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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationFri, 12 Dec 2008 06:08:46 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/12/t1229087374ohx4n5xph9mx739.htm/, Retrieved Sat, 18 May 2024 05:09:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32669, Retrieved Sat, 18 May 2024 05:09:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact242

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Central Tendency:...] [2008-12-12 13:08:46] [14a75ec03b2c0d8ddd8b141a7b1594fd] [Current]
- RMPD    [Mean Plot] [Mean Plot - Goudp...] [2008-12-12 14:53:25] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
- RMPD      [Box-Cox Normality Plot] [Box Cox Normality...] [2008-12-13 11:54:35] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
-    D        [Box-Cox Normality Plot] [Box Cox Normality...] [2008-12-13 11:59:23] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
-    D          [Box-Cox Normality Plot] [Box Cox Normality...] [2008-12-13 12:02:48] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
-    D          [Box-Cox Normality Plot] [Box Cox Normality...] [2008-12-13 12:16:55] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
- RMPD      [Notched Boxplots] [Notched boxplot: ...] [2008-12-13 13:10:25] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
-    D        [Notched Boxplots] [Notched boxplot: ...] [2008-12-13 13:16:58] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
- RMPD    [Mean Plot] [Mean plot - prijs...] [2008-12-12 14:56:05] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
- RMPD      [Partial Correlation] [Partiële correlat...] [2008-12-12 15:00:18] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
- RMPD      [Tukey lambda PPCC Plot] [PPCC: Bel 20] [2008-12-12 15:02:48] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
-    D        [Tukey lambda PPCC Plot] [PPCC: Dow Jones] [2008-12-12 15:15:38] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
- RMPD        [Variance Reduction Matrix] [VRM Matrix: Dow J...] [2008-12-13 14:12:15] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
- RMPD        [Variance Reduction Matrix] [VRM Matrix: Prijs...] [2008-12-13 14:17:40] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
- RMP         [Variance Reduction Matrix] [VRM Matrix: Bel 20] [2008-12-13 14:24:44] [7670c7b8188a1e79d237811892660e29]
- RMP         [ARIMA Backward Selection] [Arima: Bel 20] [2008-12-14 20:11:31] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
-    D          [ARIMA Backward Selection] [Arima: Dow Jones] [2008-12-14 20:18:50] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
- RMPD            [Central Tendency] [Central tendency ...] [2008-12-14 21:13:09] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
-   PD            [ARIMA Backward Selection] [Backward selectio...] [2008-12-17 20:48:25] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
- RMPD          [Central Tendency] [Central tendency ...] [2008-12-14 21:08:44] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
F RMPD          [ARIMA Forecasting] [Arima forecasting...] [2008-12-14 22:14:13] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
-   PD            [ARIMA Forecasting] [Arima forecasting...] [2008-12-14 22:31:41] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
-                   [ARIMA Forecasting] [arima forecast do...] [2008-12-15 23:20:43] [73d6180dc45497329efd1b6934a84aba]
-   PD              [ARIMA Forecasting] [Arima forecasting...] [2008-12-19 23:09:36] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
F                 [ARIMA Forecasting] [arima forecasting...] [2008-12-15 23:16:18] [73d6180dc45497329efd1b6934a84aba]
- RMPD      [Tukey lambda PPCC Plot] [PPCC: Dow Jones] [2008-12-12 15:04:49] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
- RMPD      [Tukey lambda PPCC Plot] [] [2008-12-12 15:04:49] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
- RMPD      [Tukey lambda PPCC Plot] [PPCC: Dow Jones] [2008-12-12 15:04:49] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3032,93
3045,78
3110,52
3013,24
2987,1
2995,55
2833,18
2848,96
2794,83
2845,26
2915,02
2892,63
2604,42
2641,65
2659,81
2638,53
2720,25
2745,88
2735,7
2811,7
2799,43
2555,28
2304,98
2214,95
2065,81
1940,49
2042
1995,37
1946,81
1765,9
1635,25
1833,42
1910,43
1959,67
1969,6
2061,41
2093,48
2120,88
2174,56
2196,72
2350,44
2440,25
2408,64
2472,81
2407,6
2454,62
2448,05
2497,84
2645,64
2756,76
2849,27
2921,44
2981,85
3080,58
3106,22
3119,31
3061,26
3097,31
3161,69
3257,16
3277,01
3295,32
3363,99
3494,17
3667,03
3813,06
3917,96
3895,51
3801,06
3570,12
3701,61
3862,27
3970,1
4138,52
4199,75
4290,89
4443,91
4502,64
4356,98
4591,27
4696,96
4621,4
4562,84
4202,52
4296,49
4435,23
4105,18
4116,68
3844,49
3720,98
3674,4
3857,62
3801,06
3504,37
3032,6
3047,03
2962,34
2197,82
2014,45

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32669&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32669&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32669&T=0

As an alternative you can also use a QR Code:  
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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean3058.8459595959679.846287104774338.3091821862943
Geometric Mean2956.92708959004
Harmonic Mean2856.55632799435
Quadratic Mean3159.32440592122
Winsorized Mean ( 1 / 33 )3059.4024242424279.460163436321738.5023424560936
Winsorized Mean ( 2 / 33 )3060.1577777777879.117806595360338.6784961497812
Winsorized Mean ( 3 / 33 )3061.629898989978.589727995409138.9571255313258
Winsorized Mean ( 4 / 33 )3060.4121212121277.943207375033739.2646418370566
Winsorized Mean ( 5 / 33 )3057.7651515151577.345143629518139.5340290033178
Winsorized Mean ( 6 / 33 )3058.0184848484977.13538131984439.6448222919691
Winsorized Mean ( 7 / 33 )3053.1877777777876.045196952479840.1496465277839
Winsorized Mean ( 8 / 33 )3050.3821212121274.901558795139440.7252154732202
Winsorized Mean ( 9 / 33 )3051.6075757575874.567433590817540.9241330807094
Winsorized Mean ( 10 / 33 )3045.4641414141472.691728626149841.8956076430212
Winsorized Mean ( 11 / 33 )3047.3130303030372.339855064020342.1249534935642
Winsorized Mean ( 12 / 33 )3040.4245454545571.077042274220342.7764640757612
Winsorized Mean ( 13 / 33 )3041.190101010170.121795081150843.3701119244107
Winsorized Mean ( 14 / 33 )3043.4385858585969.337238866056343.8932763350703
Winsorized Mean ( 15 / 33 )3031.1052525252565.131853653215846.5379853713958
Winsorized Mean ( 16 / 33 )3026.2663.428112557652747.7116514739311
Winsorized Mean ( 17 / 33 )3022.5938383838462.853175963259548.0897550849408
Winsorized Mean ( 18 / 33 )3019.6647474747561.586841420252649.0310052900641
Winsorized Mean ( 19 / 33 )3036.0508080808159.220000454036351.2673215941166
Winsorized Mean ( 20 / 33 )3042.5821212121257.703495898649352.7278646436973
Winsorized Mean ( 21 / 33 )3048.0455.301210454346655.1170575645226
Winsorized Mean ( 22 / 33 )3045.6044444444454.898432765833755.4770744992905
Winsorized Mean ( 23 / 33 )3052.9481818181854.038810886736256.4954730076699
Winsorized Mean ( 24 / 33 )3035.4257575757651.117856438816259.3809280952324
Winsorized Mean ( 25 / 33 )3032.1934343434350.256177832287360.3347402276062
Winsorized Mean ( 26 / 33 )3029.8245454545548.729468307536562.1764334946776
Winsorized Mean ( 27 / 33 )3034.6409090909147.667374844800763.6628494640482
Winsorized Mean ( 28 / 33 )3023.4776767676842.140520795860771.7475156848243
Winsorized Mean ( 29 / 33 )3018.6121212121237.99099921320579.4559812515514
Winsorized Mean ( 30 / 33 )3025.8575757575836.451145170660283.0113172464362
Winsorized Mean ( 31 / 33 )2986.0711111111131.135162154134295.9067146118785
Winsorized Mean ( 32 / 33 )2965.1644444444428.2893340342881104.815632663905
Winsorized Mean ( 33 / 33 )2963.7844444444427.0215912731553109.682084022521
Trimmed Mean ( 1 / 33 )3056.6344329896978.336372242175139.0193513626106
Trimmed Mean ( 2 / 33 )3053.7498947368477.06007825263539.6281701755529
Trimmed Mean ( 3 / 33 )3050.3392473118375.811310831446240.2359385935662
Trimmed Mean ( 4 / 33 )3046.2448351648374.605835154532840.8311873844061
Trimmed Mean ( 5 / 33 )3042.3050561797873.439354029559341.4260868219953
Trimmed Mean ( 6 / 33 )3038.7865517241472.267052386785242.0494049689484
Trimmed Mean ( 7 / 33 )3035.0532941176570.966925732414542.7671519203399
Trimmed Mean ( 8 / 33 )3031.9632530120569.712204889689843.4925743319943
Trimmed Mean ( 9 / 33 )3029.1492592592668.495230697665944.2242361753587
Trimmed Mean ( 10 / 33 )3026.0221518987367.142696776354845.0685226716182
Trimmed Mean ( 11 / 33 )3023.5224675324765.915708503491745.8695284656207
Trimmed Mean ( 12 / 33 )3020.667664.537800298318146.8046259097356
Trimmed Mean ( 13 / 33 )3018.4347945205563.141302834169147.8044427187066
Trimmed Mean ( 14 / 33 )3015.9940845070461.654976804240948.917285202832
Trimmed Mean ( 15 / 33 )3013.1814492753660.023687606495550.1998722409266
Trimmed Mean ( 16 / 33 )3011.4158208955258.793369407634351.2203306467497
Trimmed Mean ( 17 / 33 )3010.0027692307757.595385704059752.2611791280808
Trimmed Mean ( 18 / 33 )3008.8388888888956.243156545697353.4969776535252
Trimmed Mean ( 19 / 33 )3007.8627868852554.815036164668754.8729508788316
Trimmed Mean ( 20 / 33 )3005.3733898305153.461866143973656.2152728028048
Trimmed Mean ( 21 / 33 )3002.1421052631652.047705709234157.680584847192
Trimmed Mean ( 22 / 33 )2998.20850.702448294507859.1333969236506
Trimmed Mean ( 23 / 33 )2994.1837735849149.092166872141760.9910697440412
Trimmed Mean ( 24 / 33 )2989.2241176470647.208034376992863.3202410796388
Trimmed Mean ( 25 / 33 )2985.3346938775545.428088729187265.7156129035976
Trimmed Mean ( 26 / 33 )2981.3865957446843.326140048433268.812651955883
Trimmed Mean ( 27 / 33 )2981.3865957446840.940546777792972.8223443601358
Trimmed Mean ( 28 / 33 )2972.3974418604738.03078623525278.1576647791008
Trimmed Mean ( 29 / 33 )2967.9924390243935.613409747954183.3391820673643
Trimmed Mean ( 30 / 33 )2963.5615384615433.461814155099288.5654771951425
Trimmed Mean ( 31 / 33 )2958.0054054054130.890827604959295.7567548281073
Trimmed Mean ( 32 / 33 )2955.4445714285729.0742056036996101.651773799540
Trimmed Mean ( 33 / 33 )2954.5333333333327.4275326572432107.721440723655
Median2981.85
Midrange3166.105
Midmean - Weighted Average at Xnp2974.589
Midmean - Weighted Average at X(n+1)p2989.22411764706
Midmean - Empirical Distribution Function2989.22411764706
Midmean - Empirical Distribution Function - Averaging2989.22411764706
Midmean - Empirical Distribution Function - Interpolation2985.33469387755
Midmean - Closest Observation2974.589
Midmean - True Basic - Statistics Graphics Toolkit2989.22411764706
Midmean - MS Excel (old versions)2989.22411764706
Number of observations99

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 3058.84595959596 & 79.8462871047743 & 38.3091821862943 \tabularnewline
Geometric Mean & 2956.92708959004 &  &  \tabularnewline
Harmonic Mean & 2856.55632799435 &  &  \tabularnewline
Quadratic Mean & 3159.32440592122 &  &  \tabularnewline
Winsorized Mean ( 1 / 33 ) & 3059.40242424242 & 79.4601634363217 & 38.5023424560936 \tabularnewline
Winsorized Mean ( 2 / 33 ) & 3060.15777777778 & 79.1178065953603 & 38.6784961497812 \tabularnewline
Winsorized Mean ( 3 / 33 ) & 3061.6298989899 & 78.5897279954091 & 38.9571255313258 \tabularnewline
Winsorized Mean ( 4 / 33 ) & 3060.41212121212 & 77.9432073750337 & 39.2646418370566 \tabularnewline
Winsorized Mean ( 5 / 33 ) & 3057.76515151515 & 77.3451436295181 & 39.5340290033178 \tabularnewline
Winsorized Mean ( 6 / 33 ) & 3058.01848484849 & 77.135381319844 & 39.6448222919691 \tabularnewline
Winsorized Mean ( 7 / 33 ) & 3053.18777777778 & 76.0451969524798 & 40.1496465277839 \tabularnewline
Winsorized Mean ( 8 / 33 ) & 3050.38212121212 & 74.9015587951394 & 40.7252154732202 \tabularnewline
Winsorized Mean ( 9 / 33 ) & 3051.60757575758 & 74.5674335908175 & 40.9241330807094 \tabularnewline
Winsorized Mean ( 10 / 33 ) & 3045.46414141414 & 72.6917286261498 & 41.8956076430212 \tabularnewline
Winsorized Mean ( 11 / 33 ) & 3047.31303030303 & 72.3398550640203 & 42.1249534935642 \tabularnewline
Winsorized Mean ( 12 / 33 ) & 3040.42454545455 & 71.0770422742203 & 42.7764640757612 \tabularnewline
Winsorized Mean ( 13 / 33 ) & 3041.1901010101 & 70.1217950811508 & 43.3701119244107 \tabularnewline
Winsorized Mean ( 14 / 33 ) & 3043.43858585859 & 69.3372388660563 & 43.8932763350703 \tabularnewline
Winsorized Mean ( 15 / 33 ) & 3031.10525252525 & 65.1318536532158 & 46.5379853713958 \tabularnewline
Winsorized Mean ( 16 / 33 ) & 3026.26 & 63.4281125576527 & 47.7116514739311 \tabularnewline
Winsorized Mean ( 17 / 33 ) & 3022.59383838384 & 62.8531759632595 & 48.0897550849408 \tabularnewline
Winsorized Mean ( 18 / 33 ) & 3019.66474747475 & 61.5868414202526 & 49.0310052900641 \tabularnewline
Winsorized Mean ( 19 / 33 ) & 3036.05080808081 & 59.2200004540363 & 51.2673215941166 \tabularnewline
Winsorized Mean ( 20 / 33 ) & 3042.58212121212 & 57.7034958986493 & 52.7278646436973 \tabularnewline
Winsorized Mean ( 21 / 33 ) & 3048.04 & 55.3012104543466 & 55.1170575645226 \tabularnewline
Winsorized Mean ( 22 / 33 ) & 3045.60444444444 & 54.8984327658337 & 55.4770744992905 \tabularnewline
Winsorized Mean ( 23 / 33 ) & 3052.94818181818 & 54.0388108867362 & 56.4954730076699 \tabularnewline
Winsorized Mean ( 24 / 33 ) & 3035.42575757576 & 51.1178564388162 & 59.3809280952324 \tabularnewline
Winsorized Mean ( 25 / 33 ) & 3032.19343434343 & 50.2561778322873 & 60.3347402276062 \tabularnewline
Winsorized Mean ( 26 / 33 ) & 3029.82454545455 & 48.7294683075365 & 62.1764334946776 \tabularnewline
Winsorized Mean ( 27 / 33 ) & 3034.64090909091 & 47.6673748448007 & 63.6628494640482 \tabularnewline
Winsorized Mean ( 28 / 33 ) & 3023.47767676768 & 42.1405207958607 & 71.7475156848243 \tabularnewline
Winsorized Mean ( 29 / 33 ) & 3018.61212121212 & 37.990999213205 & 79.4559812515514 \tabularnewline
Winsorized Mean ( 30 / 33 ) & 3025.85757575758 & 36.4511451706602 & 83.0113172464362 \tabularnewline
Winsorized Mean ( 31 / 33 ) & 2986.07111111111 & 31.1351621541342 & 95.9067146118785 \tabularnewline
Winsorized Mean ( 32 / 33 ) & 2965.16444444444 & 28.2893340342881 & 104.815632663905 \tabularnewline
Winsorized Mean ( 33 / 33 ) & 2963.78444444444 & 27.0215912731553 & 109.682084022521 \tabularnewline
Trimmed Mean ( 1 / 33 ) & 3056.63443298969 & 78.3363722421751 & 39.0193513626106 \tabularnewline
Trimmed Mean ( 2 / 33 ) & 3053.74989473684 & 77.060078252635 & 39.6281701755529 \tabularnewline
Trimmed Mean ( 3 / 33 ) & 3050.33924731183 & 75.8113108314462 & 40.2359385935662 \tabularnewline
Trimmed Mean ( 4 / 33 ) & 3046.24483516483 & 74.6058351545328 & 40.8311873844061 \tabularnewline
Trimmed Mean ( 5 / 33 ) & 3042.30505617978 & 73.4393540295593 & 41.4260868219953 \tabularnewline
Trimmed Mean ( 6 / 33 ) & 3038.78655172414 & 72.2670523867852 & 42.0494049689484 \tabularnewline
Trimmed Mean ( 7 / 33 ) & 3035.05329411765 & 70.9669257324145 & 42.7671519203399 \tabularnewline
Trimmed Mean ( 8 / 33 ) & 3031.96325301205 & 69.7122048896898 & 43.4925743319943 \tabularnewline
Trimmed Mean ( 9 / 33 ) & 3029.14925925926 & 68.4952306976659 & 44.2242361753587 \tabularnewline
Trimmed Mean ( 10 / 33 ) & 3026.02215189873 & 67.1426967763548 & 45.0685226716182 \tabularnewline
Trimmed Mean ( 11 / 33 ) & 3023.52246753247 & 65.9157085034917 & 45.8695284656207 \tabularnewline
Trimmed Mean ( 12 / 33 ) & 3020.6676 & 64.5378002983181 & 46.8046259097356 \tabularnewline
Trimmed Mean ( 13 / 33 ) & 3018.43479452055 & 63.1413028341691 & 47.8044427187066 \tabularnewline
Trimmed Mean ( 14 / 33 ) & 3015.99408450704 & 61.6549768042409 & 48.917285202832 \tabularnewline
Trimmed Mean ( 15 / 33 ) & 3013.18144927536 & 60.0236876064955 & 50.1998722409266 \tabularnewline
Trimmed Mean ( 16 / 33 ) & 3011.41582089552 & 58.7933694076343 & 51.2203306467497 \tabularnewline
Trimmed Mean ( 17 / 33 ) & 3010.00276923077 & 57.5953857040597 & 52.2611791280808 \tabularnewline
Trimmed Mean ( 18 / 33 ) & 3008.83888888889 & 56.2431565456973 & 53.4969776535252 \tabularnewline
Trimmed Mean ( 19 / 33 ) & 3007.86278688525 & 54.8150361646687 & 54.8729508788316 \tabularnewline
Trimmed Mean ( 20 / 33 ) & 3005.37338983051 & 53.4618661439736 & 56.2152728028048 \tabularnewline
Trimmed Mean ( 21 / 33 ) & 3002.14210526316 & 52.0477057092341 & 57.680584847192 \tabularnewline
Trimmed Mean ( 22 / 33 ) & 2998.208 & 50.7024482945078 & 59.1333969236506 \tabularnewline
Trimmed Mean ( 23 / 33 ) & 2994.18377358491 & 49.0921668721417 & 60.9910697440412 \tabularnewline
Trimmed Mean ( 24 / 33 ) & 2989.22411764706 & 47.2080343769928 & 63.3202410796388 \tabularnewline
Trimmed Mean ( 25 / 33 ) & 2985.33469387755 & 45.4280887291872 & 65.7156129035976 \tabularnewline
Trimmed Mean ( 26 / 33 ) & 2981.38659574468 & 43.3261400484332 & 68.812651955883 \tabularnewline
Trimmed Mean ( 27 / 33 ) & 2981.38659574468 & 40.9405467777929 & 72.8223443601358 \tabularnewline
Trimmed Mean ( 28 / 33 ) & 2972.39744186047 & 38.030786235252 & 78.1576647791008 \tabularnewline
Trimmed Mean ( 29 / 33 ) & 2967.99243902439 & 35.6134097479541 & 83.3391820673643 \tabularnewline
Trimmed Mean ( 30 / 33 ) & 2963.56153846154 & 33.4618141550992 & 88.5654771951425 \tabularnewline
Trimmed Mean ( 31 / 33 ) & 2958.00540540541 & 30.8908276049592 & 95.7567548281073 \tabularnewline
Trimmed Mean ( 32 / 33 ) & 2955.44457142857 & 29.0742056036996 & 101.651773799540 \tabularnewline
Trimmed Mean ( 33 / 33 ) & 2954.53333333333 & 27.4275326572432 & 107.721440723655 \tabularnewline
Median & 2981.85 &  &  \tabularnewline
Midrange & 3166.105 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 2974.589 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 2989.22411764706 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 2989.22411764706 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 2989.22411764706 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 2985.33469387755 &  &  \tabularnewline
Midmean - Closest Observation & 2974.589 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 2989.22411764706 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 2989.22411764706 &  &  \tabularnewline
Number of observations & 99 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32669&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]3058.84595959596[/C][C]79.8462871047743[/C][C]38.3091821862943[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]2956.92708959004[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]2856.55632799435[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]3159.32440592122[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 33 )[/C][C]3059.40242424242[/C][C]79.4601634363217[/C][C]38.5023424560936[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 33 )[/C][C]3060.15777777778[/C][C]79.1178065953603[/C][C]38.6784961497812[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 33 )[/C][C]3061.6298989899[/C][C]78.5897279954091[/C][C]38.9571255313258[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 33 )[/C][C]3060.41212121212[/C][C]77.9432073750337[/C][C]39.2646418370566[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 33 )[/C][C]3057.76515151515[/C][C]77.3451436295181[/C][C]39.5340290033178[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 33 )[/C][C]3058.01848484849[/C][C]77.135381319844[/C][C]39.6448222919691[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 33 )[/C][C]3053.18777777778[/C][C]76.0451969524798[/C][C]40.1496465277839[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 33 )[/C][C]3050.38212121212[/C][C]74.9015587951394[/C][C]40.7252154732202[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 33 )[/C][C]3051.60757575758[/C][C]74.5674335908175[/C][C]40.9241330807094[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 33 )[/C][C]3045.46414141414[/C][C]72.6917286261498[/C][C]41.8956076430212[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 33 )[/C][C]3047.31303030303[/C][C]72.3398550640203[/C][C]42.1249534935642[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 33 )[/C][C]3040.42454545455[/C][C]71.0770422742203[/C][C]42.7764640757612[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 33 )[/C][C]3041.1901010101[/C][C]70.1217950811508[/C][C]43.3701119244107[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 33 )[/C][C]3043.43858585859[/C][C]69.3372388660563[/C][C]43.8932763350703[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 33 )[/C][C]3031.10525252525[/C][C]65.1318536532158[/C][C]46.5379853713958[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 33 )[/C][C]3026.26[/C][C]63.4281125576527[/C][C]47.7116514739311[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 33 )[/C][C]3022.59383838384[/C][C]62.8531759632595[/C][C]48.0897550849408[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 33 )[/C][C]3019.66474747475[/C][C]61.5868414202526[/C][C]49.0310052900641[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 33 )[/C][C]3036.05080808081[/C][C]59.2200004540363[/C][C]51.2673215941166[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 33 )[/C][C]3042.58212121212[/C][C]57.7034958986493[/C][C]52.7278646436973[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 33 )[/C][C]3048.04[/C][C]55.3012104543466[/C][C]55.1170575645226[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 33 )[/C][C]3045.60444444444[/C][C]54.8984327658337[/C][C]55.4770744992905[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 33 )[/C][C]3052.94818181818[/C][C]54.0388108867362[/C][C]56.4954730076699[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 33 )[/C][C]3035.42575757576[/C][C]51.1178564388162[/C][C]59.3809280952324[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 33 )[/C][C]3032.19343434343[/C][C]50.2561778322873[/C][C]60.3347402276062[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 33 )[/C][C]3029.82454545455[/C][C]48.7294683075365[/C][C]62.1764334946776[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 33 )[/C][C]3034.64090909091[/C][C]47.6673748448007[/C][C]63.6628494640482[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 33 )[/C][C]3023.47767676768[/C][C]42.1405207958607[/C][C]71.7475156848243[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 33 )[/C][C]3018.61212121212[/C][C]37.990999213205[/C][C]79.4559812515514[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 33 )[/C][C]3025.85757575758[/C][C]36.4511451706602[/C][C]83.0113172464362[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 33 )[/C][C]2986.07111111111[/C][C]31.1351621541342[/C][C]95.9067146118785[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 33 )[/C][C]2965.16444444444[/C][C]28.2893340342881[/C][C]104.815632663905[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 33 )[/C][C]2963.78444444444[/C][C]27.0215912731553[/C][C]109.682084022521[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 33 )[/C][C]3056.63443298969[/C][C]78.3363722421751[/C][C]39.0193513626106[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 33 )[/C][C]3053.74989473684[/C][C]77.060078252635[/C][C]39.6281701755529[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 33 )[/C][C]3050.33924731183[/C][C]75.8113108314462[/C][C]40.2359385935662[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 33 )[/C][C]3046.24483516483[/C][C]74.6058351545328[/C][C]40.8311873844061[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 33 )[/C][C]3042.30505617978[/C][C]73.4393540295593[/C][C]41.4260868219953[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 33 )[/C][C]3038.78655172414[/C][C]72.2670523867852[/C][C]42.0494049689484[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 33 )[/C][C]3035.05329411765[/C][C]70.9669257324145[/C][C]42.7671519203399[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 33 )[/C][C]3031.96325301205[/C][C]69.7122048896898[/C][C]43.4925743319943[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 33 )[/C][C]3029.14925925926[/C][C]68.4952306976659[/C][C]44.2242361753587[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 33 )[/C][C]3026.02215189873[/C][C]67.1426967763548[/C][C]45.0685226716182[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 33 )[/C][C]3023.52246753247[/C][C]65.9157085034917[/C][C]45.8695284656207[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 33 )[/C][C]3020.6676[/C][C]64.5378002983181[/C][C]46.8046259097356[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 33 )[/C][C]3018.43479452055[/C][C]63.1413028341691[/C][C]47.8044427187066[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 33 )[/C][C]3015.99408450704[/C][C]61.6549768042409[/C][C]48.917285202832[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 33 )[/C][C]3013.18144927536[/C][C]60.0236876064955[/C][C]50.1998722409266[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 33 )[/C][C]3011.41582089552[/C][C]58.7933694076343[/C][C]51.2203306467497[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 33 )[/C][C]3010.00276923077[/C][C]57.5953857040597[/C][C]52.2611791280808[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 33 )[/C][C]3008.83888888889[/C][C]56.2431565456973[/C][C]53.4969776535252[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 33 )[/C][C]3007.86278688525[/C][C]54.8150361646687[/C][C]54.8729508788316[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 33 )[/C][C]3005.37338983051[/C][C]53.4618661439736[/C][C]56.2152728028048[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 33 )[/C][C]3002.14210526316[/C][C]52.0477057092341[/C][C]57.680584847192[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 33 )[/C][C]2998.208[/C][C]50.7024482945078[/C][C]59.1333969236506[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 33 )[/C][C]2994.18377358491[/C][C]49.0921668721417[/C][C]60.9910697440412[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 33 )[/C][C]2989.22411764706[/C][C]47.2080343769928[/C][C]63.3202410796388[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 33 )[/C][C]2985.33469387755[/C][C]45.4280887291872[/C][C]65.7156129035976[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 33 )[/C][C]2981.38659574468[/C][C]43.3261400484332[/C][C]68.812651955883[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 33 )[/C][C]2981.38659574468[/C][C]40.9405467777929[/C][C]72.8223443601358[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 33 )[/C][C]2972.39744186047[/C][C]38.030786235252[/C][C]78.1576647791008[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 33 )[/C][C]2967.99243902439[/C][C]35.6134097479541[/C][C]83.3391820673643[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 33 )[/C][C]2963.56153846154[/C][C]33.4618141550992[/C][C]88.5654771951425[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 33 )[/C][C]2958.00540540541[/C][C]30.8908276049592[/C][C]95.7567548281073[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 33 )[/C][C]2955.44457142857[/C][C]29.0742056036996[/C][C]101.651773799540[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 33 )[/C][C]2954.53333333333[/C][C]27.4275326572432[/C][C]107.721440723655[/C][/ROW]
[ROW][C]Median[/C][C]2981.85[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]3166.105[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]2974.589[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]2989.22411764706[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]2989.22411764706[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]2989.22411764706[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]2985.33469387755[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]2974.589[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]2989.22411764706[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]2989.22411764706[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]99[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32669&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32669&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean3058.8459595959679.846287104774338.3091821862943
Geometric Mean2956.92708959004
Harmonic Mean2856.55632799435
Quadratic Mean3159.32440592122
Winsorized Mean ( 1 / 33 )3059.4024242424279.460163436321738.5023424560936
Winsorized Mean ( 2 / 33 )3060.1577777777879.117806595360338.6784961497812
Winsorized Mean ( 3 / 33 )3061.629898989978.589727995409138.9571255313258
Winsorized Mean ( 4 / 33 )3060.4121212121277.943207375033739.2646418370566
Winsorized Mean ( 5 / 33 )3057.7651515151577.345143629518139.5340290033178
Winsorized Mean ( 6 / 33 )3058.0184848484977.13538131984439.6448222919691
Winsorized Mean ( 7 / 33 )3053.1877777777876.045196952479840.1496465277839
Winsorized Mean ( 8 / 33 )3050.3821212121274.901558795139440.7252154732202
Winsorized Mean ( 9 / 33 )3051.6075757575874.567433590817540.9241330807094
Winsorized Mean ( 10 / 33 )3045.4641414141472.691728626149841.8956076430212
Winsorized Mean ( 11 / 33 )3047.3130303030372.339855064020342.1249534935642
Winsorized Mean ( 12 / 33 )3040.4245454545571.077042274220342.7764640757612
Winsorized Mean ( 13 / 33 )3041.190101010170.121795081150843.3701119244107
Winsorized Mean ( 14 / 33 )3043.4385858585969.337238866056343.8932763350703
Winsorized Mean ( 15 / 33 )3031.1052525252565.131853653215846.5379853713958
Winsorized Mean ( 16 / 33 )3026.2663.428112557652747.7116514739311
Winsorized Mean ( 17 / 33 )3022.5938383838462.853175963259548.0897550849408
Winsorized Mean ( 18 / 33 )3019.6647474747561.586841420252649.0310052900641
Winsorized Mean ( 19 / 33 )3036.0508080808159.220000454036351.2673215941166
Winsorized Mean ( 20 / 33 )3042.5821212121257.703495898649352.7278646436973
Winsorized Mean ( 21 / 33 )3048.0455.301210454346655.1170575645226
Winsorized Mean ( 22 / 33 )3045.6044444444454.898432765833755.4770744992905
Winsorized Mean ( 23 / 33 )3052.9481818181854.038810886736256.4954730076699
Winsorized Mean ( 24 / 33 )3035.4257575757651.117856438816259.3809280952324
Winsorized Mean ( 25 / 33 )3032.1934343434350.256177832287360.3347402276062
Winsorized Mean ( 26 / 33 )3029.8245454545548.729468307536562.1764334946776
Winsorized Mean ( 27 / 33 )3034.6409090909147.667374844800763.6628494640482
Winsorized Mean ( 28 / 33 )3023.4776767676842.140520795860771.7475156848243
Winsorized Mean ( 29 / 33 )3018.6121212121237.99099921320579.4559812515514
Winsorized Mean ( 30 / 33 )3025.8575757575836.451145170660283.0113172464362
Winsorized Mean ( 31 / 33 )2986.0711111111131.135162154134295.9067146118785
Winsorized Mean ( 32 / 33 )2965.1644444444428.2893340342881104.815632663905
Winsorized Mean ( 33 / 33 )2963.7844444444427.0215912731553109.682084022521
Trimmed Mean ( 1 / 33 )3056.6344329896978.336372242175139.0193513626106
Trimmed Mean ( 2 / 33 )3053.7498947368477.06007825263539.6281701755529
Trimmed Mean ( 3 / 33 )3050.3392473118375.811310831446240.2359385935662
Trimmed Mean ( 4 / 33 )3046.2448351648374.605835154532840.8311873844061
Trimmed Mean ( 5 / 33 )3042.3050561797873.439354029559341.4260868219953
Trimmed Mean ( 6 / 33 )3038.7865517241472.267052386785242.0494049689484
Trimmed Mean ( 7 / 33 )3035.0532941176570.966925732414542.7671519203399
Trimmed Mean ( 8 / 33 )3031.9632530120569.712204889689843.4925743319943
Trimmed Mean ( 9 / 33 )3029.1492592592668.495230697665944.2242361753587
Trimmed Mean ( 10 / 33 )3026.0221518987367.142696776354845.0685226716182
Trimmed Mean ( 11 / 33 )3023.5224675324765.915708503491745.8695284656207
Trimmed Mean ( 12 / 33 )3020.667664.537800298318146.8046259097356
Trimmed Mean ( 13 / 33 )3018.4347945205563.141302834169147.8044427187066
Trimmed Mean ( 14 / 33 )3015.9940845070461.654976804240948.917285202832
Trimmed Mean ( 15 / 33 )3013.1814492753660.023687606495550.1998722409266
Trimmed Mean ( 16 / 33 )3011.4158208955258.793369407634351.2203306467497
Trimmed Mean ( 17 / 33 )3010.0027692307757.595385704059752.2611791280808
Trimmed Mean ( 18 / 33 )3008.8388888888956.243156545697353.4969776535252
Trimmed Mean ( 19 / 33 )3007.8627868852554.815036164668754.8729508788316
Trimmed Mean ( 20 / 33 )3005.3733898305153.461866143973656.2152728028048
Trimmed Mean ( 21 / 33 )3002.1421052631652.047705709234157.680584847192
Trimmed Mean ( 22 / 33 )2998.20850.702448294507859.1333969236506
Trimmed Mean ( 23 / 33 )2994.1837735849149.092166872141760.9910697440412
Trimmed Mean ( 24 / 33 )2989.2241176470647.208034376992863.3202410796388
Trimmed Mean ( 25 / 33 )2985.3346938775545.428088729187265.7156129035976
Trimmed Mean ( 26 / 33 )2981.3865957446843.326140048433268.812651955883
Trimmed Mean ( 27 / 33 )2981.3865957446840.940546777792972.8223443601358
Trimmed Mean ( 28 / 33 )2972.3974418604738.03078623525278.1576647791008
Trimmed Mean ( 29 / 33 )2967.9924390243935.613409747954183.3391820673643
Trimmed Mean ( 30 / 33 )2963.5615384615433.461814155099288.5654771951425
Trimmed Mean ( 31 / 33 )2958.0054054054130.890827604959295.7567548281073
Trimmed Mean ( 32 / 33 )2955.4445714285729.0742056036996101.651773799540
Trimmed Mean ( 33 / 33 )2954.5333333333327.4275326572432107.721440723655
Median2981.85
Midrange3166.105
Midmean - Weighted Average at Xnp2974.589
Midmean - Weighted Average at X(n+1)p2989.22411764706
Midmean - Empirical Distribution Function2989.22411764706
Midmean - Empirical Distribution Function - Averaging2989.22411764706
Midmean - Empirical Distribution Function - Interpolation2985.33469387755
Midmean - Closest Observation2974.589
Midmean - True Basic - Statistics Graphics Toolkit2989.22411764706
Midmean - MS Excel (old versions)2989.22411764706
Number of observations99


Figures (Output of Computation)

Input Parameters & R Code

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')