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 38 )[/C][C]2332.07[/C][C]8.43598[/C][C]276.443[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 38 )[/C][C]2331.51[/C][C]8.35214[/C][C]279.151[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 38 )[/C][C]2331.88[/C][C]8.28545[/C][C]281.443[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 38 )[/C][C]2330.34[/C][C]7.95025[/C][C]293.115[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 38 )[/C][C]2331.59[/C][C]7.67057[/C][C]303.965[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 38 )[/C][C]2331.64[/C][C]7.59407[/C][C]307.034[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 38 )[/C][C]2327.23[/C][C]6.93665[/C][C]335.497[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 38 )[/C][C]2325.08[/C][C]6.38507[/C][C]364.142[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 38 )[/C][C]2321.24[/C][C]5.92947[/C][C]391.475[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 38 )[/C][C]2319.86[/C][C]5.74772[/C][C]403.614[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 38 )[/C][C]2318.86[/C][C]5.53857[/C][C]418.675[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 38 )[/C][C]2315.73[/C][C]4.72122[/C][C]490.493[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 38 )[/C][C]2315.73[/C][C]4.71459[/C][C]491.183[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 38 )[/C][C]2315.4[/C][C]4.66041[/C][C]496.823[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 38 )[/C][C]2332.29[/C][C]11.5914[/C][C]201.209[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 38 )[/C][C]2332.23[/C][C]11.4282[/C][C]204.077[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 38 )[/C][C]2332.14[/C][C]11.2551[/C][C]207.207[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 38 )[/C][C]2332.11[/C][C]11.0807[/C][C]210.466[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 38 )[/C][C]2332.08[/C][C]10.8995[/C][C]213.962[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 38 )[/C][C]2332.11[/C][C]10.7312[/C][C]217.321[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 38 )[/C][C]2331.99[/C][C]10.5714[/C][C]220.596[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 38 )[/C][C]2331.86[/C][C]10.4022[/C][C]224.17[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 38 )[/C][C]2331.56[/C][C]10.2434[/C][C]227.615[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 38 )[/C][C]2331.2[/C][C]10.0877[/C][C]231.093[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 38 )[/C][C]2330.93[/C][C]9.94178[/C][C]234.458[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 38 )[/C][C]2330.55[/C][C]9.79531[/C][C]237.925[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 38 )[/C][C]2330.07[/C][C]9.64705[/C][C]241.532[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 38 )[/C][C]2329.55[/C][C]9.53494[/C][C]244.317[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 38 )[/C][C]2328.99[/C][C]9.42001[/C][C]247.239[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 38 )[/C][C]2328.36[/C][C]9.29922[/C][C]250.382[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 38 )[/C][C]2327.7[/C][C]9.18221[/C][C]253.501[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 38 )[/C][C]2327.1[/C][C]9.0707[/C][C]256.551[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 38 )[/C][C]2326.56[/C][C]8.96843[/C][C]259.417[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 38 )[/C][C]2326[/C][C]8.84872[/C][C]262.863[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 38 )[/C][C]2325.42[/C][C]8.71131[/C][C]266.942[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 38 )[/C][C]2324.79[/C][C]8.55767[/C][C]271.662[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 38 )[/C][C]2324.09[/C][C]8.38315[/C][C]277.234[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 38 )[/C][C]2323.41[/C][C]8.21978[/C][C]282.661[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 38 )[/C][C]2322.69[/C][C]8.02606[/C][C]289.393[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 38 )[/C][C]2322.01[/C][C]7.8584[/C][C]295.481[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 38 )[/C][C]2321.32[/C][C]7.66753[/C][C]302.747[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 38 )[/C][C]2320.57[/C][C]7.4438[/C][C]311.745[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 38 )[/C][C]2319.87[/C][C]7.22595[/C][C]321.047[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 38 )[/C][C]2319.03[/C][C]6.99999[/C][C]331.291[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 38 )[/C][C]2319.03[/C][C]6.73052[/C][C]344.555[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 38 )[/C][C]2317.48[/C][C]6.5216[/C][C]355.354[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 38 )[/C][C]2316.93[/C][C]6.35987[/C][C]364.304[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 38 )[/C][C]2316.61[/C][C]6.23909[/C][C]371.306[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 38 )[/C][C]2316.37[/C][C]6.11484[/C][C]378.811[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 38 )[/C][C]2316.18[/C][C]5.99054[/C][C]386.64[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 38 )[/C][C]2316.22[/C][C]5.97727[/C][C]387.504[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 38 )[/C][C]2316.26[/C][C]5.94695[/C][C]389.486[/C][/ROW]
[ROW][C]Median[/C][C]2313.95[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]2332.4[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]2318.42[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]2319.87[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]2318.42[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]2319.87[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]2319.87[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]2318.42[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]2319.87[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]2320.57[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]116[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301201&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301201&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 Mean2332.311.7649198.243
Geometric Mean2328.9
Harmonic Mean2325.52
Quadratic Mean2335.71
Winsorized Mean ( 1 / 38 )2332.3511.738198.701
Winsorized Mean ( 2 / 38 )2332.4211.7229198.963
Winsorized Mean ( 3 / 38 )2332.2211.6767199.732
Winsorized Mean ( 4 / 38 )2332.2311.6334200.477
Winsorized Mean ( 5 / 38 )2331.9411.5044202.699
Winsorized Mean ( 6 / 38 )2332.7111.3788205.005
Winsorized Mean ( 7 / 38 )2332.8111.3271205.949
Winsorized Mean ( 8 / 38 )2333.8911.1585209.159
Winsorized Mean ( 9 / 38 )2334.1911.023211.758
Winsorized Mean ( 10 / 38 )2333.410.8404215.25
Winsorized Mean ( 11 / 38 )2334.2810.7133217.886
Winsorized Mean ( 12 / 38 )2334.9810.5849220.594
Winsorized Mean ( 13 / 38 )2335.2210.1871229.233
Winsorized Mean ( 14 / 38 )2335.3310.0789231.704
Winsorized Mean ( 15 / 38 )2335.869.98139234.022
Winsorized Mean ( 16 / 38 )2335.869.80395238.257
Winsorized Mean ( 17 / 38 )2334.729.61797242.745
Winsorized Mean ( 18 / 38 )2333.599.40185248.205
Winsorized Mean ( 19 / 38 )2333.579.38741248.585
Winsorized Mean ( 20 / 38 )2333.479.35187249.519
Winsorized Mean ( 21 / 38 )2333.569.27934251.479
Winsorized Mean ( 22 / 38 )2334.099.21218253.37
Winsorized Mean ( 23 / 38 )2333.298.89719262.251
Winsorized Mean ( 24 / 38 )2333.258.87665262.853
Winsorized Mean ( 25 / 38 )2332.078.43598276.443
Winsorized Mean ( 26 / 38 )2331.518.35214279.151
Winsorized Mean ( 27 / 38 )2331.888.28545281.443
Winsorized Mean ( 28 / 38 )2330.347.95025293.115
Winsorized Mean ( 29 / 38 )2331.597.67057303.965
Winsorized Mean ( 30 / 38 )2331.647.59407307.034
Winsorized Mean ( 31 / 38 )2327.236.93665335.497
Winsorized Mean ( 32 / 38 )2325.086.38507364.142
Winsorized Mean ( 33 / 38 )2321.245.92947391.475
Winsorized Mean ( 34 / 38 )2319.865.74772403.614
Winsorized Mean ( 35 / 38 )2318.865.53857418.675
Winsorized Mean ( 36 / 38 )2315.734.72122490.493
Winsorized Mean ( 37 / 38 )2315.734.71459491.183
Winsorized Mean ( 38 / 38 )2315.44.66041496.823
Trimmed Mean ( 1 / 38 )2332.2911.5914201.209
Trimmed Mean ( 2 / 38 )2332.2311.4282204.077
Trimmed Mean ( 3 / 38 )2332.1411.2551207.207
Trimmed Mean ( 4 / 38 )2332.1111.0807210.466
Trimmed Mean ( 5 / 38 )2332.0810.8995213.962
Trimmed Mean ( 6 / 38 )2332.1110.7312217.321
Trimmed Mean ( 7 / 38 )2331.9910.5714220.596
Trimmed Mean ( 8 / 38 )2331.8610.4022224.17
Trimmed Mean ( 9 / 38 )2331.5610.2434227.615
Trimmed Mean ( 10 / 38 )2331.210.0877231.093
Trimmed Mean ( 11 / 38 )2330.939.94178234.458
Trimmed Mean ( 12 / 38 )2330.559.79531237.925
Trimmed Mean ( 13 / 38 )2330.079.64705241.532
Trimmed Mean ( 14 / 38 )2329.559.53494244.317
Trimmed Mean ( 15 / 38 )2328.999.42001247.239
Trimmed Mean ( 16 / 38 )2328.369.29922250.382
Trimmed Mean ( 17 / 38 )2327.79.18221253.501
Trimmed Mean ( 18 / 38 )2327.19.0707256.551
Trimmed Mean ( 19 / 38 )2326.568.96843259.417
Trimmed Mean ( 20 / 38 )23268.84872262.863
Trimmed Mean ( 21 / 38 )2325.428.71131266.942
Trimmed Mean ( 22 / 38 )2324.798.55767271.662
Trimmed Mean ( 23 / 38 )2324.098.38315277.234
Trimmed Mean ( 24 / 38 )2323.418.21978282.661
Trimmed Mean ( 25 / 38 )2322.698.02606289.393
Trimmed Mean ( 26 / 38 )2322.017.8584295.481
Trimmed Mean ( 27 / 38 )2321.327.66753302.747
Trimmed Mean ( 28 / 38 )2320.577.4438311.745
Trimmed Mean ( 29 / 38 )2319.877.22595321.047
Trimmed Mean ( 30 / 38 )2319.036.99999331.291
Trimmed Mean ( 31 / 38 )2319.036.73052344.555
Trimmed Mean ( 32 / 38 )2317.486.5216355.354
Trimmed Mean ( 33 / 38 )2316.936.35987364.304
Trimmed Mean ( 34 / 38 )2316.616.23909371.306
Trimmed Mean ( 35 / 38 )2316.376.11484378.811
Trimmed Mean ( 36 / 38 )2316.185.99054386.64
Trimmed Mean ( 37 / 38 )2316.225.97727387.504
Trimmed Mean ( 38 / 38 )2316.265.94695389.486
Median2313.95
Midrange2332.4
Midmean - Weighted Average at Xnp2318.42
Midmean - Weighted Average at X(n+1)p2319.87
Midmean - Empirical Distribution Function2318.42
Midmean - Empirical Distribution Function - Averaging2319.87
Midmean - Empirical Distribution Function - Interpolation2319.87
Midmean - Closest Observation2318.42
Midmean - True Basic - Statistics Graphics Toolkit2319.87
Midmean - MS Excel (old versions)2320.57
Number of observations116



Parameters (Session):
par1 = n1862 ; par4 = 12 ;
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')