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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationWed, 14 Aug 2013 09:38:59 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Aug/14/t1376487563zhnwhqi8nnkdlb1.htm/, Retrieved Sun, 05 May 2024 07:35:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=211095, Retrieved Sun, 05 May 2024 07:35:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact182
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [Stap 2/2] [2013-08-14 13:02:24] [1cfd0014ba435dd2b8f9632cac0a7144]
- RMP   [Harrell-Davis Quantiles] [Stap 6 / 2] [2013-08-14 13:20:36] [9b490dd2ab715f1b5bf65aa31d98df3d]
- RMP       [Central Tendency] [Stap 9/2] [2013-08-14 13:38:59] [38a0db91cd47487c7649642dcb33e029] [Current]
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Dataseries X:
10320
11400
9360
10080
10080
10800
10320
9720
10440
11160
9480
11160
9840
11160
8760
10320
9600
10680
10200
10680
10200
12480
8880
11280
9480
11040
9240
9360
9240
10680
10680
10320
9960
12240
8880
11280
9360
10320
9840
9120
9360
10800
9840
11760
9960
11160
9240
11520
9000
10200
10200
9840
8760
11520
9120
11280
10560
10680
9960
10200
10200
10320
9600
10080
9120
10920
7800
11880
9360
10920
9840
9360
10680
9720
9960
10680
9120
10320
8040
11280
8880
11040
9600
9600
11040
9720
9480
10200
9360
10800
8520
11520
9120
11040
8880
9600
10440
8880
8520
10800
8880
10560
8400
12480
10560
10800
9840
8880




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211095&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211095&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211095&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean10102.222222222291.8097470463004110.034310595885
Geometric Mean10057.5423458977
Harmonic Mean10012.7880322178
Quadratic Mean10146.7630306418
Winsorized Mean ( 1 / 36 )10104.444444444491.3145160040006110.655401645033
Winsorized Mean ( 2 / 36 )10106.666666666788.9724425582839113.593224779077
Winsorized Mean ( 3 / 36 )1010086.301651652107117.031363903838
Winsorized Mean ( 4 / 36 )10095.555555555685.4687291209576118.119874477928
Winsorized Mean ( 5 / 36 )10095.555555555681.7425880312709123.504231988513
Winsorized Mean ( 6 / 36 )10095.555555555681.7425880312709123.504231988513
Winsorized Mean ( 7 / 36 )10103.333333333380.5968132968253125.356486442266
Winsorized Mean ( 8 / 36 )10094.444444444479.181444577248127.484974520722
Winsorized Mean ( 9 / 36 )10084.444444444477.691392466391129.801309055015
Winsorized Mean ( 10 / 36 )10084.444444444477.691392466391129.801309055015
Winsorized Mean ( 11 / 36 )10084.444444444477.691392466391129.801309055015
Winsorized Mean ( 12 / 36 )10084.444444444477.691392466391129.801309055015
Winsorized Mean ( 13 / 36 )1007075.679682413565133.060812081249
Winsorized Mean ( 14 / 36 )10085.555555555673.4615292840973137.290302200921
Winsorized Mean ( 15 / 36 )10102.222222222271.2356127140722141.814211141425
Winsorized Mean ( 16 / 36 )10102.222222222271.2356127140722141.814211141425
Winsorized Mean ( 17 / 36 )10083.333333333368.6942448324813146.785707564334
Winsorized Mean ( 18 / 36 )10083.333333333368.6942448324813146.785707564334
Winsorized Mean ( 19 / 36 )10083.333333333368.6942448324813146.785707564334
Winsorized Mean ( 20 / 36 )10105.555555555665.8716003157985153.412935272682
Winsorized Mean ( 21 / 36 )10082.222222222262.8697210349052160.366899299976
Winsorized Mean ( 22 / 36 )10082.222222222262.8697210349052160.366899299976
Winsorized Mean ( 23 / 36 )10082.222222222256.6341812286798178.023624664261
Winsorized Mean ( 24 / 36 )10082.222222222256.6341812286798178.023624664261
Winsorized Mean ( 25 / 36 )10082.222222222256.6341812286798178.023624664261
Winsorized Mean ( 26 / 36 )10082.222222222256.6341812286798178.023624664261
Winsorized Mean ( 27 / 36 )10082.222222222256.6341812286798178.023624664261
Winsorized Mean ( 28 / 36 )10051.111111111153.0648312203998189.411911428961
Winsorized Mean ( 29 / 36 )10051.111111111153.0648312203998189.411911428961
Winsorized Mean ( 30 / 36 )10084.444444444449.1149310383893205.323396190096
Winsorized Mean ( 31 / 36 )10084.444444444449.1149310383893205.323396190096
Winsorized Mean ( 32 / 36 )10084.444444444449.1149310383893205.323396190096
Winsorized Mean ( 33 / 36 )10121.111111111145.0174638881508224.826328205821
Winsorized Mean ( 34 / 36 )10121.111111111145.0174638881508224.826328205821
Winsorized Mean ( 35 / 36 )10082.222222222240.6177065414709248.222341454169
Winsorized Mean ( 36 / 36 )10082.222222222240.6177065414709248.222341454169
Trimmed Mean ( 1 / 36 )10101.509433962388.1331583062968114.616446614288
Trimmed Mean ( 2 / 36 )10098.461538461584.5316987212486119.463605857043
Trimmed Mean ( 3 / 36 )10094.117647058881.881670111426123.276890094237
Trimmed Mean ( 4 / 36 )1009280.0272680800965126.107016297236
Trimmed Mean ( 5 / 36 )10091.020408163378.2122584381514129.020956684725
Trimmed Mean ( 6 / 36 )1009077.1874001171312130.720816929816
Trimmed Mean ( 7 / 36 )10088.936170212876.0212959009062132.71197301561
Trimmed Mean ( 8 / 36 )10086.521739130474.9359393213527134.6019257312
Trimmed Mean ( 9 / 36 )10085.333333333373.9732380666307136.337594472329
Trimmed Mean ( 10 / 36 )10085.454545454573.1359988184273137.900004216712
Trimmed Mean ( 11 / 36 )10085.581395348872.166892123558139.753578110045
Trimmed Mean ( 12 / 36 )10085.714285714371.0454440948113141.961450367665
Trimmed Mean ( 13 / 36 )10085.853658536669.7468108359513144.606664271132
Trimmed Mean ( 14 / 36 )10087.568.5550457938544147.144530109909
Trimmed Mean ( 15 / 36 )10087.692307692367.5061011726735149.43378646456
Trimmed Mean ( 16 / 36 )10086.315789473766.6008909126605151.444157146497
Trimmed Mean ( 17 / 36 )10084.864864864965.5292703585386153.898628959033
Trimmed Mean ( 18 / 36 )1008564.6305862270824156.040670350195
Trimmed Mean ( 19 / 36 )10085.142857142963.556024374171158.681147168189
Trimmed Mean ( 20 / 36 )10085.294117647162.2713448912657161.957223426881
Trimmed Mean ( 21 / 36 )10083.636363636461.1481583236159164.904988802287
Trimmed Mean ( 22 / 36 )10083.7560.2357718825426167.404678065102
Trimmed Mean ( 23 / 36 )10083.870967741959.1189297073846170.569240980057
Trimmed Mean ( 24 / 36 )1008458.6607598464486171.903671660511
Trimmed Mean ( 25 / 36 )10084.137931034558.0605241934343173.683205088507
Trimmed Mean ( 26 / 36 )10084.285714285757.2865077510874176.032474489498
Trimmed Mean ( 27 / 36 )10084.444444444456.2977674602728179.126897910484
Trimmed Mean ( 28 / 36 )10084.615384615455.0404085334404183.222030019787
Trimmed Mean ( 29 / 36 )10087.254.0378098923262186.669297295716
Trimmed Mean ( 30 / 36 )1009052.733775361051191.338471992894
Trimmed Mean ( 31 / 36 )10090.434782608751.7957308237754194.812094010979
Trimmed Mean ( 32 / 36 )10090.909090909150.5423212255284199.652664266877
Trimmed Mean ( 33 / 36 )10091.428571428648.8717911084944206.487798841377
Trimmed Mean ( 34 / 36 )1008947.5337936468523212.248996470916
Trimmed Mean ( 35 / 36 )10086.315789473745.6974107614776220.71963425062
Trimmed Mean ( 36 / 36 )10086.666666666744.3220537029191227.576698820758
Median10140
Midrange10140
Midmean - Weighted Average at Xnp10083.8709677419
Midmean - Weighted Average at X(n+1)p10083.8709677419
Midmean - Empirical Distribution Function10083.8709677419
Midmean - Empirical Distribution Function - Averaging10083.8709677419
Midmean - Empirical Distribution Function - Interpolation10083.8709677419
Midmean - Closest Observation10083.8709677419
Midmean - True Basic - Statistics Graphics Toolkit10083.8709677419
Midmean - MS Excel (old versions)10083.8709677419
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 10102.2222222222 & 91.8097470463004 & 110.034310595885 \tabularnewline
Geometric Mean & 10057.5423458977 &  &  \tabularnewline
Harmonic Mean & 10012.7880322178 &  &  \tabularnewline
Quadratic Mean & 10146.7630306418 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 10104.4444444444 & 91.3145160040006 & 110.655401645033 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 10106.6666666667 & 88.9724425582839 & 113.593224779077 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 10100 & 86.301651652107 & 117.031363903838 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 10095.5555555556 & 85.4687291209576 & 118.119874477928 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 10095.5555555556 & 81.7425880312709 & 123.504231988513 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 10095.5555555556 & 81.7425880312709 & 123.504231988513 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 10103.3333333333 & 80.5968132968253 & 125.356486442266 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 10094.4444444444 & 79.181444577248 & 127.484974520722 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 10084.4444444444 & 77.691392466391 & 129.801309055015 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 10084.4444444444 & 77.691392466391 & 129.801309055015 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 10084.4444444444 & 77.691392466391 & 129.801309055015 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 10084.4444444444 & 77.691392466391 & 129.801309055015 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 10070 & 75.679682413565 & 133.060812081249 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 10085.5555555556 & 73.4615292840973 & 137.290302200921 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 10102.2222222222 & 71.2356127140722 & 141.814211141425 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 10102.2222222222 & 71.2356127140722 & 141.814211141425 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 10083.3333333333 & 68.6942448324813 & 146.785707564334 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 10083.3333333333 & 68.6942448324813 & 146.785707564334 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 10083.3333333333 & 68.6942448324813 & 146.785707564334 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 10105.5555555556 & 65.8716003157985 & 153.412935272682 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 10082.2222222222 & 62.8697210349052 & 160.366899299976 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 10082.2222222222 & 62.8697210349052 & 160.366899299976 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 10082.2222222222 & 56.6341812286798 & 178.023624664261 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 10082.2222222222 & 56.6341812286798 & 178.023624664261 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 10082.2222222222 & 56.6341812286798 & 178.023624664261 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 10082.2222222222 & 56.6341812286798 & 178.023624664261 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 10082.2222222222 & 56.6341812286798 & 178.023624664261 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 10051.1111111111 & 53.0648312203998 & 189.411911428961 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 10051.1111111111 & 53.0648312203998 & 189.411911428961 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 10084.4444444444 & 49.1149310383893 & 205.323396190096 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 10084.4444444444 & 49.1149310383893 & 205.323396190096 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 10084.4444444444 & 49.1149310383893 & 205.323396190096 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 10121.1111111111 & 45.0174638881508 & 224.826328205821 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 10121.1111111111 & 45.0174638881508 & 224.826328205821 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 10082.2222222222 & 40.6177065414709 & 248.222341454169 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 10082.2222222222 & 40.6177065414709 & 248.222341454169 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 10101.5094339623 & 88.1331583062968 & 114.616446614288 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 10098.4615384615 & 84.5316987212486 & 119.463605857043 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 10094.1176470588 & 81.881670111426 & 123.276890094237 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 10092 & 80.0272680800965 & 126.107016297236 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 10091.0204081633 & 78.2122584381514 & 129.020956684725 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 10090 & 77.1874001171312 & 130.720816929816 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 10088.9361702128 & 76.0212959009062 & 132.71197301561 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 10086.5217391304 & 74.9359393213527 & 134.6019257312 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 10085.3333333333 & 73.9732380666307 & 136.337594472329 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 10085.4545454545 & 73.1359988184273 & 137.900004216712 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 10085.5813953488 & 72.166892123558 & 139.753578110045 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 10085.7142857143 & 71.0454440948113 & 141.961450367665 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 10085.8536585366 & 69.7468108359513 & 144.606664271132 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 10087.5 & 68.5550457938544 & 147.144530109909 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 10087.6923076923 & 67.5061011726735 & 149.43378646456 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 10086.3157894737 & 66.6008909126605 & 151.444157146497 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 10084.8648648649 & 65.5292703585386 & 153.898628959033 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 10085 & 64.6305862270824 & 156.040670350195 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 10085.1428571429 & 63.556024374171 & 158.681147168189 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 10085.2941176471 & 62.2713448912657 & 161.957223426881 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 10083.6363636364 & 61.1481583236159 & 164.904988802287 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 10083.75 & 60.2357718825426 & 167.404678065102 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 10083.8709677419 & 59.1189297073846 & 170.569240980057 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 10084 & 58.6607598464486 & 171.903671660511 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 10084.1379310345 & 58.0605241934343 & 173.683205088507 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 10084.2857142857 & 57.2865077510874 & 176.032474489498 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 10084.4444444444 & 56.2977674602728 & 179.126897910484 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 10084.6153846154 & 55.0404085334404 & 183.222030019787 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 10087.2 & 54.0378098923262 & 186.669297295716 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 10090 & 52.733775361051 & 191.338471992894 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 10090.4347826087 & 51.7957308237754 & 194.812094010979 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 10090.9090909091 & 50.5423212255284 & 199.652664266877 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 10091.4285714286 & 48.8717911084944 & 206.487798841377 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 10089 & 47.5337936468523 & 212.248996470916 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 10086.3157894737 & 45.6974107614776 & 220.71963425062 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 10086.6666666667 & 44.3220537029191 & 227.576698820758 \tabularnewline
Median & 10140 &  &  \tabularnewline
Midrange & 10140 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 10083.8709677419 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 10083.8709677419 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 10083.8709677419 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 10083.8709677419 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 10083.8709677419 &  &  \tabularnewline
Midmean - Closest Observation & 10083.8709677419 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 10083.8709677419 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 10083.8709677419 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211095&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]10102.2222222222[/C][C]91.8097470463004[/C][C]110.034310595885[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]10057.5423458977[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]10012.7880322178[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]10146.7630306418[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]10104.4444444444[/C][C]91.3145160040006[/C][C]110.655401645033[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]10106.6666666667[/C][C]88.9724425582839[/C][C]113.593224779077[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]10100[/C][C]86.301651652107[/C][C]117.031363903838[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]10095.5555555556[/C][C]85.4687291209576[/C][C]118.119874477928[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]10095.5555555556[/C][C]81.7425880312709[/C][C]123.504231988513[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]10095.5555555556[/C][C]81.7425880312709[/C][C]123.504231988513[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]10103.3333333333[/C][C]80.5968132968253[/C][C]125.356486442266[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]10094.4444444444[/C][C]79.181444577248[/C][C]127.484974520722[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]10084.4444444444[/C][C]77.691392466391[/C][C]129.801309055015[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]10084.4444444444[/C][C]77.691392466391[/C][C]129.801309055015[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]10084.4444444444[/C][C]77.691392466391[/C][C]129.801309055015[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]10084.4444444444[/C][C]77.691392466391[/C][C]129.801309055015[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]10070[/C][C]75.679682413565[/C][C]133.060812081249[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]10085.5555555556[/C][C]73.4615292840973[/C][C]137.290302200921[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]10102.2222222222[/C][C]71.2356127140722[/C][C]141.814211141425[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]10102.2222222222[/C][C]71.2356127140722[/C][C]141.814211141425[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]10083.3333333333[/C][C]68.6942448324813[/C][C]146.785707564334[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]10083.3333333333[/C][C]68.6942448324813[/C][C]146.785707564334[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]10083.3333333333[/C][C]68.6942448324813[/C][C]146.785707564334[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]10105.5555555556[/C][C]65.8716003157985[/C][C]153.412935272682[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]10082.2222222222[/C][C]62.8697210349052[/C][C]160.366899299976[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]10082.2222222222[/C][C]62.8697210349052[/C][C]160.366899299976[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]10082.2222222222[/C][C]56.6341812286798[/C][C]178.023624664261[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]10082.2222222222[/C][C]56.6341812286798[/C][C]178.023624664261[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]10082.2222222222[/C][C]56.6341812286798[/C][C]178.023624664261[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]10082.2222222222[/C][C]56.6341812286798[/C][C]178.023624664261[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]10082.2222222222[/C][C]56.6341812286798[/C][C]178.023624664261[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]10051.1111111111[/C][C]53.0648312203998[/C][C]189.411911428961[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]10051.1111111111[/C][C]53.0648312203998[/C][C]189.411911428961[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]10084.4444444444[/C][C]49.1149310383893[/C][C]205.323396190096[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]10084.4444444444[/C][C]49.1149310383893[/C][C]205.323396190096[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]10084.4444444444[/C][C]49.1149310383893[/C][C]205.323396190096[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]10121.1111111111[/C][C]45.0174638881508[/C][C]224.826328205821[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]10121.1111111111[/C][C]45.0174638881508[/C][C]224.826328205821[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]10082.2222222222[/C][C]40.6177065414709[/C][C]248.222341454169[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]10082.2222222222[/C][C]40.6177065414709[/C][C]248.222341454169[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]10101.5094339623[/C][C]88.1331583062968[/C][C]114.616446614288[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]10098.4615384615[/C][C]84.5316987212486[/C][C]119.463605857043[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]10094.1176470588[/C][C]81.881670111426[/C][C]123.276890094237[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]10092[/C][C]80.0272680800965[/C][C]126.107016297236[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]10091.0204081633[/C][C]78.2122584381514[/C][C]129.020956684725[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]10090[/C][C]77.1874001171312[/C][C]130.720816929816[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]10088.9361702128[/C][C]76.0212959009062[/C][C]132.71197301561[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]10086.5217391304[/C][C]74.9359393213527[/C][C]134.6019257312[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]10085.3333333333[/C][C]73.9732380666307[/C][C]136.337594472329[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]10085.4545454545[/C][C]73.1359988184273[/C][C]137.900004216712[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]10085.5813953488[/C][C]72.166892123558[/C][C]139.753578110045[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]10085.7142857143[/C][C]71.0454440948113[/C][C]141.961450367665[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]10085.8536585366[/C][C]69.7468108359513[/C][C]144.606664271132[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]10087.5[/C][C]68.5550457938544[/C][C]147.144530109909[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]10087.6923076923[/C][C]67.5061011726735[/C][C]149.43378646456[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]10086.3157894737[/C][C]66.6008909126605[/C][C]151.444157146497[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]10084.8648648649[/C][C]65.5292703585386[/C][C]153.898628959033[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]10085[/C][C]64.6305862270824[/C][C]156.040670350195[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]10085.1428571429[/C][C]63.556024374171[/C][C]158.681147168189[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]10085.2941176471[/C][C]62.2713448912657[/C][C]161.957223426881[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]10083.6363636364[/C][C]61.1481583236159[/C][C]164.904988802287[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]10083.75[/C][C]60.2357718825426[/C][C]167.404678065102[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]10083.8709677419[/C][C]59.1189297073846[/C][C]170.569240980057[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]10084[/C][C]58.6607598464486[/C][C]171.903671660511[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]10084.1379310345[/C][C]58.0605241934343[/C][C]173.683205088507[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]10084.2857142857[/C][C]57.2865077510874[/C][C]176.032474489498[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]10084.4444444444[/C][C]56.2977674602728[/C][C]179.126897910484[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]10084.6153846154[/C][C]55.0404085334404[/C][C]183.222030019787[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]10087.2[/C][C]54.0378098923262[/C][C]186.669297295716[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]10090[/C][C]52.733775361051[/C][C]191.338471992894[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]10090.4347826087[/C][C]51.7957308237754[/C][C]194.812094010979[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]10090.9090909091[/C][C]50.5423212255284[/C][C]199.652664266877[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]10091.4285714286[/C][C]48.8717911084944[/C][C]206.487798841377[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]10089[/C][C]47.5337936468523[/C][C]212.248996470916[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]10086.3157894737[/C][C]45.6974107614776[/C][C]220.71963425062[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]10086.6666666667[/C][C]44.3220537029191[/C][C]227.576698820758[/C][/ROW]
[ROW][C]Median[/C][C]10140[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]10140[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]10083.8709677419[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]10083.8709677419[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]10083.8709677419[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]10083.8709677419[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]10083.8709677419[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]10083.8709677419[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]10083.8709677419[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]10083.8709677419[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]108[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211095&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211095&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 Mean10102.222222222291.8097470463004110.034310595885
Geometric Mean10057.5423458977
Harmonic Mean10012.7880322178
Quadratic Mean10146.7630306418
Winsorized Mean ( 1 / 36 )10104.444444444491.3145160040006110.655401645033
Winsorized Mean ( 2 / 36 )10106.666666666788.9724425582839113.593224779077
Winsorized Mean ( 3 / 36 )1010086.301651652107117.031363903838
Winsorized Mean ( 4 / 36 )10095.555555555685.4687291209576118.119874477928
Winsorized Mean ( 5 / 36 )10095.555555555681.7425880312709123.504231988513
Winsorized Mean ( 6 / 36 )10095.555555555681.7425880312709123.504231988513
Winsorized Mean ( 7 / 36 )10103.333333333380.5968132968253125.356486442266
Winsorized Mean ( 8 / 36 )10094.444444444479.181444577248127.484974520722
Winsorized Mean ( 9 / 36 )10084.444444444477.691392466391129.801309055015
Winsorized Mean ( 10 / 36 )10084.444444444477.691392466391129.801309055015
Winsorized Mean ( 11 / 36 )10084.444444444477.691392466391129.801309055015
Winsorized Mean ( 12 / 36 )10084.444444444477.691392466391129.801309055015
Winsorized Mean ( 13 / 36 )1007075.679682413565133.060812081249
Winsorized Mean ( 14 / 36 )10085.555555555673.4615292840973137.290302200921
Winsorized Mean ( 15 / 36 )10102.222222222271.2356127140722141.814211141425
Winsorized Mean ( 16 / 36 )10102.222222222271.2356127140722141.814211141425
Winsorized Mean ( 17 / 36 )10083.333333333368.6942448324813146.785707564334
Winsorized Mean ( 18 / 36 )10083.333333333368.6942448324813146.785707564334
Winsorized Mean ( 19 / 36 )10083.333333333368.6942448324813146.785707564334
Winsorized Mean ( 20 / 36 )10105.555555555665.8716003157985153.412935272682
Winsorized Mean ( 21 / 36 )10082.222222222262.8697210349052160.366899299976
Winsorized Mean ( 22 / 36 )10082.222222222262.8697210349052160.366899299976
Winsorized Mean ( 23 / 36 )10082.222222222256.6341812286798178.023624664261
Winsorized Mean ( 24 / 36 )10082.222222222256.6341812286798178.023624664261
Winsorized Mean ( 25 / 36 )10082.222222222256.6341812286798178.023624664261
Winsorized Mean ( 26 / 36 )10082.222222222256.6341812286798178.023624664261
Winsorized Mean ( 27 / 36 )10082.222222222256.6341812286798178.023624664261
Winsorized Mean ( 28 / 36 )10051.111111111153.0648312203998189.411911428961
Winsorized Mean ( 29 / 36 )10051.111111111153.0648312203998189.411911428961
Winsorized Mean ( 30 / 36 )10084.444444444449.1149310383893205.323396190096
Winsorized Mean ( 31 / 36 )10084.444444444449.1149310383893205.323396190096
Winsorized Mean ( 32 / 36 )10084.444444444449.1149310383893205.323396190096
Winsorized Mean ( 33 / 36 )10121.111111111145.0174638881508224.826328205821
Winsorized Mean ( 34 / 36 )10121.111111111145.0174638881508224.826328205821
Winsorized Mean ( 35 / 36 )10082.222222222240.6177065414709248.222341454169
Winsorized Mean ( 36 / 36 )10082.222222222240.6177065414709248.222341454169
Trimmed Mean ( 1 / 36 )10101.509433962388.1331583062968114.616446614288
Trimmed Mean ( 2 / 36 )10098.461538461584.5316987212486119.463605857043
Trimmed Mean ( 3 / 36 )10094.117647058881.881670111426123.276890094237
Trimmed Mean ( 4 / 36 )1009280.0272680800965126.107016297236
Trimmed Mean ( 5 / 36 )10091.020408163378.2122584381514129.020956684725
Trimmed Mean ( 6 / 36 )1009077.1874001171312130.720816929816
Trimmed Mean ( 7 / 36 )10088.936170212876.0212959009062132.71197301561
Trimmed Mean ( 8 / 36 )10086.521739130474.9359393213527134.6019257312
Trimmed Mean ( 9 / 36 )10085.333333333373.9732380666307136.337594472329
Trimmed Mean ( 10 / 36 )10085.454545454573.1359988184273137.900004216712
Trimmed Mean ( 11 / 36 )10085.581395348872.166892123558139.753578110045
Trimmed Mean ( 12 / 36 )10085.714285714371.0454440948113141.961450367665
Trimmed Mean ( 13 / 36 )10085.853658536669.7468108359513144.606664271132
Trimmed Mean ( 14 / 36 )10087.568.5550457938544147.144530109909
Trimmed Mean ( 15 / 36 )10087.692307692367.5061011726735149.43378646456
Trimmed Mean ( 16 / 36 )10086.315789473766.6008909126605151.444157146497
Trimmed Mean ( 17 / 36 )10084.864864864965.5292703585386153.898628959033
Trimmed Mean ( 18 / 36 )1008564.6305862270824156.040670350195
Trimmed Mean ( 19 / 36 )10085.142857142963.556024374171158.681147168189
Trimmed Mean ( 20 / 36 )10085.294117647162.2713448912657161.957223426881
Trimmed Mean ( 21 / 36 )10083.636363636461.1481583236159164.904988802287
Trimmed Mean ( 22 / 36 )10083.7560.2357718825426167.404678065102
Trimmed Mean ( 23 / 36 )10083.870967741959.1189297073846170.569240980057
Trimmed Mean ( 24 / 36 )1008458.6607598464486171.903671660511
Trimmed Mean ( 25 / 36 )10084.137931034558.0605241934343173.683205088507
Trimmed Mean ( 26 / 36 )10084.285714285757.2865077510874176.032474489498
Trimmed Mean ( 27 / 36 )10084.444444444456.2977674602728179.126897910484
Trimmed Mean ( 28 / 36 )10084.615384615455.0404085334404183.222030019787
Trimmed Mean ( 29 / 36 )10087.254.0378098923262186.669297295716
Trimmed Mean ( 30 / 36 )1009052.733775361051191.338471992894
Trimmed Mean ( 31 / 36 )10090.434782608751.7957308237754194.812094010979
Trimmed Mean ( 32 / 36 )10090.909090909150.5423212255284199.652664266877
Trimmed Mean ( 33 / 36 )10091.428571428648.8717911084944206.487798841377
Trimmed Mean ( 34 / 36 )1008947.5337936468523212.248996470916
Trimmed Mean ( 35 / 36 )10086.315789473745.6974107614776220.71963425062
Trimmed Mean ( 36 / 36 )10086.666666666744.3220537029191227.576698820758
Median10140
Midrange10140
Midmean - Weighted Average at Xnp10083.8709677419
Midmean - Weighted Average at X(n+1)p10083.8709677419
Midmean - Empirical Distribution Function10083.8709677419
Midmean - Empirical Distribution Function - Averaging10083.8709677419
Midmean - Empirical Distribution Function - Interpolation10083.8709677419
Midmean - Closest Observation10083.8709677419
Midmean - True Basic - Statistics Graphics Toolkit10083.8709677419
Midmean - MS Excel (old versions)10083.8709677419
Number of observations108



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,hyperlink('arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE)
a<-table.element(a,arm)
a<-table.element(a,hyperlink('arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean'))
a<-table.element(a,armose)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE)
a<-table.element(a,geo)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE)
a<-table.element(a,har)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE)
a<-table.element(a,qua)
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,hyperlink('winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE)
a<-table.element(a,win[j,1])
a<-table.element(a,win[j,2])
a<-table.element(a,win[j,1]/win[j,2])
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,hyperlink('arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE)
a<-table.element(a,tri[j,1])
a<-table.element(a,tri[j,2])
a<-table.element(a,tri[j,1]/tri[j,2])
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,hyperlink('median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE)
a<-table.element(a,median(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE)
a<-table.element(a,midr)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_1.htm','Weighted Average at Xnp',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[2])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_3.htm','Empirical Distribution Function',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[3])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[4])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[5])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_6.htm','Closest Observation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[6])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[7])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_8.htm','MS Excel (old versions)',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[8])
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,length(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')