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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, 14 Dec 2016 19:25:56 +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/14/t1481740001wqb2x76ebp47i11.htm/, Retrieved Sat, 04 May 2024 00:05:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299682, Retrieved Sat, 04 May 2024 00:05:59 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact78
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2016-12-14 18:25:56] [219800a2f11ddd28e3280d87dbde8c8d] [Current]
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Dataseries X:
100
101
102
103
99
101
100
101
100
100
101
100
99
99
102
99
101
99
99
99
100
99
99
100
104
100
102
100
99
99
100
101
100
102
98
100
100
101
100
102
99
99
100
99
99
99
100
101
100
101
98
101
101
100
101
99
101
101
99
98
99
102
97
100
100
100
98
101
101
100
100
98
98
101
103
100
101
100
100
101
101
104
101
98
101
100
99
100
104
100
101
100
104
101
100
100
99
100
99
100
100
99
100
99
99
102
101
100
98
101
101
99
102
99
102
101
101
99
103
101
101
100
101
100
99
99
99
100
103
101
98
100
102
100
100
99
101
100
100
100
98
98
102




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=299682&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=299682&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299682&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 Mean100.1890.112698889.005
Geometric Mean100.18
Harmonic Mean100.171
Quadratic Mean100.198
Winsorized Mean ( 1 / 47 )100.1960.111515898.496
Winsorized Mean ( 2 / 47 )100.1960.111515898.496
Winsorized Mean ( 3 / 47 )100.1960.111515898.496
Winsorized Mean ( 4 / 47 )100.1680.105491949.54
Winsorized Mean ( 5 / 47 )100.1680.105491949.54
Winsorized Mean ( 6 / 47 )100.1680.105491949.54
Winsorized Mean ( 7 / 47 )100.1680.105491949.54
Winsorized Mean ( 8 / 47 )100.1120.0962741039.86
Winsorized Mean ( 9 / 47 )100.1120.0962741039.86
Winsorized Mean ( 10 / 47 )100.1120.0962741039.86
Winsorized Mean ( 11 / 47 )100.1120.0962741039.86
Winsorized Mean ( 12 / 47 )100.1960.08552181171.58
Winsorized Mean ( 13 / 47 )100.1960.08552181171.58
Winsorized Mean ( 14 / 47 )100.1960.08552181171.58
Winsorized Mean ( 15 / 47 )100.1960.08552181171.58
Winsorized Mean ( 16 / 47 )100.1960.08552181171.58
Winsorized Mean ( 17 / 47 )100.1960.08552181171.58
Winsorized Mean ( 18 / 47 )100.1960.08552181171.58
Winsorized Mean ( 19 / 47 )100.0630.06891311452.02
Winsorized Mean ( 20 / 47 )100.0630.06891311452.02
Winsorized Mean ( 21 / 47 )100.0630.06891311452.02
Winsorized Mean ( 22 / 47 )100.0630.06891311452.02
Winsorized Mean ( 23 / 47 )100.0630.06891311452.02
Winsorized Mean ( 24 / 47 )100.0630.06891311452.02
Winsorized Mean ( 25 / 47 )100.0630.06891311452.02
Winsorized Mean ( 26 / 47 )100.0630.06891311452.02
Winsorized Mean ( 27 / 47 )100.0630.06891311452.02
Winsorized Mean ( 28 / 47 )100.0630.06891311452.02
Winsorized Mean ( 29 / 47 )100.0630.06891311452.02
Winsorized Mean ( 30 / 47 )100.0630.06891311452.02
Winsorized Mean ( 31 / 47 )100.0630.06891311452.02
Winsorized Mean ( 32 / 47 )100.0630.06891311452.02
Winsorized Mean ( 33 / 47 )100.0630.06891311452.02
Winsorized Mean ( 34 / 47 )100.0630.06891311452.02
Winsorized Mean ( 35 / 47 )100.0630.06891311452.02
Winsorized Mean ( 36 / 47 )100.0630.06891311452.02
Winsorized Mean ( 37 / 47 )100.0630.06891311452.02
Winsorized Mean ( 38 / 47 )100.0630.06891311452.02
Winsorized Mean ( 39 / 47 )100.0630.06891311452.02
Winsorized Mean ( 40 / 47 )100.0630.06891311452.02
Winsorized Mean ( 41 / 47 )100.0630.06891311452.02
Winsorized Mean ( 42 / 47 )100.0630.06891311452.02
Winsorized Mean ( 43 / 47 )100.0630.06891311452.02
Winsorized Mean ( 44 / 47 )100.3710.04053022476.44
Winsorized Mean ( 45 / 47 )100.3710.04053022476.44
Winsorized Mean ( 46 / 47 )100.3710.04053022476.44
Winsorized Mean ( 47 / 47 )100.3710.04053022476.44
Trimmed Mean ( 1 / 47 )100.1840.108692921.731
Trimmed Mean ( 2 / 47 )100.1730.105588948.714
Trimmed Mean ( 3 / 47 )100.1610.102163980.4
Trimmed Mean ( 4 / 47 )100.1480.09836621018.12
Trimmed Mean ( 5 / 47 )100.1430.09614511041.58
Trimmed Mean ( 6 / 47 )100.1370.09370271068.67
Trimmed Mean ( 7 / 47 )100.1320.09100791100.25
Trimmed Mean ( 8 / 47 )100.1260.0880231137.5
Trimmed Mean ( 9 / 47 )100.1280.08649151157.66
Trimmed Mean ( 10 / 47 )100.130.08480391180.72
Trimmed Mean ( 11 / 47 )100.1320.08294021207.28
Trimmed Mean ( 12 / 47 )100.1340.08087651238.12
Trimmed Mean ( 13 / 47 )100.1280.08009951250.05
Trimmed Mean ( 14 / 47 )100.1220.07922951263.69
Trimmed Mean ( 15 / 47 )100.1150.07825551279.34
Trimmed Mean ( 16 / 47 )100.1080.07716451297.33
Trimmed Mean ( 17 / 47 )100.1010.07594121318.14
Trimmed Mean ( 18 / 47 )100.0930.07456771342.32
Trimmed Mean ( 19 / 47 )100.0860.07302251370.61
Trimmed Mean ( 20 / 47 )100.0870.07314791368.29
Trimmed Mean ( 21 / 47 )100.0890.07325391366.33
Trimmed Mean ( 22 / 47 )100.0910.0733381364.79
Trimmed Mean ( 23 / 47 )100.0930.07339711363.72
Trimmed Mean ( 24 / 47 )100.0950.07342781363.17
Trimmed Mean ( 25 / 47 )100.0970.07342631363.23
Trimmed Mean ( 26 / 47 )100.0990.07338821363.97
Trimmed Mean ( 27 / 47 )100.1010.07330821365.48
Trimmed Mean ( 28 / 47 )100.1030.07318051367.9
Trimmed Mean ( 29 / 47 )100.1060.07299811371.35
Trimmed Mean ( 30 / 47 )100.1080.07275291376.01
Trimmed Mean ( 31 / 47 )100.1080.07243561382.03
Trimmed Mean ( 32 / 47 )100.1140.07203481389.8
Trimmed Mean ( 33 / 47 )100.1170.07153721399.51
Trimmed Mean ( 34 / 47 )100.120.07092691411.59
Trimmed Mean ( 35 / 47 )100.1230.07018461426.57
Trimmed Mean ( 36 / 47 )100.1270.06928661445.11
Trimmed Mean ( 37 / 47 )100.130.06820391468.11
Trimmed Mean ( 38 / 47 )100.1340.06689981496.78
Trimmed Mean ( 39 / 47 )100.1380.0653281532.86
Trimmed Mean ( 40 / 47 )100.1430.0634281578.84
Trimmed Mean ( 41 / 47 )100.1480.06111921638.56
Trimmed Mean ( 42 / 47 )100.1530.05829031718.17
Trimmed Mean ( 43 / 47 )100.1580.05478071828.34
Trimmed Mean ( 44 / 47 )100.1640.05034321989.62
Trimmed Mean ( 45 / 47 )100.1510.04964482017.35
Trimmed Mean ( 46 / 47 )100.1370.04866542057.67
Trimmed Mean ( 47 / 47 )100.1370.04731442116.42
Median100
Midrange100.5
Midmean - Weighted Average at Xnp100.018
Midmean - Weighted Average at X(n+1)p100.018
Midmean - Empirical Distribution Function100.018
Midmean - Empirical Distribution Function - Averaging100.018
Midmean - Empirical Distribution Function - Interpolation100.018
Midmean - Closest Observation100.018
Midmean - True Basic - Statistics Graphics Toolkit100.018
Midmean - MS Excel (old versions)100.018
Number of observations143

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 100.189 & 0.112698 & 889.005 \tabularnewline
Geometric Mean & 100.18 &  &  \tabularnewline
Harmonic Mean & 100.171 &  &  \tabularnewline
Quadratic Mean & 100.198 &  &  \tabularnewline
Winsorized Mean ( 1 / 47 ) & 100.196 & 0.111515 & 898.496 \tabularnewline
Winsorized Mean ( 2 / 47 ) & 100.196 & 0.111515 & 898.496 \tabularnewline
Winsorized Mean ( 3 / 47 ) & 100.196 & 0.111515 & 898.496 \tabularnewline
Winsorized Mean ( 4 / 47 ) & 100.168 & 0.105491 & 949.54 \tabularnewline
Winsorized Mean ( 5 / 47 ) & 100.168 & 0.105491 & 949.54 \tabularnewline
Winsorized Mean ( 6 / 47 ) & 100.168 & 0.105491 & 949.54 \tabularnewline
Winsorized Mean ( 7 / 47 ) & 100.168 & 0.105491 & 949.54 \tabularnewline
Winsorized Mean ( 8 / 47 ) & 100.112 & 0.096274 & 1039.86 \tabularnewline
Winsorized Mean ( 9 / 47 ) & 100.112 & 0.096274 & 1039.86 \tabularnewline
Winsorized Mean ( 10 / 47 ) & 100.112 & 0.096274 & 1039.86 \tabularnewline
Winsorized Mean ( 11 / 47 ) & 100.112 & 0.096274 & 1039.86 \tabularnewline
Winsorized Mean ( 12 / 47 ) & 100.196 & 0.0855218 & 1171.58 \tabularnewline
Winsorized Mean ( 13 / 47 ) & 100.196 & 0.0855218 & 1171.58 \tabularnewline
Winsorized Mean ( 14 / 47 ) & 100.196 & 0.0855218 & 1171.58 \tabularnewline
Winsorized Mean ( 15 / 47 ) & 100.196 & 0.0855218 & 1171.58 \tabularnewline
Winsorized Mean ( 16 / 47 ) & 100.196 & 0.0855218 & 1171.58 \tabularnewline
Winsorized Mean ( 17 / 47 ) & 100.196 & 0.0855218 & 1171.58 \tabularnewline
Winsorized Mean ( 18 / 47 ) & 100.196 & 0.0855218 & 1171.58 \tabularnewline
Winsorized Mean ( 19 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 20 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 21 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 22 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 23 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 24 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 25 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 26 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 27 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 28 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 29 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 30 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 31 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 32 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 33 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 34 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 35 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 36 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 37 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 38 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 39 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 40 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 41 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 42 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 43 / 47 ) & 100.063 & 0.0689131 & 1452.02 \tabularnewline
Winsorized Mean ( 44 / 47 ) & 100.371 & 0.0405302 & 2476.44 \tabularnewline
Winsorized Mean ( 45 / 47 ) & 100.371 & 0.0405302 & 2476.44 \tabularnewline
Winsorized Mean ( 46 / 47 ) & 100.371 & 0.0405302 & 2476.44 \tabularnewline
Winsorized Mean ( 47 / 47 ) & 100.371 & 0.0405302 & 2476.44 \tabularnewline
Trimmed Mean ( 1 / 47 ) & 100.184 & 0.108692 & 921.731 \tabularnewline
Trimmed Mean ( 2 / 47 ) & 100.173 & 0.105588 & 948.714 \tabularnewline
Trimmed Mean ( 3 / 47 ) & 100.161 & 0.102163 & 980.4 \tabularnewline
Trimmed Mean ( 4 / 47 ) & 100.148 & 0.0983662 & 1018.12 \tabularnewline
Trimmed Mean ( 5 / 47 ) & 100.143 & 0.0961451 & 1041.58 \tabularnewline
Trimmed Mean ( 6 / 47 ) & 100.137 & 0.0937027 & 1068.67 \tabularnewline
Trimmed Mean ( 7 / 47 ) & 100.132 & 0.0910079 & 1100.25 \tabularnewline
Trimmed Mean ( 8 / 47 ) & 100.126 & 0.088023 & 1137.5 \tabularnewline
Trimmed Mean ( 9 / 47 ) & 100.128 & 0.0864915 & 1157.66 \tabularnewline
Trimmed Mean ( 10 / 47 ) & 100.13 & 0.0848039 & 1180.72 \tabularnewline
Trimmed Mean ( 11 / 47 ) & 100.132 & 0.0829402 & 1207.28 \tabularnewline
Trimmed Mean ( 12 / 47 ) & 100.134 & 0.0808765 & 1238.12 \tabularnewline
Trimmed Mean ( 13 / 47 ) & 100.128 & 0.0800995 & 1250.05 \tabularnewline
Trimmed Mean ( 14 / 47 ) & 100.122 & 0.0792295 & 1263.69 \tabularnewline
Trimmed Mean ( 15 / 47 ) & 100.115 & 0.0782555 & 1279.34 \tabularnewline
Trimmed Mean ( 16 / 47 ) & 100.108 & 0.0771645 & 1297.33 \tabularnewline
Trimmed Mean ( 17 / 47 ) & 100.101 & 0.0759412 & 1318.14 \tabularnewline
Trimmed Mean ( 18 / 47 ) & 100.093 & 0.0745677 & 1342.32 \tabularnewline
Trimmed Mean ( 19 / 47 ) & 100.086 & 0.0730225 & 1370.61 \tabularnewline
Trimmed Mean ( 20 / 47 ) & 100.087 & 0.0731479 & 1368.29 \tabularnewline
Trimmed Mean ( 21 / 47 ) & 100.089 & 0.0732539 & 1366.33 \tabularnewline
Trimmed Mean ( 22 / 47 ) & 100.091 & 0.073338 & 1364.79 \tabularnewline
Trimmed Mean ( 23 / 47 ) & 100.093 & 0.0733971 & 1363.72 \tabularnewline
Trimmed Mean ( 24 / 47 ) & 100.095 & 0.0734278 & 1363.17 \tabularnewline
Trimmed Mean ( 25 / 47 ) & 100.097 & 0.0734263 & 1363.23 \tabularnewline
Trimmed Mean ( 26 / 47 ) & 100.099 & 0.0733882 & 1363.97 \tabularnewline
Trimmed Mean ( 27 / 47 ) & 100.101 & 0.0733082 & 1365.48 \tabularnewline
Trimmed Mean ( 28 / 47 ) & 100.103 & 0.0731805 & 1367.9 \tabularnewline
Trimmed Mean ( 29 / 47 ) & 100.106 & 0.0729981 & 1371.35 \tabularnewline
Trimmed Mean ( 30 / 47 ) & 100.108 & 0.0727529 & 1376.01 \tabularnewline
Trimmed Mean ( 31 / 47 ) & 100.108 & 0.0724356 & 1382.03 \tabularnewline
Trimmed Mean ( 32 / 47 ) & 100.114 & 0.0720348 & 1389.8 \tabularnewline
Trimmed Mean ( 33 / 47 ) & 100.117 & 0.0715372 & 1399.51 \tabularnewline
Trimmed Mean ( 34 / 47 ) & 100.12 & 0.0709269 & 1411.59 \tabularnewline
Trimmed Mean ( 35 / 47 ) & 100.123 & 0.0701846 & 1426.57 \tabularnewline
Trimmed Mean ( 36 / 47 ) & 100.127 & 0.0692866 & 1445.11 \tabularnewline
Trimmed Mean ( 37 / 47 ) & 100.13 & 0.0682039 & 1468.11 \tabularnewline
Trimmed Mean ( 38 / 47 ) & 100.134 & 0.0668998 & 1496.78 \tabularnewline
Trimmed Mean ( 39 / 47 ) & 100.138 & 0.065328 & 1532.86 \tabularnewline
Trimmed Mean ( 40 / 47 ) & 100.143 & 0.063428 & 1578.84 \tabularnewline
Trimmed Mean ( 41 / 47 ) & 100.148 & 0.0611192 & 1638.56 \tabularnewline
Trimmed Mean ( 42 / 47 ) & 100.153 & 0.0582903 & 1718.17 \tabularnewline
Trimmed Mean ( 43 / 47 ) & 100.158 & 0.0547807 & 1828.34 \tabularnewline
Trimmed Mean ( 44 / 47 ) & 100.164 & 0.0503432 & 1989.62 \tabularnewline
Trimmed Mean ( 45 / 47 ) & 100.151 & 0.0496448 & 2017.35 \tabularnewline
Trimmed Mean ( 46 / 47 ) & 100.137 & 0.0486654 & 2057.67 \tabularnewline
Trimmed Mean ( 47 / 47 ) & 100.137 & 0.0473144 & 2116.42 \tabularnewline
Median & 100 &  &  \tabularnewline
Midrange & 100.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 100.018 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 100.018 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 100.018 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 100.018 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 100.018 &  &  \tabularnewline
Midmean - Closest Observation & 100.018 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 100.018 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 100.018 &  &  \tabularnewline
Number of observations & 143 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299682&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]100.189[/C][C]0.112698[/C][C]889.005[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]100.18[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]100.171[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]100.198[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 47 )[/C][C]100.196[/C][C]0.111515[/C][C]898.496[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 47 )[/C][C]100.196[/C][C]0.111515[/C][C]898.496[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 47 )[/C][C]100.196[/C][C]0.111515[/C][C]898.496[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 47 )[/C][C]100.168[/C][C]0.105491[/C][C]949.54[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 47 )[/C][C]100.168[/C][C]0.105491[/C][C]949.54[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 47 )[/C][C]100.168[/C][C]0.105491[/C][C]949.54[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 47 )[/C][C]100.168[/C][C]0.105491[/C][C]949.54[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 47 )[/C][C]100.112[/C][C]0.096274[/C][C]1039.86[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 47 )[/C][C]100.112[/C][C]0.096274[/C][C]1039.86[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 47 )[/C][C]100.112[/C][C]0.096274[/C][C]1039.86[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 47 )[/C][C]100.112[/C][C]0.096274[/C][C]1039.86[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 47 )[/C][C]100.196[/C][C]0.0855218[/C][C]1171.58[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 47 )[/C][C]100.196[/C][C]0.0855218[/C][C]1171.58[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 47 )[/C][C]100.196[/C][C]0.0855218[/C][C]1171.58[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 47 )[/C][C]100.196[/C][C]0.0855218[/C][C]1171.58[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 47 )[/C][C]100.196[/C][C]0.0855218[/C][C]1171.58[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 47 )[/C][C]100.196[/C][C]0.0855218[/C][C]1171.58[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 47 )[/C][C]100.196[/C][C]0.0855218[/C][C]1171.58[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 39 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 40 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 41 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 42 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 43 / 47 )[/C][C]100.063[/C][C]0.0689131[/C][C]1452.02[/C][/ROW]
[ROW][C]Winsorized Mean ( 44 / 47 )[/C][C]100.371[/C][C]0.0405302[/C][C]2476.44[/C][/ROW]
[ROW][C]Winsorized Mean ( 45 / 47 )[/C][C]100.371[/C][C]0.0405302[/C][C]2476.44[/C][/ROW]
[ROW][C]Winsorized Mean ( 46 / 47 )[/C][C]100.371[/C][C]0.0405302[/C][C]2476.44[/C][/ROW]
[ROW][C]Winsorized Mean ( 47 / 47 )[/C][C]100.371[/C][C]0.0405302[/C][C]2476.44[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 47 )[/C][C]100.184[/C][C]0.108692[/C][C]921.731[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 47 )[/C][C]100.173[/C][C]0.105588[/C][C]948.714[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 47 )[/C][C]100.161[/C][C]0.102163[/C][C]980.4[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 47 )[/C][C]100.148[/C][C]0.0983662[/C][C]1018.12[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 47 )[/C][C]100.143[/C][C]0.0961451[/C][C]1041.58[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 47 )[/C][C]100.137[/C][C]0.0937027[/C][C]1068.67[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 47 )[/C][C]100.132[/C][C]0.0910079[/C][C]1100.25[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 47 )[/C][C]100.126[/C][C]0.088023[/C][C]1137.5[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 47 )[/C][C]100.128[/C][C]0.0864915[/C][C]1157.66[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 47 )[/C][C]100.13[/C][C]0.0848039[/C][C]1180.72[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 47 )[/C][C]100.132[/C][C]0.0829402[/C][C]1207.28[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 47 )[/C][C]100.134[/C][C]0.0808765[/C][C]1238.12[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 47 )[/C][C]100.128[/C][C]0.0800995[/C][C]1250.05[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 47 )[/C][C]100.122[/C][C]0.0792295[/C][C]1263.69[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 47 )[/C][C]100.115[/C][C]0.0782555[/C][C]1279.34[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 47 )[/C][C]100.108[/C][C]0.0771645[/C][C]1297.33[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 47 )[/C][C]100.101[/C][C]0.0759412[/C][C]1318.14[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 47 )[/C][C]100.093[/C][C]0.0745677[/C][C]1342.32[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 47 )[/C][C]100.086[/C][C]0.0730225[/C][C]1370.61[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 47 )[/C][C]100.087[/C][C]0.0731479[/C][C]1368.29[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 47 )[/C][C]100.089[/C][C]0.0732539[/C][C]1366.33[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 47 )[/C][C]100.091[/C][C]0.073338[/C][C]1364.79[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 47 )[/C][C]100.093[/C][C]0.0733971[/C][C]1363.72[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 47 )[/C][C]100.095[/C][C]0.0734278[/C][C]1363.17[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 47 )[/C][C]100.097[/C][C]0.0734263[/C][C]1363.23[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 47 )[/C][C]100.099[/C][C]0.0733882[/C][C]1363.97[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 47 )[/C][C]100.101[/C][C]0.0733082[/C][C]1365.48[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 47 )[/C][C]100.103[/C][C]0.0731805[/C][C]1367.9[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 47 )[/C][C]100.106[/C][C]0.0729981[/C][C]1371.35[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 47 )[/C][C]100.108[/C][C]0.0727529[/C][C]1376.01[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 47 )[/C][C]100.108[/C][C]0.0724356[/C][C]1382.03[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 47 )[/C][C]100.114[/C][C]0.0720348[/C][C]1389.8[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 47 )[/C][C]100.117[/C][C]0.0715372[/C][C]1399.51[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 47 )[/C][C]100.12[/C][C]0.0709269[/C][C]1411.59[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 47 )[/C][C]100.123[/C][C]0.0701846[/C][C]1426.57[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 47 )[/C][C]100.127[/C][C]0.0692866[/C][C]1445.11[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 47 )[/C][C]100.13[/C][C]0.0682039[/C][C]1468.11[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 47 )[/C][C]100.134[/C][C]0.0668998[/C][C]1496.78[/C][/ROW]
[ROW][C]Trimmed Mean ( 39 / 47 )[/C][C]100.138[/C][C]0.065328[/C][C]1532.86[/C][/ROW]
[ROW][C]Trimmed Mean ( 40 / 47 )[/C][C]100.143[/C][C]0.063428[/C][C]1578.84[/C][/ROW]
[ROW][C]Trimmed Mean ( 41 / 47 )[/C][C]100.148[/C][C]0.0611192[/C][C]1638.56[/C][/ROW]
[ROW][C]Trimmed Mean ( 42 / 47 )[/C][C]100.153[/C][C]0.0582903[/C][C]1718.17[/C][/ROW]
[ROW][C]Trimmed Mean ( 43 / 47 )[/C][C]100.158[/C][C]0.0547807[/C][C]1828.34[/C][/ROW]
[ROW][C]Trimmed Mean ( 44 / 47 )[/C][C]100.164[/C][C]0.0503432[/C][C]1989.62[/C][/ROW]
[ROW][C]Trimmed Mean ( 45 / 47 )[/C][C]100.151[/C][C]0.0496448[/C][C]2017.35[/C][/ROW]
[ROW][C]Trimmed Mean ( 46 / 47 )[/C][C]100.137[/C][C]0.0486654[/C][C]2057.67[/C][/ROW]
[ROW][C]Trimmed Mean ( 47 / 47 )[/C][C]100.137[/C][C]0.0473144[/C][C]2116.42[/C][/ROW]
[ROW][C]Median[/C][C]100[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]100.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]100.018[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]100.018[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]100.018[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]100.018[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]100.018[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]100.018[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]100.018[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]100.018[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]143[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299682&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299682&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 Mean100.1890.112698889.005
Geometric Mean100.18
Harmonic Mean100.171
Quadratic Mean100.198
Winsorized Mean ( 1 / 47 )100.1960.111515898.496
Winsorized Mean ( 2 / 47 )100.1960.111515898.496
Winsorized Mean ( 3 / 47 )100.1960.111515898.496
Winsorized Mean ( 4 / 47 )100.1680.105491949.54
Winsorized Mean ( 5 / 47 )100.1680.105491949.54
Winsorized Mean ( 6 / 47 )100.1680.105491949.54
Winsorized Mean ( 7 / 47 )100.1680.105491949.54
Winsorized Mean ( 8 / 47 )100.1120.0962741039.86
Winsorized Mean ( 9 / 47 )100.1120.0962741039.86
Winsorized Mean ( 10 / 47 )100.1120.0962741039.86
Winsorized Mean ( 11 / 47 )100.1120.0962741039.86
Winsorized Mean ( 12 / 47 )100.1960.08552181171.58
Winsorized Mean ( 13 / 47 )100.1960.08552181171.58
Winsorized Mean ( 14 / 47 )100.1960.08552181171.58
Winsorized Mean ( 15 / 47 )100.1960.08552181171.58
Winsorized Mean ( 16 / 47 )100.1960.08552181171.58
Winsorized Mean ( 17 / 47 )100.1960.08552181171.58
Winsorized Mean ( 18 / 47 )100.1960.08552181171.58
Winsorized Mean ( 19 / 47 )100.0630.06891311452.02
Winsorized Mean ( 20 / 47 )100.0630.06891311452.02
Winsorized Mean ( 21 / 47 )100.0630.06891311452.02
Winsorized Mean ( 22 / 47 )100.0630.06891311452.02
Winsorized Mean ( 23 / 47 )100.0630.06891311452.02
Winsorized Mean ( 24 / 47 )100.0630.06891311452.02
Winsorized Mean ( 25 / 47 )100.0630.06891311452.02
Winsorized Mean ( 26 / 47 )100.0630.06891311452.02
Winsorized Mean ( 27 / 47 )100.0630.06891311452.02
Winsorized Mean ( 28 / 47 )100.0630.06891311452.02
Winsorized Mean ( 29 / 47 )100.0630.06891311452.02
Winsorized Mean ( 30 / 47 )100.0630.06891311452.02
Winsorized Mean ( 31 / 47 )100.0630.06891311452.02
Winsorized Mean ( 32 / 47 )100.0630.06891311452.02
Winsorized Mean ( 33 / 47 )100.0630.06891311452.02
Winsorized Mean ( 34 / 47 )100.0630.06891311452.02
Winsorized Mean ( 35 / 47 )100.0630.06891311452.02
Winsorized Mean ( 36 / 47 )100.0630.06891311452.02
Winsorized Mean ( 37 / 47 )100.0630.06891311452.02
Winsorized Mean ( 38 / 47 )100.0630.06891311452.02
Winsorized Mean ( 39 / 47 )100.0630.06891311452.02
Winsorized Mean ( 40 / 47 )100.0630.06891311452.02
Winsorized Mean ( 41 / 47 )100.0630.06891311452.02
Winsorized Mean ( 42 / 47 )100.0630.06891311452.02
Winsorized Mean ( 43 / 47 )100.0630.06891311452.02
Winsorized Mean ( 44 / 47 )100.3710.04053022476.44
Winsorized Mean ( 45 / 47 )100.3710.04053022476.44
Winsorized Mean ( 46 / 47 )100.3710.04053022476.44
Winsorized Mean ( 47 / 47 )100.3710.04053022476.44
Trimmed Mean ( 1 / 47 )100.1840.108692921.731
Trimmed Mean ( 2 / 47 )100.1730.105588948.714
Trimmed Mean ( 3 / 47 )100.1610.102163980.4
Trimmed Mean ( 4 / 47 )100.1480.09836621018.12
Trimmed Mean ( 5 / 47 )100.1430.09614511041.58
Trimmed Mean ( 6 / 47 )100.1370.09370271068.67
Trimmed Mean ( 7 / 47 )100.1320.09100791100.25
Trimmed Mean ( 8 / 47 )100.1260.0880231137.5
Trimmed Mean ( 9 / 47 )100.1280.08649151157.66
Trimmed Mean ( 10 / 47 )100.130.08480391180.72
Trimmed Mean ( 11 / 47 )100.1320.08294021207.28
Trimmed Mean ( 12 / 47 )100.1340.08087651238.12
Trimmed Mean ( 13 / 47 )100.1280.08009951250.05
Trimmed Mean ( 14 / 47 )100.1220.07922951263.69
Trimmed Mean ( 15 / 47 )100.1150.07825551279.34
Trimmed Mean ( 16 / 47 )100.1080.07716451297.33
Trimmed Mean ( 17 / 47 )100.1010.07594121318.14
Trimmed Mean ( 18 / 47 )100.0930.07456771342.32
Trimmed Mean ( 19 / 47 )100.0860.07302251370.61
Trimmed Mean ( 20 / 47 )100.0870.07314791368.29
Trimmed Mean ( 21 / 47 )100.0890.07325391366.33
Trimmed Mean ( 22 / 47 )100.0910.0733381364.79
Trimmed Mean ( 23 / 47 )100.0930.07339711363.72
Trimmed Mean ( 24 / 47 )100.0950.07342781363.17
Trimmed Mean ( 25 / 47 )100.0970.07342631363.23
Trimmed Mean ( 26 / 47 )100.0990.07338821363.97
Trimmed Mean ( 27 / 47 )100.1010.07330821365.48
Trimmed Mean ( 28 / 47 )100.1030.07318051367.9
Trimmed Mean ( 29 / 47 )100.1060.07299811371.35
Trimmed Mean ( 30 / 47 )100.1080.07275291376.01
Trimmed Mean ( 31 / 47 )100.1080.07243561382.03
Trimmed Mean ( 32 / 47 )100.1140.07203481389.8
Trimmed Mean ( 33 / 47 )100.1170.07153721399.51
Trimmed Mean ( 34 / 47 )100.120.07092691411.59
Trimmed Mean ( 35 / 47 )100.1230.07018461426.57
Trimmed Mean ( 36 / 47 )100.1270.06928661445.11
Trimmed Mean ( 37 / 47 )100.130.06820391468.11
Trimmed Mean ( 38 / 47 )100.1340.06689981496.78
Trimmed Mean ( 39 / 47 )100.1380.0653281532.86
Trimmed Mean ( 40 / 47 )100.1430.0634281578.84
Trimmed Mean ( 41 / 47 )100.1480.06111921638.56
Trimmed Mean ( 42 / 47 )100.1530.05829031718.17
Trimmed Mean ( 43 / 47 )100.1580.05478071828.34
Trimmed Mean ( 44 / 47 )100.1640.05034321989.62
Trimmed Mean ( 45 / 47 )100.1510.04964482017.35
Trimmed Mean ( 46 / 47 )100.1370.04866542057.67
Trimmed Mean ( 47 / 47 )100.1370.04731442116.42
Median100
Midrange100.5
Midmean - Weighted Average at Xnp100.018
Midmean - Weighted Average at X(n+1)p100.018
Midmean - Empirical Distribution Function100.018
Midmean - Empirical Distribution Function - Averaging100.018
Midmean - Empirical Distribution Function - Interpolation100.018
Midmean - Closest Observation100.018
Midmean - True Basic - Statistics Graphics Toolkit100.018
Midmean - MS Excel (old versions)100.018
Number of observations143



Parameters (Session):
par1 = 200 ; par2 = 5 ; par3 = 0 ; par4 = P1 P5 Q1 Q3 P95 P99 ;
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')