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Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationWed, 16 Aug 2017 09:28:38 +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/Aug/16/t150286867771opyvvawtu7mzo.htm/, Retrieved Sun, 12 May 2024 08:56:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307347, Retrieved Sun, 12 May 2024 08:56:39 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2017-08-16 07:28:38] [888a13d027786d499af5f5e6685ea85b] [Current]
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Dataseries X:
19064
18993
18921
18772
20246
20168
19064
18330
18401
18401
18480
18622
18843
18843
18701
18330
20246
20538
20097
19064
19506
18843
19142
19285
19434
19064
19142
18622
20246
20759
20318
19506
20389
19434
20318
20246
20467
19655
20538
20467
21792
21493
20318
19726
20538
19434
20246
20389
20688
20026
20389
20610
21422
20759
19876
18921
19805
17375
18551
19213
19876
18921
18921
18921
19434
18701
17739
16934
17518
15238
16635
17447
17596
16784
16855
16635
17375
16855
15830
15089
16342
13621
15388
16193
16193
15238
14355
14284
15089
14355
12959
11997
13030
10601
12809
13984
14355
13543
12517
13251
13543
13322
11113
10088
10821
8613
10893
11705
12367
11263
10230
10821
11113
10529
8321
7359
8242
5813
8463
10088




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 time3 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307347&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]3 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=307347&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307347&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 time3 seconds
R ServerBig Analytics Cloud Computing Center







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean16776.6346.22948.4552
Geometric Mean16251.9
Harmonic Mean15603
Quadratic Mean17196.5
Winsorized Mean ( 1 / 40 )16787342.72948.9804
Winsorized Mean ( 2 / 40 )16800.5339.33249.5106
Winsorized Mean ( 3 / 40 )16785.9337.14449.7885
Winsorized Mean ( 4 / 40 )16790.6336.15249.9495
Winsorized Mean ( 5 / 40 )16793.9334.56850.1959
Winsorized Mean ( 6 / 40 )16863.8320.02552.6952
Winsorized Mean ( 7 / 40 )16859.6319.61552.7496
Winsorized Mean ( 8 / 40 )16869.1317.94253.057
Winsorized Mean ( 9 / 40 )16891.5314.06553.7833
Winsorized Mean ( 10 / 40 )16891.6312.47454.0575
Winsorized Mean ( 11 / 40 )16911.7309.09854.7131
Winsorized Mean ( 12 / 40 )16903.9308.35154.8204
Winsorized Mean ( 13 / 40 )16911.7307.06255.0759
Winsorized Mean ( 14 / 40 )16937.4302.87455.9222
Winsorized Mean ( 15 / 40 )16928.5302.03156.049
Winsorized Mean ( 16 / 40 )16948.5298.81456.7194
Winsorized Mean ( 17 / 40 )17011.1288.97458.8674
Winsorized Mean ( 18 / 40 )17044.1281.25560.6003
Winsorized Mean ( 19 / 40 )17102.7272.55962.7487
Winsorized Mean ( 20 / 40 )17127.7268.93363.6878
Winsorized Mean ( 21 / 40 )17178.8261.66565.652
Winsorized Mean ( 22 / 40 )17206.3257.83266.7347
Winsorized Mean ( 23 / 40 )17205254.4867.6085
Winsorized Mean ( 24 / 40 )17235247.05169.7628
Winsorized Mean ( 25 / 40 )17235243.61970.7457
Winsorized Mean ( 26 / 40 )17250.4234.10373.6869
Winsorized Mean ( 27 / 40 )17250.4234.10373.6869
Winsorized Mean ( 28 / 40 )17252230.13374.9654
Winsorized Mean ( 29 / 40 )17320.6216.86279.8693
Winsorized Mean ( 30 / 40 )17377.9205.61684.5162
Winsorized Mean ( 31 / 40 )17357.7199.76786.8899
Winsorized Mean ( 32 / 40 )17357.7199.76786.8899
Winsorized Mean ( 33 / 40 )17337.9197.99187.5691
Winsorized Mean ( 34 / 40 )17545.9172.319101.822
Winsorized Mean ( 35 / 40 )17545.9172.319101.822
Winsorized Mean ( 36 / 40 )17590.6166.995105.336
Winsorized Mean ( 37 / 40 )17544.7162.8107.768
Winsorized Mean ( 38 / 40 )17569.4155.126113.259
Winsorized Mean ( 39 / 40 )17689.9136.328129.76
Winsorized Mean ( 40 / 40 )17810.9122.674145.189
Trimmed Mean ( 1 / 40 )16827336.80849.9602
Trimmed Mean ( 2 / 40 )16868.4330.20651.0845
Trimmed Mean ( 3 / 40 )16904.1324.8352.0398
Trimmed Mean ( 4 / 40 )16946.3319.68253.0099
Trimmed Mean ( 5 / 40 )16988.8314.21854.0669
Trimmed Mean ( 6 / 40 )17032.1308.49455.2104
Trimmed Mean ( 7 / 40 )17063.9305.48255.8589
Trimmed Mean ( 8 / 40 )17097.5302.12656.5908
Trimmed Mean ( 9 / 40 )17131.1298.62157.3675
Trimmed Mean ( 10 / 40 )17163.1295.31358.1182
Trimmed Mean ( 11 / 40 )17196.3291.77958.9361
Trimmed Mean ( 12 / 40 )17228.7288.26759.7664
Trimmed Mean ( 13 / 40 )17263.2284.32260.7172
Trimmed Mean ( 14 / 40 )17298.5279.97161.7867
Trimmed Mean ( 15 / 40 )17332.9275.57962.8961
Trimmed Mean ( 16 / 40 )17369.6270.59764.19
Trimmed Mean ( 17 / 40 )17406.3265.29665.6109
Trimmed Mean ( 18 / 40 )17439.6260.58266.9255
Trimmed Mean ( 19 / 40 )17471.7256.1668.2061
Trimmed Mean ( 20 / 40 )17500.8252.2169.39
Trimmed Mean ( 21 / 40 )17529.5248.06170.6663
Trimmed Mean ( 22 / 40 )17555.9244.18171.8971
Trimmed Mean ( 23 / 40 )17581.7240.1173.2233
Trimmed Mean ( 24 / 40 )17609235.69474.711
Trimmed Mean ( 25 / 40 )17635.7231.45576.195
Trimmed Mean ( 26 / 40 )17664226.8177.8801
Trimmed Mean ( 27 / 40 )17692.9222.53279.5073
Trimmed Mean ( 28 / 40 )17723.6217.30481.5616
Trimmed Mean ( 29 / 40 )17756.2211.49283.9569
Trimmed Mean ( 30 / 40 )17786.3206.53286.1185
Trimmed Mean ( 31 / 40 )17814.4202.22488.0927
Trimmed Mean ( 32 / 40 )17846197.64290.2945
Trimmed Mean ( 33 / 40 )17879.9191.8293.2118
Trimmed Mean ( 34 / 40 )17917.8184.6297.0522
Trimmed Mean ( 35 / 40 )17944.1180.76699.2668
Trimmed Mean ( 36 / 40 )17972.5175.704102.289
Trimmed Mean ( 37 / 40 )18000.2170.249105.729
Trimmed Mean ( 38 / 40 )18033.8163.647110.199
Trimmed Mean ( 39 / 40 )18068.7156.594115.385
Trimmed Mean ( 40 / 40 )18097.8151.972119.087
Median18515.5
Midrange13802.5
Midmean - Weighted Average at Xnp17723.9
Midmean - Weighted Average at X(n+1)p17786.3
Midmean - Empirical Distribution Function17723.9
Midmean - Empirical Distribution Function - Averaging17786.3
Midmean - Empirical Distribution Function - Interpolation17786.3
Midmean - Closest Observation17723.9
Midmean - True Basic - Statistics Graphics Toolkit17786.3
Midmean - MS Excel (old versions)17756.2
Number of observations120

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 16776.6 & 346.229 & 48.4552 \tabularnewline
Geometric Mean & 16251.9 &  &  \tabularnewline
Harmonic Mean & 15603 &  &  \tabularnewline
Quadratic Mean & 17196.5 &  &  \tabularnewline
Winsorized Mean ( 1 / 40 ) & 16787 & 342.729 & 48.9804 \tabularnewline
Winsorized Mean ( 2 / 40 ) & 16800.5 & 339.332 & 49.5106 \tabularnewline
Winsorized Mean ( 3 / 40 ) & 16785.9 & 337.144 & 49.7885 \tabularnewline
Winsorized Mean ( 4 / 40 ) & 16790.6 & 336.152 & 49.9495 \tabularnewline
Winsorized Mean ( 5 / 40 ) & 16793.9 & 334.568 & 50.1959 \tabularnewline
Winsorized Mean ( 6 / 40 ) & 16863.8 & 320.025 & 52.6952 \tabularnewline
Winsorized Mean ( 7 / 40 ) & 16859.6 & 319.615 & 52.7496 \tabularnewline
Winsorized Mean ( 8 / 40 ) & 16869.1 & 317.942 & 53.057 \tabularnewline
Winsorized Mean ( 9 / 40 ) & 16891.5 & 314.065 & 53.7833 \tabularnewline
Winsorized Mean ( 10 / 40 ) & 16891.6 & 312.474 & 54.0575 \tabularnewline
Winsorized Mean ( 11 / 40 ) & 16911.7 & 309.098 & 54.7131 \tabularnewline
Winsorized Mean ( 12 / 40 ) & 16903.9 & 308.351 & 54.8204 \tabularnewline
Winsorized Mean ( 13 / 40 ) & 16911.7 & 307.062 & 55.0759 \tabularnewline
Winsorized Mean ( 14 / 40 ) & 16937.4 & 302.874 & 55.9222 \tabularnewline
Winsorized Mean ( 15 / 40 ) & 16928.5 & 302.031 & 56.049 \tabularnewline
Winsorized Mean ( 16 / 40 ) & 16948.5 & 298.814 & 56.7194 \tabularnewline
Winsorized Mean ( 17 / 40 ) & 17011.1 & 288.974 & 58.8674 \tabularnewline
Winsorized Mean ( 18 / 40 ) & 17044.1 & 281.255 & 60.6003 \tabularnewline
Winsorized Mean ( 19 / 40 ) & 17102.7 & 272.559 & 62.7487 \tabularnewline
Winsorized Mean ( 20 / 40 ) & 17127.7 & 268.933 & 63.6878 \tabularnewline
Winsorized Mean ( 21 / 40 ) & 17178.8 & 261.665 & 65.652 \tabularnewline
Winsorized Mean ( 22 / 40 ) & 17206.3 & 257.832 & 66.7347 \tabularnewline
Winsorized Mean ( 23 / 40 ) & 17205 & 254.48 & 67.6085 \tabularnewline
Winsorized Mean ( 24 / 40 ) & 17235 & 247.051 & 69.7628 \tabularnewline
Winsorized Mean ( 25 / 40 ) & 17235 & 243.619 & 70.7457 \tabularnewline
Winsorized Mean ( 26 / 40 ) & 17250.4 & 234.103 & 73.6869 \tabularnewline
Winsorized Mean ( 27 / 40 ) & 17250.4 & 234.103 & 73.6869 \tabularnewline
Winsorized Mean ( 28 / 40 ) & 17252 & 230.133 & 74.9654 \tabularnewline
Winsorized Mean ( 29 / 40 ) & 17320.6 & 216.862 & 79.8693 \tabularnewline
Winsorized Mean ( 30 / 40 ) & 17377.9 & 205.616 & 84.5162 \tabularnewline
Winsorized Mean ( 31 / 40 ) & 17357.7 & 199.767 & 86.8899 \tabularnewline
Winsorized Mean ( 32 / 40 ) & 17357.7 & 199.767 & 86.8899 \tabularnewline
Winsorized Mean ( 33 / 40 ) & 17337.9 & 197.991 & 87.5691 \tabularnewline
Winsorized Mean ( 34 / 40 ) & 17545.9 & 172.319 & 101.822 \tabularnewline
Winsorized Mean ( 35 / 40 ) & 17545.9 & 172.319 & 101.822 \tabularnewline
Winsorized Mean ( 36 / 40 ) & 17590.6 & 166.995 & 105.336 \tabularnewline
Winsorized Mean ( 37 / 40 ) & 17544.7 & 162.8 & 107.768 \tabularnewline
Winsorized Mean ( 38 / 40 ) & 17569.4 & 155.126 & 113.259 \tabularnewline
Winsorized Mean ( 39 / 40 ) & 17689.9 & 136.328 & 129.76 \tabularnewline
Winsorized Mean ( 40 / 40 ) & 17810.9 & 122.674 & 145.189 \tabularnewline
Trimmed Mean ( 1 / 40 ) & 16827 & 336.808 & 49.9602 \tabularnewline
Trimmed Mean ( 2 / 40 ) & 16868.4 & 330.206 & 51.0845 \tabularnewline
Trimmed Mean ( 3 / 40 ) & 16904.1 & 324.83 & 52.0398 \tabularnewline
Trimmed Mean ( 4 / 40 ) & 16946.3 & 319.682 & 53.0099 \tabularnewline
Trimmed Mean ( 5 / 40 ) & 16988.8 & 314.218 & 54.0669 \tabularnewline
Trimmed Mean ( 6 / 40 ) & 17032.1 & 308.494 & 55.2104 \tabularnewline
Trimmed Mean ( 7 / 40 ) & 17063.9 & 305.482 & 55.8589 \tabularnewline
Trimmed Mean ( 8 / 40 ) & 17097.5 & 302.126 & 56.5908 \tabularnewline
Trimmed Mean ( 9 / 40 ) & 17131.1 & 298.621 & 57.3675 \tabularnewline
Trimmed Mean ( 10 / 40 ) & 17163.1 & 295.313 & 58.1182 \tabularnewline
Trimmed Mean ( 11 / 40 ) & 17196.3 & 291.779 & 58.9361 \tabularnewline
Trimmed Mean ( 12 / 40 ) & 17228.7 & 288.267 & 59.7664 \tabularnewline
Trimmed Mean ( 13 / 40 ) & 17263.2 & 284.322 & 60.7172 \tabularnewline
Trimmed Mean ( 14 / 40 ) & 17298.5 & 279.971 & 61.7867 \tabularnewline
Trimmed Mean ( 15 / 40 ) & 17332.9 & 275.579 & 62.8961 \tabularnewline
Trimmed Mean ( 16 / 40 ) & 17369.6 & 270.597 & 64.19 \tabularnewline
Trimmed Mean ( 17 / 40 ) & 17406.3 & 265.296 & 65.6109 \tabularnewline
Trimmed Mean ( 18 / 40 ) & 17439.6 & 260.582 & 66.9255 \tabularnewline
Trimmed Mean ( 19 / 40 ) & 17471.7 & 256.16 & 68.2061 \tabularnewline
Trimmed Mean ( 20 / 40 ) & 17500.8 & 252.21 & 69.39 \tabularnewline
Trimmed Mean ( 21 / 40 ) & 17529.5 & 248.061 & 70.6663 \tabularnewline
Trimmed Mean ( 22 / 40 ) & 17555.9 & 244.181 & 71.8971 \tabularnewline
Trimmed Mean ( 23 / 40 ) & 17581.7 & 240.11 & 73.2233 \tabularnewline
Trimmed Mean ( 24 / 40 ) & 17609 & 235.694 & 74.711 \tabularnewline
Trimmed Mean ( 25 / 40 ) & 17635.7 & 231.455 & 76.195 \tabularnewline
Trimmed Mean ( 26 / 40 ) & 17664 & 226.81 & 77.8801 \tabularnewline
Trimmed Mean ( 27 / 40 ) & 17692.9 & 222.532 & 79.5073 \tabularnewline
Trimmed Mean ( 28 / 40 ) & 17723.6 & 217.304 & 81.5616 \tabularnewline
Trimmed Mean ( 29 / 40 ) & 17756.2 & 211.492 & 83.9569 \tabularnewline
Trimmed Mean ( 30 / 40 ) & 17786.3 & 206.532 & 86.1185 \tabularnewline
Trimmed Mean ( 31 / 40 ) & 17814.4 & 202.224 & 88.0927 \tabularnewline
Trimmed Mean ( 32 / 40 ) & 17846 & 197.642 & 90.2945 \tabularnewline
Trimmed Mean ( 33 / 40 ) & 17879.9 & 191.82 & 93.2118 \tabularnewline
Trimmed Mean ( 34 / 40 ) & 17917.8 & 184.62 & 97.0522 \tabularnewline
Trimmed Mean ( 35 / 40 ) & 17944.1 & 180.766 & 99.2668 \tabularnewline
Trimmed Mean ( 36 / 40 ) & 17972.5 & 175.704 & 102.289 \tabularnewline
Trimmed Mean ( 37 / 40 ) & 18000.2 & 170.249 & 105.729 \tabularnewline
Trimmed Mean ( 38 / 40 ) & 18033.8 & 163.647 & 110.199 \tabularnewline
Trimmed Mean ( 39 / 40 ) & 18068.7 & 156.594 & 115.385 \tabularnewline
Trimmed Mean ( 40 / 40 ) & 18097.8 & 151.972 & 119.087 \tabularnewline
Median & 18515.5 &  &  \tabularnewline
Midrange & 13802.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 17723.9 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 17786.3 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 17723.9 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 17786.3 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 17786.3 &  &  \tabularnewline
Midmean - Closest Observation & 17723.9 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 17786.3 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 17756.2 &  &  \tabularnewline
Number of observations & 120 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307347&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]16776.6[/C][C]346.229[/C][C]48.4552[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]16251.9[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]15603[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]17196.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 40 )[/C][C]16787[/C][C]342.729[/C][C]48.9804[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 40 )[/C][C]16800.5[/C][C]339.332[/C][C]49.5106[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 40 )[/C][C]16785.9[/C][C]337.144[/C][C]49.7885[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 40 )[/C][C]16790.6[/C][C]336.152[/C][C]49.9495[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 40 )[/C][C]16793.9[/C][C]334.568[/C][C]50.1959[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 40 )[/C][C]16863.8[/C][C]320.025[/C][C]52.6952[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 40 )[/C][C]16859.6[/C][C]319.615[/C][C]52.7496[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 40 )[/C][C]16869.1[/C][C]317.942[/C][C]53.057[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 40 )[/C][C]16891.5[/C][C]314.065[/C][C]53.7833[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 40 )[/C][C]16891.6[/C][C]312.474[/C][C]54.0575[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 40 )[/C][C]16911.7[/C][C]309.098[/C][C]54.7131[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 40 )[/C][C]16903.9[/C][C]308.351[/C][C]54.8204[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 40 )[/C][C]16911.7[/C][C]307.062[/C][C]55.0759[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 40 )[/C][C]16937.4[/C][C]302.874[/C][C]55.9222[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 40 )[/C][C]16928.5[/C][C]302.031[/C][C]56.049[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 40 )[/C][C]16948.5[/C][C]298.814[/C][C]56.7194[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 40 )[/C][C]17011.1[/C][C]288.974[/C][C]58.8674[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 40 )[/C][C]17044.1[/C][C]281.255[/C][C]60.6003[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 40 )[/C][C]17102.7[/C][C]272.559[/C][C]62.7487[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 40 )[/C][C]17127.7[/C][C]268.933[/C][C]63.6878[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 40 )[/C][C]17178.8[/C][C]261.665[/C][C]65.652[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 40 )[/C][C]17206.3[/C][C]257.832[/C][C]66.7347[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 40 )[/C][C]17205[/C][C]254.48[/C][C]67.6085[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 40 )[/C][C]17235[/C][C]247.051[/C][C]69.7628[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 40 )[/C][C]17235[/C][C]243.619[/C][C]70.7457[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 40 )[/C][C]17250.4[/C][C]234.103[/C][C]73.6869[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 40 )[/C][C]17250.4[/C][C]234.103[/C][C]73.6869[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 40 )[/C][C]17252[/C][C]230.133[/C][C]74.9654[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 40 )[/C][C]17320.6[/C][C]216.862[/C][C]79.8693[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 40 )[/C][C]17377.9[/C][C]205.616[/C][C]84.5162[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 40 )[/C][C]17357.7[/C][C]199.767[/C][C]86.8899[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 40 )[/C][C]17357.7[/C][C]199.767[/C][C]86.8899[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 40 )[/C][C]17337.9[/C][C]197.991[/C][C]87.5691[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 40 )[/C][C]17545.9[/C][C]172.319[/C][C]101.822[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 40 )[/C][C]17545.9[/C][C]172.319[/C][C]101.822[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 40 )[/C][C]17590.6[/C][C]166.995[/C][C]105.336[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 40 )[/C][C]17544.7[/C][C]162.8[/C][C]107.768[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 40 )[/C][C]17569.4[/C][C]155.126[/C][C]113.259[/C][/ROW]
[ROW][C]Winsorized Mean ( 39 / 40 )[/C][C]17689.9[/C][C]136.328[/C][C]129.76[/C][/ROW]
[ROW][C]Winsorized Mean ( 40 / 40 )[/C][C]17810.9[/C][C]122.674[/C][C]145.189[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 40 )[/C][C]16827[/C][C]336.808[/C][C]49.9602[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 40 )[/C][C]16868.4[/C][C]330.206[/C][C]51.0845[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 40 )[/C][C]16904.1[/C][C]324.83[/C][C]52.0398[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 40 )[/C][C]16946.3[/C][C]319.682[/C][C]53.0099[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 40 )[/C][C]16988.8[/C][C]314.218[/C][C]54.0669[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 40 )[/C][C]17032.1[/C][C]308.494[/C][C]55.2104[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 40 )[/C][C]17063.9[/C][C]305.482[/C][C]55.8589[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 40 )[/C][C]17097.5[/C][C]302.126[/C][C]56.5908[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 40 )[/C][C]17131.1[/C][C]298.621[/C][C]57.3675[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 40 )[/C][C]17163.1[/C][C]295.313[/C][C]58.1182[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 40 )[/C][C]17196.3[/C][C]291.779[/C][C]58.9361[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 40 )[/C][C]17228.7[/C][C]288.267[/C][C]59.7664[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 40 )[/C][C]17263.2[/C][C]284.322[/C][C]60.7172[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 40 )[/C][C]17298.5[/C][C]279.971[/C][C]61.7867[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 40 )[/C][C]17332.9[/C][C]275.579[/C][C]62.8961[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 40 )[/C][C]17369.6[/C][C]270.597[/C][C]64.19[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 40 )[/C][C]17406.3[/C][C]265.296[/C][C]65.6109[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 40 )[/C][C]17439.6[/C][C]260.582[/C][C]66.9255[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 40 )[/C][C]17471.7[/C][C]256.16[/C][C]68.2061[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 40 )[/C][C]17500.8[/C][C]252.21[/C][C]69.39[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 40 )[/C][C]17529.5[/C][C]248.061[/C][C]70.6663[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 40 )[/C][C]17555.9[/C][C]244.181[/C][C]71.8971[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 40 )[/C][C]17581.7[/C][C]240.11[/C][C]73.2233[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 40 )[/C][C]17609[/C][C]235.694[/C][C]74.711[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 40 )[/C][C]17635.7[/C][C]231.455[/C][C]76.195[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 40 )[/C][C]17664[/C][C]226.81[/C][C]77.8801[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 40 )[/C][C]17692.9[/C][C]222.532[/C][C]79.5073[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 40 )[/C][C]17723.6[/C][C]217.304[/C][C]81.5616[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 40 )[/C][C]17756.2[/C][C]211.492[/C][C]83.9569[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 40 )[/C][C]17786.3[/C][C]206.532[/C][C]86.1185[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 40 )[/C][C]17814.4[/C][C]202.224[/C][C]88.0927[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 40 )[/C][C]17846[/C][C]197.642[/C][C]90.2945[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 40 )[/C][C]17879.9[/C][C]191.82[/C][C]93.2118[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 40 )[/C][C]17917.8[/C][C]184.62[/C][C]97.0522[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 40 )[/C][C]17944.1[/C][C]180.766[/C][C]99.2668[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 40 )[/C][C]17972.5[/C][C]175.704[/C][C]102.289[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 40 )[/C][C]18000.2[/C][C]170.249[/C][C]105.729[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 40 )[/C][C]18033.8[/C][C]163.647[/C][C]110.199[/C][/ROW]
[ROW][C]Trimmed Mean ( 39 / 40 )[/C][C]18068.7[/C][C]156.594[/C][C]115.385[/C][/ROW]
[ROW][C]Trimmed Mean ( 40 / 40 )[/C][C]18097.8[/C][C]151.972[/C][C]119.087[/C][/ROW]
[ROW][C]Median[/C][C]18515.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]13802.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]17723.9[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]17786.3[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]17723.9[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]17786.3[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]17786.3[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]17723.9[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]17786.3[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]17756.2[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]120[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307347&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307347&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 Mean16776.6346.22948.4552
Geometric Mean16251.9
Harmonic Mean15603
Quadratic Mean17196.5
Winsorized Mean ( 1 / 40 )16787342.72948.9804
Winsorized Mean ( 2 / 40 )16800.5339.33249.5106
Winsorized Mean ( 3 / 40 )16785.9337.14449.7885
Winsorized Mean ( 4 / 40 )16790.6336.15249.9495
Winsorized Mean ( 5 / 40 )16793.9334.56850.1959
Winsorized Mean ( 6 / 40 )16863.8320.02552.6952
Winsorized Mean ( 7 / 40 )16859.6319.61552.7496
Winsorized Mean ( 8 / 40 )16869.1317.94253.057
Winsorized Mean ( 9 / 40 )16891.5314.06553.7833
Winsorized Mean ( 10 / 40 )16891.6312.47454.0575
Winsorized Mean ( 11 / 40 )16911.7309.09854.7131
Winsorized Mean ( 12 / 40 )16903.9308.35154.8204
Winsorized Mean ( 13 / 40 )16911.7307.06255.0759
Winsorized Mean ( 14 / 40 )16937.4302.87455.9222
Winsorized Mean ( 15 / 40 )16928.5302.03156.049
Winsorized Mean ( 16 / 40 )16948.5298.81456.7194
Winsorized Mean ( 17 / 40 )17011.1288.97458.8674
Winsorized Mean ( 18 / 40 )17044.1281.25560.6003
Winsorized Mean ( 19 / 40 )17102.7272.55962.7487
Winsorized Mean ( 20 / 40 )17127.7268.93363.6878
Winsorized Mean ( 21 / 40 )17178.8261.66565.652
Winsorized Mean ( 22 / 40 )17206.3257.83266.7347
Winsorized Mean ( 23 / 40 )17205254.4867.6085
Winsorized Mean ( 24 / 40 )17235247.05169.7628
Winsorized Mean ( 25 / 40 )17235243.61970.7457
Winsorized Mean ( 26 / 40 )17250.4234.10373.6869
Winsorized Mean ( 27 / 40 )17250.4234.10373.6869
Winsorized Mean ( 28 / 40 )17252230.13374.9654
Winsorized Mean ( 29 / 40 )17320.6216.86279.8693
Winsorized Mean ( 30 / 40 )17377.9205.61684.5162
Winsorized Mean ( 31 / 40 )17357.7199.76786.8899
Winsorized Mean ( 32 / 40 )17357.7199.76786.8899
Winsorized Mean ( 33 / 40 )17337.9197.99187.5691
Winsorized Mean ( 34 / 40 )17545.9172.319101.822
Winsorized Mean ( 35 / 40 )17545.9172.319101.822
Winsorized Mean ( 36 / 40 )17590.6166.995105.336
Winsorized Mean ( 37 / 40 )17544.7162.8107.768
Winsorized Mean ( 38 / 40 )17569.4155.126113.259
Winsorized Mean ( 39 / 40 )17689.9136.328129.76
Winsorized Mean ( 40 / 40 )17810.9122.674145.189
Trimmed Mean ( 1 / 40 )16827336.80849.9602
Trimmed Mean ( 2 / 40 )16868.4330.20651.0845
Trimmed Mean ( 3 / 40 )16904.1324.8352.0398
Trimmed Mean ( 4 / 40 )16946.3319.68253.0099
Trimmed Mean ( 5 / 40 )16988.8314.21854.0669
Trimmed Mean ( 6 / 40 )17032.1308.49455.2104
Trimmed Mean ( 7 / 40 )17063.9305.48255.8589
Trimmed Mean ( 8 / 40 )17097.5302.12656.5908
Trimmed Mean ( 9 / 40 )17131.1298.62157.3675
Trimmed Mean ( 10 / 40 )17163.1295.31358.1182
Trimmed Mean ( 11 / 40 )17196.3291.77958.9361
Trimmed Mean ( 12 / 40 )17228.7288.26759.7664
Trimmed Mean ( 13 / 40 )17263.2284.32260.7172
Trimmed Mean ( 14 / 40 )17298.5279.97161.7867
Trimmed Mean ( 15 / 40 )17332.9275.57962.8961
Trimmed Mean ( 16 / 40 )17369.6270.59764.19
Trimmed Mean ( 17 / 40 )17406.3265.29665.6109
Trimmed Mean ( 18 / 40 )17439.6260.58266.9255
Trimmed Mean ( 19 / 40 )17471.7256.1668.2061
Trimmed Mean ( 20 / 40 )17500.8252.2169.39
Trimmed Mean ( 21 / 40 )17529.5248.06170.6663
Trimmed Mean ( 22 / 40 )17555.9244.18171.8971
Trimmed Mean ( 23 / 40 )17581.7240.1173.2233
Trimmed Mean ( 24 / 40 )17609235.69474.711
Trimmed Mean ( 25 / 40 )17635.7231.45576.195
Trimmed Mean ( 26 / 40 )17664226.8177.8801
Trimmed Mean ( 27 / 40 )17692.9222.53279.5073
Trimmed Mean ( 28 / 40 )17723.6217.30481.5616
Trimmed Mean ( 29 / 40 )17756.2211.49283.9569
Trimmed Mean ( 30 / 40 )17786.3206.53286.1185
Trimmed Mean ( 31 / 40 )17814.4202.22488.0927
Trimmed Mean ( 32 / 40 )17846197.64290.2945
Trimmed Mean ( 33 / 40 )17879.9191.8293.2118
Trimmed Mean ( 34 / 40 )17917.8184.6297.0522
Trimmed Mean ( 35 / 40 )17944.1180.76699.2668
Trimmed Mean ( 36 / 40 )17972.5175.704102.289
Trimmed Mean ( 37 / 40 )18000.2170.249105.729
Trimmed Mean ( 38 / 40 )18033.8163.647110.199
Trimmed Mean ( 39 / 40 )18068.7156.594115.385
Trimmed Mean ( 40 / 40 )18097.8151.972119.087
Median18515.5
Midrange13802.5
Midmean - Weighted Average at Xnp17723.9
Midmean - Weighted Average at X(n+1)p17786.3
Midmean - Empirical Distribution Function17723.9
Midmean - Empirical Distribution Function - Averaging17786.3
Midmean - Empirical Distribution Function - Interpolation17786.3
Midmean - Closest Observation17723.9
Midmean - True Basic - Statistics Graphics Toolkit17786.3
Midmean - MS Excel (old versions)17756.2
Number of observations120



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,'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')