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R Software Module

rwasp_centraltendency.wasp

Title produced by software

Central Tendency

Date of computation

Wed, 14 Dec 2016 19:25:56 +0100

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Statistical 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 Fri, 01 Nov 2024 03:42:15 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299682, Retrieved Fri, 01 Nov 2024 03:42:15 +0000

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Estimated Impact

103

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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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big 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 Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center

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

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

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code