FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationMon, 15 Dec 2014 20:23:02 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/15/t1418674992y4t60nm1ippy5px.htm/, Retrieved Thu, 16 May 2024 06:13:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269010, Retrieved Thu, 16 May 2024 06:13:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact82

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [Chi-squared test] [2014-11-02 11:21:00] [5c51c91cab622bcf955f01721b682696]
- R  D  [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 17:26:49] [e493208d2907342b139e6792bbaea494]
-    D    [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 17:30:24] [e493208d2907342b139e6792bbaea494]
-    D      [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 17:36:06] [e493208d2907342b139e6792bbaea494]
-    D        [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 17:38:19] [e493208d2907342b139e6792bbaea494]
-    D          [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 17:39:21] [e493208d2907342b139e6792bbaea494]
-    D            [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 17:40:38] [e493208d2907342b139e6792bbaea494]
-    D              [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 18:43:34] [e493208d2907342b139e6792bbaea494]
-    D                [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 18:53:25] [e493208d2907342b139e6792bbaea494]
-    D                  [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 18:54:41] [e493208d2907342b139e6792bbaea494]
-    D                    [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 18:55:52] [e493208d2907342b139e6792bbaea494]
-    D                      [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 18:56:38] [e493208d2907342b139e6792bbaea494]
-    D                        [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 18:59:28] [e493208d2907342b139e6792bbaea494]
-    D                          [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 19:00:52] [e493208d2907342b139e6792bbaea494]
-    D                            [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 19:02:37] [e493208d2907342b139e6792bbaea494]
-    D                              [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 19:03:31] [e493208d2907342b139e6792bbaea494]
-    D                                [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 19:04:30] [e493208d2907342b139e6792bbaea494]
-    D                                  [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 19:05:26] [e493208d2907342b139e6792bbaea494]
-    D                                    [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 19:06:29] [e493208d2907342b139e6792bbaea494]
-    D                                      [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 19:07:30] [e493208d2907342b139e6792bbaea494]
-    D                                        [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 19:08:04] [e493208d2907342b139e6792bbaea494]
- RM D                                            [Central Tendency] [] [2014-12-15 20:23:02] [04df4205f362f56e0d1a9032a00a5d3d] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.47646
-3.73774
-3.55172
-0.649836
2.40434
0.82592
-4.31749
-0.424751
-5.81404
0.44423
0.220407
-4.36699
2.85689
3.25782
0.724056
-2.42275
-0.324008
-4.52202
-1.75119
-2.38242
-0.483089
-0.519659
-1.39055
-4.09972
-0.657976
2.3681
-0.50566
0.373386
-1.1749
1.49165
-1.68052
3.52016
-1.41162
3.43835
1.13295
2.77014
-3.29199
-2.87525
-3.56402
1.79151
2.13431
2.38214
-3.31951
-0.137976
4.47263
-2.74483
-0.643545
0.661732
-0.951047
2.2057
1.73074
2.20303
0.988048
1.34101
-0.763275
3.32594
-3.40044
-0.561716
3.44482
0.869345
0.88265
0.0877585
1.10985
2.70374
1.61699
2.8748
4.72299
-0.711078
-0.711078
0.00707875
1.71371
2.31116
-0.275245
-1.59487
1.62721
-0.427874
2.157
1.29386
1.11153
3.01825
-1.18495
-0.857501
-4.44894
-2.36863
-0.671242
3.28273
0.612779
-1.13723
-1.76586
-1.39315

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'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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269010&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269010&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269010&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'Gertrude Mary Cox' @ cox.wessa.net






Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean4.72222222042356e-080.2463131153371891.9171623134883e-07
Geometric MeanNaN
Harmonic Mean0.660726100307451
Quadratic Mean2.32371328266913
Winsorized Mean ( 1 / 30 )0.01157404722222220.2423097448887640.0477655045509434
Winsorized Mean ( 2 / 30 )-0.007967952777777790.238013155801414-0.0334769426965031
Winsorized Mean ( 3 / 30 )-0.007747619444444450.237029918982946-0.0326862510761853
Winsorized Mean ( 4 / 30 )-0.005835175000000030.236530257191004-0.0246698881965363
Winsorized Mean ( 5 / 30 )1.81583333333574e-050.2330838908151457.79047117750342e-05
Winsorized Mean ( 6 / 30 )0.02126949166666670.2280000385120660.0932872283946611
Winsorized Mean ( 7 / 30 )0.03284360277777780.2252245113053110.145826058573418
Winsorized Mean ( 8 / 30 )0.0126418250.2216919252869420.0570242916319001
Winsorized Mean ( 9 / 30 )0.0134248250.2168306458116180.0619138726896726
Winsorized Mean ( 10 / 30 )0.02042704722222220.2149552263951950.095029311753821
Winsorized Mean ( 11 / 30 )0.0131878250.2128103745753930.0619698406448125
Winsorized Mean ( 12 / 30 )0.0598998250.2021261659886090.296348692446755
Winsorized Mean ( 13 / 30 )0.03549160277777780.1928975153824110.183992016213466
Winsorized Mean ( 14 / 30 )0.08213960277777780.1845347005736320.445117381838994
Winsorized Mean ( 15 / 30 )0.08652126944444450.1831855641228550.472314889324021
Winsorized Mean ( 16 / 30 )0.07885015833333340.1814059684831310.43466132339888
Winsorized Mean ( 17 / 30 )0.1727864916666670.162303284256411.06459023585558
Winsorized Mean ( 18 / 30 )0.1751864916666670.1618350273010781.08250046104512
Winsorized Mean ( 19 / 30 )0.1803882694444440.1584881116015441.13818170726874
Winsorized Mean ( 20 / 30 )0.1943793805555560.155293202606691.25169278044873
Winsorized Mean ( 21 / 30 )0.1571510472222220.138889789210421.13148020538886
Winsorized Mean ( 22 / 30 )0.1468110472222220.1363653534548141.07660078973703
Winsorized Mean ( 23 / 30 )0.1431233805555560.1357140622176721.0545950671346
Winsorized Mean ( 24 / 30 )0.1748833805555560.1259061284043381.38899815896118
Winsorized Mean ( 25 / 30 )0.1748361583333330.1251999797504471.39645516462401
Winsorized Mean ( 26 / 30 )0.1495092694444440.119247140266321.25377656110276
Winsorized Mean ( 27 / 30 )0.2008071694444440.1120509857445581.792105335889
Winsorized Mean ( 28 / 30 )0.1877703694444440.1033775544971121.81635530418443
Winsorized Mean ( 29 / 30 )0.2029393027777780.09806948894010972.06934190206407
Winsorized Mean ( 30 / 30 )0.1667016361111110.08953972522916561.8617617564099
Trimmed Mean ( 1 / 30 )0.012398343750.2369489661283570.0523249539872805
Trimmed Mean ( 2 / 30 )0.01326097965116280.2307988875690590.0574568612129679
Trimmed Mean ( 3 / 30 )0.02463362202380950.2263385511070240.10883529077714
Trimmed Mean ( 4 / 30 )0.03648041768292680.2216028022977240.16462074172652
Trimmed Mean ( 5 / 30 )0.0483816781250.2162807432376820.223698501312393
Trimmed Mean ( 6 / 30 )0.05954249038461540.2111108144344510.282043771865146
Trimmed Mean ( 7 / 30 )0.06709637171052630.2064152830784410.325055251286934
Trimmed Mean ( 8 / 30 )0.0730476250.2015733603699940.362387295949816
Trimmed Mean ( 9 / 30 )0.082486031250.1966431503804350.41947065580682
Trimmed Mean ( 10 / 30 )0.09235191785714280.1918305161316720.481424539324873
Trimmed Mean ( 11 / 30 )0.1018713860294120.1864890238949280.546259420001085
Trimmed Mean ( 12 / 30 )0.1128652159090910.1805220023138660.625215843290156
Trimmed Mean ( 13 / 30 )0.1128652159090910.1754807872752730.643177054659789
Trimmed Mean ( 14 / 30 )0.1284049072580650.171108336923250.750430455739046
Trimmed Mean ( 15 / 30 )0.1333619041666670.1673492631415970.79690762697788
Trimmed Mean ( 16 / 30 )0.1382074870689660.1629802891770270.848001238473975
Trimmed Mean ( 17 / 30 )0.144169718750.1579165531706430.912948743215105
Trimmed Mean ( 18 / 30 )0.1413641527777780.1551687823922570.911034749376444
Trimmed Mean ( 19 / 30 )0.1381120048076920.1517576774929740.910082488670709
Trimmed Mean ( 20 / 30 )0.1341068850.1480381476304470.90589410328732
Trimmed Mean ( 21 / 30 )0.1284563385416670.1438773519756630.892818339910751
Trimmed Mean ( 22 / 30 )0.1257829184782610.141699230189170.887675383347809
Trimmed Mean ( 23 / 30 )0.1238278238636360.1392361335404640.889336846082778
Trimmed Mean ( 24 / 30 )0.1220301011904760.1360177723064950.897162915707077
Trimmed Mean ( 25 / 30 )0.117075106250.1336942819870830.875692696126762
Trimmed Mean ( 26 / 30 )0.117075106250.130551976714190.896770077302665
Trimmed Mean ( 27 / 30 )0.1079581736111110.1275502302234910.846397324583018
Trimmed Mean ( 28 / 30 )0.09885533088235290.1248953595668040.791505234663877
Trimmed Mean ( 29 / 30 )0.08992413281250.1231385286851360.730268046668276
Trimmed Mean ( 30 / 30 )0.07823290833333330.1215809724712560.643463419835936
Median-0.065448625
Midrange-0.545525
Midmean - Weighted Average at Xnp0.0901172055555555
Midmean - Weighted Average at X(n+1)p0.125782918478261
Midmean - Empirical Distribution Function0.125782918478261
Midmean - Empirical Distribution Function - Averaging0.125782918478261
Midmean - Empirical Distribution Function - Interpolation0.123827823863636
Midmean - Closest Observation0.125782918478261
Midmean - True Basic - Statistics Graphics Toolkit0.125782918478261
Midmean - MS Excel (old versions)0.125782918478261
Number of observations90

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 4.72222222042356e-08 & 0.246313115337189 & 1.9171623134883e-07 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 0.660726100307451 &  &  \tabularnewline
Quadratic Mean & 2.32371328266913 &  &  \tabularnewline
Winsorized Mean ( 1 / 30 ) & 0.0115740472222222 & 0.242309744888764 & 0.0477655045509434 \tabularnewline
Winsorized Mean ( 2 / 30 ) & -0.00796795277777779 & 0.238013155801414 & -0.0334769426965031 \tabularnewline
Winsorized Mean ( 3 / 30 ) & -0.00774761944444445 & 0.237029918982946 & -0.0326862510761853 \tabularnewline
Winsorized Mean ( 4 / 30 ) & -0.00583517500000003 & 0.236530257191004 & -0.0246698881965363 \tabularnewline
Winsorized Mean ( 5 / 30 ) & 1.81583333333574e-05 & 0.233083890815145 & 7.79047117750342e-05 \tabularnewline
Winsorized Mean ( 6 / 30 ) & 0.0212694916666667 & 0.228000038512066 & 0.0932872283946611 \tabularnewline
Winsorized Mean ( 7 / 30 ) & 0.0328436027777778 & 0.225224511305311 & 0.145826058573418 \tabularnewline
Winsorized Mean ( 8 / 30 ) & 0.012641825 & 0.221691925286942 & 0.0570242916319001 \tabularnewline
Winsorized Mean ( 9 / 30 ) & 0.013424825 & 0.216830645811618 & 0.0619138726896726 \tabularnewline
Winsorized Mean ( 10 / 30 ) & 0.0204270472222222 & 0.214955226395195 & 0.095029311753821 \tabularnewline
Winsorized Mean ( 11 / 30 ) & 0.013187825 & 0.212810374575393 & 0.0619698406448125 \tabularnewline
Winsorized Mean ( 12 / 30 ) & 0.059899825 & 0.202126165988609 & 0.296348692446755 \tabularnewline
Winsorized Mean ( 13 / 30 ) & 0.0354916027777778 & 0.192897515382411 & 0.183992016213466 \tabularnewline
Winsorized Mean ( 14 / 30 ) & 0.0821396027777778 & 0.184534700573632 & 0.445117381838994 \tabularnewline
Winsorized Mean ( 15 / 30 ) & 0.0865212694444445 & 0.183185564122855 & 0.472314889324021 \tabularnewline
Winsorized Mean ( 16 / 30 ) & 0.0788501583333334 & 0.181405968483131 & 0.43466132339888 \tabularnewline
Winsorized Mean ( 17 / 30 ) & 0.172786491666667 & 0.16230328425641 & 1.06459023585558 \tabularnewline
Winsorized Mean ( 18 / 30 ) & 0.175186491666667 & 0.161835027301078 & 1.08250046104512 \tabularnewline
Winsorized Mean ( 19 / 30 ) & 0.180388269444444 & 0.158488111601544 & 1.13818170726874 \tabularnewline
Winsorized Mean ( 20 / 30 ) & 0.194379380555556 & 0.15529320260669 & 1.25169278044873 \tabularnewline
Winsorized Mean ( 21 / 30 ) & 0.157151047222222 & 0.13888978921042 & 1.13148020538886 \tabularnewline
Winsorized Mean ( 22 / 30 ) & 0.146811047222222 & 0.136365353454814 & 1.07660078973703 \tabularnewline
Winsorized Mean ( 23 / 30 ) & 0.143123380555556 & 0.135714062217672 & 1.0545950671346 \tabularnewline
Winsorized Mean ( 24 / 30 ) & 0.174883380555556 & 0.125906128404338 & 1.38899815896118 \tabularnewline
Winsorized Mean ( 25 / 30 ) & 0.174836158333333 & 0.125199979750447 & 1.39645516462401 \tabularnewline
Winsorized Mean ( 26 / 30 ) & 0.149509269444444 & 0.11924714026632 & 1.25377656110276 \tabularnewline
Winsorized Mean ( 27 / 30 ) & 0.200807169444444 & 0.112050985744558 & 1.792105335889 \tabularnewline
Winsorized Mean ( 28 / 30 ) & 0.187770369444444 & 0.103377554497112 & 1.81635530418443 \tabularnewline
Winsorized Mean ( 29 / 30 ) & 0.202939302777778 & 0.0980694889401097 & 2.06934190206407 \tabularnewline
Winsorized Mean ( 30 / 30 ) & 0.166701636111111 & 0.0895397252291656 & 1.8617617564099 \tabularnewline
Trimmed Mean ( 1 / 30 ) & 0.01239834375 & 0.236948966128357 & 0.0523249539872805 \tabularnewline
Trimmed Mean ( 2 / 30 ) & 0.0132609796511628 & 0.230798887569059 & 0.0574568612129679 \tabularnewline
Trimmed Mean ( 3 / 30 ) & 0.0246336220238095 & 0.226338551107024 & 0.10883529077714 \tabularnewline
Trimmed Mean ( 4 / 30 ) & 0.0364804176829268 & 0.221602802297724 & 0.16462074172652 \tabularnewline
Trimmed Mean ( 5 / 30 ) & 0.048381678125 & 0.216280743237682 & 0.223698501312393 \tabularnewline
Trimmed Mean ( 6 / 30 ) & 0.0595424903846154 & 0.211110814434451 & 0.282043771865146 \tabularnewline
Trimmed Mean ( 7 / 30 ) & 0.0670963717105263 & 0.206415283078441 & 0.325055251286934 \tabularnewline
Trimmed Mean ( 8 / 30 ) & 0.073047625 & 0.201573360369994 & 0.362387295949816 \tabularnewline
Trimmed Mean ( 9 / 30 ) & 0.08248603125 & 0.196643150380435 & 0.41947065580682 \tabularnewline
Trimmed Mean ( 10 / 30 ) & 0.0923519178571428 & 0.191830516131672 & 0.481424539324873 \tabularnewline
Trimmed Mean ( 11 / 30 ) & 0.101871386029412 & 0.186489023894928 & 0.546259420001085 \tabularnewline
Trimmed Mean ( 12 / 30 ) & 0.112865215909091 & 0.180522002313866 & 0.625215843290156 \tabularnewline
Trimmed Mean ( 13 / 30 ) & 0.112865215909091 & 0.175480787275273 & 0.643177054659789 \tabularnewline
Trimmed Mean ( 14 / 30 ) & 0.128404907258065 & 0.17110833692325 & 0.750430455739046 \tabularnewline
Trimmed Mean ( 15 / 30 ) & 0.133361904166667 & 0.167349263141597 & 0.79690762697788 \tabularnewline
Trimmed Mean ( 16 / 30 ) & 0.138207487068966 & 0.162980289177027 & 0.848001238473975 \tabularnewline
Trimmed Mean ( 17 / 30 ) & 0.14416971875 & 0.157916553170643 & 0.912948743215105 \tabularnewline
Trimmed Mean ( 18 / 30 ) & 0.141364152777778 & 0.155168782392257 & 0.911034749376444 \tabularnewline
Trimmed Mean ( 19 / 30 ) & 0.138112004807692 & 0.151757677492974 & 0.910082488670709 \tabularnewline
Trimmed Mean ( 20 / 30 ) & 0.134106885 & 0.148038147630447 & 0.90589410328732 \tabularnewline
Trimmed Mean ( 21 / 30 ) & 0.128456338541667 & 0.143877351975663 & 0.892818339910751 \tabularnewline
Trimmed Mean ( 22 / 30 ) & 0.125782918478261 & 0.14169923018917 & 0.887675383347809 \tabularnewline
Trimmed Mean ( 23 / 30 ) & 0.123827823863636 & 0.139236133540464 & 0.889336846082778 \tabularnewline
Trimmed Mean ( 24 / 30 ) & 0.122030101190476 & 0.136017772306495 & 0.897162915707077 \tabularnewline
Trimmed Mean ( 25 / 30 ) & 0.11707510625 & 0.133694281987083 & 0.875692696126762 \tabularnewline
Trimmed Mean ( 26 / 30 ) & 0.11707510625 & 0.13055197671419 & 0.896770077302665 \tabularnewline
Trimmed Mean ( 27 / 30 ) & 0.107958173611111 & 0.127550230223491 & 0.846397324583018 \tabularnewline
Trimmed Mean ( 28 / 30 ) & 0.0988553308823529 & 0.124895359566804 & 0.791505234663877 \tabularnewline
Trimmed Mean ( 29 / 30 ) & 0.0899241328125 & 0.123138528685136 & 0.730268046668276 \tabularnewline
Trimmed Mean ( 30 / 30 ) & 0.0782329083333333 & 0.121580972471256 & 0.643463419835936 \tabularnewline
Median & -0.065448625 &  &  \tabularnewline
Midrange & -0.545525 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 0.0901172055555555 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 0.125782918478261 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 0.125782918478261 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 0.125782918478261 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 0.123827823863636 &  &  \tabularnewline
Midmean - Closest Observation & 0.125782918478261 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 0.125782918478261 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 0.125782918478261 &  &  \tabularnewline
Number of observations & 90 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269010&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]4.72222222042356e-08[/C][C]0.246313115337189[/C][C]1.9171623134883e-07[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]0.660726100307451[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]2.32371328266913[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 30 )[/C][C]0.0115740472222222[/C][C]0.242309744888764[/C][C]0.0477655045509434[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 30 )[/C][C]-0.00796795277777779[/C][C]0.238013155801414[/C][C]-0.0334769426965031[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 30 )[/C][C]-0.00774761944444445[/C][C]0.237029918982946[/C][C]-0.0326862510761853[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 30 )[/C][C]-0.00583517500000003[/C][C]0.236530257191004[/C][C]-0.0246698881965363[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 30 )[/C][C]1.81583333333574e-05[/C][C]0.233083890815145[/C][C]7.79047117750342e-05[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 30 )[/C][C]0.0212694916666667[/C][C]0.228000038512066[/C][C]0.0932872283946611[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 30 )[/C][C]0.0328436027777778[/C][C]0.225224511305311[/C][C]0.145826058573418[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 30 )[/C][C]0.012641825[/C][C]0.221691925286942[/C][C]0.0570242916319001[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 30 )[/C][C]0.013424825[/C][C]0.216830645811618[/C][C]0.0619138726896726[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 30 )[/C][C]0.0204270472222222[/C][C]0.214955226395195[/C][C]0.095029311753821[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 30 )[/C][C]0.013187825[/C][C]0.212810374575393[/C][C]0.0619698406448125[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 30 )[/C][C]0.059899825[/C][C]0.202126165988609[/C][C]0.296348692446755[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 30 )[/C][C]0.0354916027777778[/C][C]0.192897515382411[/C][C]0.183992016213466[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 30 )[/C][C]0.0821396027777778[/C][C]0.184534700573632[/C][C]0.445117381838994[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 30 )[/C][C]0.0865212694444445[/C][C]0.183185564122855[/C][C]0.472314889324021[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 30 )[/C][C]0.0788501583333334[/C][C]0.181405968483131[/C][C]0.43466132339888[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 30 )[/C][C]0.172786491666667[/C][C]0.16230328425641[/C][C]1.06459023585558[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 30 )[/C][C]0.175186491666667[/C][C]0.161835027301078[/C][C]1.08250046104512[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 30 )[/C][C]0.180388269444444[/C][C]0.158488111601544[/C][C]1.13818170726874[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 30 )[/C][C]0.194379380555556[/C][C]0.15529320260669[/C][C]1.25169278044873[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 30 )[/C][C]0.157151047222222[/C][C]0.13888978921042[/C][C]1.13148020538886[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 30 )[/C][C]0.146811047222222[/C][C]0.136365353454814[/C][C]1.07660078973703[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 30 )[/C][C]0.143123380555556[/C][C]0.135714062217672[/C][C]1.0545950671346[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 30 )[/C][C]0.174883380555556[/C][C]0.125906128404338[/C][C]1.38899815896118[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 30 )[/C][C]0.174836158333333[/C][C]0.125199979750447[/C][C]1.39645516462401[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 30 )[/C][C]0.149509269444444[/C][C]0.11924714026632[/C][C]1.25377656110276[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 30 )[/C][C]0.200807169444444[/C][C]0.112050985744558[/C][C]1.792105335889[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 30 )[/C][C]0.187770369444444[/C][C]0.103377554497112[/C][C]1.81635530418443[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 30 )[/C][C]0.202939302777778[/C][C]0.0980694889401097[/C][C]2.06934190206407[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 30 )[/C][C]0.166701636111111[/C][C]0.0895397252291656[/C][C]1.8617617564099[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 30 )[/C][C]0.01239834375[/C][C]0.236948966128357[/C][C]0.0523249539872805[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 30 )[/C][C]0.0132609796511628[/C][C]0.230798887569059[/C][C]0.0574568612129679[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 30 )[/C][C]0.0246336220238095[/C][C]0.226338551107024[/C][C]0.10883529077714[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 30 )[/C][C]0.0364804176829268[/C][C]0.221602802297724[/C][C]0.16462074172652[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 30 )[/C][C]0.048381678125[/C][C]0.216280743237682[/C][C]0.223698501312393[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 30 )[/C][C]0.0595424903846154[/C][C]0.211110814434451[/C][C]0.282043771865146[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 30 )[/C][C]0.0670963717105263[/C][C]0.206415283078441[/C][C]0.325055251286934[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 30 )[/C][C]0.073047625[/C][C]0.201573360369994[/C][C]0.362387295949816[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 30 )[/C][C]0.08248603125[/C][C]0.196643150380435[/C][C]0.41947065580682[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 30 )[/C][C]0.0923519178571428[/C][C]0.191830516131672[/C][C]0.481424539324873[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 30 )[/C][C]0.101871386029412[/C][C]0.186489023894928[/C][C]0.546259420001085[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 30 )[/C][C]0.112865215909091[/C][C]0.180522002313866[/C][C]0.625215843290156[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 30 )[/C][C]0.112865215909091[/C][C]0.175480787275273[/C][C]0.643177054659789[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 30 )[/C][C]0.128404907258065[/C][C]0.17110833692325[/C][C]0.750430455739046[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 30 )[/C][C]0.133361904166667[/C][C]0.167349263141597[/C][C]0.79690762697788[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 30 )[/C][C]0.138207487068966[/C][C]0.162980289177027[/C][C]0.848001238473975[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 30 )[/C][C]0.14416971875[/C][C]0.157916553170643[/C][C]0.912948743215105[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 30 )[/C][C]0.141364152777778[/C][C]0.155168782392257[/C][C]0.911034749376444[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 30 )[/C][C]0.138112004807692[/C][C]0.151757677492974[/C][C]0.910082488670709[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 30 )[/C][C]0.134106885[/C][C]0.148038147630447[/C][C]0.90589410328732[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 30 )[/C][C]0.128456338541667[/C][C]0.143877351975663[/C][C]0.892818339910751[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 30 )[/C][C]0.125782918478261[/C][C]0.14169923018917[/C][C]0.887675383347809[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 30 )[/C][C]0.123827823863636[/C][C]0.139236133540464[/C][C]0.889336846082778[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 30 )[/C][C]0.122030101190476[/C][C]0.136017772306495[/C][C]0.897162915707077[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 30 )[/C][C]0.11707510625[/C][C]0.133694281987083[/C][C]0.875692696126762[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 30 )[/C][C]0.11707510625[/C][C]0.13055197671419[/C][C]0.896770077302665[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 30 )[/C][C]0.107958173611111[/C][C]0.127550230223491[/C][C]0.846397324583018[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 30 )[/C][C]0.0988553308823529[/C][C]0.124895359566804[/C][C]0.791505234663877[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 30 )[/C][C]0.0899241328125[/C][C]0.123138528685136[/C][C]0.730268046668276[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 30 )[/C][C]0.0782329083333333[/C][C]0.121580972471256[/C][C]0.643463419835936[/C][/ROW]
[ROW][C]Median[/C][C]-0.065448625[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-0.545525[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]0.0901172055555555[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]0.125782918478261[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]0.125782918478261[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]0.125782918478261[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]0.123827823863636[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]0.125782918478261[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]0.125782918478261[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]0.125782918478261[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]90[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269010&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269010&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 Mean4.72222222042356e-080.2463131153371891.9171623134883e-07
Geometric MeanNaN
Harmonic Mean0.660726100307451
Quadratic Mean2.32371328266913
Winsorized Mean ( 1 / 30 )0.01157404722222220.2423097448887640.0477655045509434
Winsorized Mean ( 2 / 30 )-0.007967952777777790.238013155801414-0.0334769426965031
Winsorized Mean ( 3 / 30 )-0.007747619444444450.237029918982946-0.0326862510761853
Winsorized Mean ( 4 / 30 )-0.005835175000000030.236530257191004-0.0246698881965363
Winsorized Mean ( 5 / 30 )1.81583333333574e-050.2330838908151457.79047117750342e-05
Winsorized Mean ( 6 / 30 )0.02126949166666670.2280000385120660.0932872283946611
Winsorized Mean ( 7 / 30 )0.03284360277777780.2252245113053110.145826058573418
Winsorized Mean ( 8 / 30 )0.0126418250.2216919252869420.0570242916319001
Winsorized Mean ( 9 / 30 )0.0134248250.2168306458116180.0619138726896726
Winsorized Mean ( 10 / 30 )0.02042704722222220.2149552263951950.095029311753821
Winsorized Mean ( 11 / 30 )0.0131878250.2128103745753930.0619698406448125
Winsorized Mean ( 12 / 30 )0.0598998250.2021261659886090.296348692446755
Winsorized Mean ( 13 / 30 )0.03549160277777780.1928975153824110.183992016213466
Winsorized Mean ( 14 / 30 )0.08213960277777780.1845347005736320.445117381838994
Winsorized Mean ( 15 / 30 )0.08652126944444450.1831855641228550.472314889324021
Winsorized Mean ( 16 / 30 )0.07885015833333340.1814059684831310.43466132339888
Winsorized Mean ( 17 / 30 )0.1727864916666670.162303284256411.06459023585558
Winsorized Mean ( 18 / 30 )0.1751864916666670.1618350273010781.08250046104512
Winsorized Mean ( 19 / 30 )0.1803882694444440.1584881116015441.13818170726874
Winsorized Mean ( 20 / 30 )0.1943793805555560.155293202606691.25169278044873
Winsorized Mean ( 21 / 30 )0.1571510472222220.138889789210421.13148020538886
Winsorized Mean ( 22 / 30 )0.1468110472222220.1363653534548141.07660078973703
Winsorized Mean ( 23 / 30 )0.1431233805555560.1357140622176721.0545950671346
Winsorized Mean ( 24 / 30 )0.1748833805555560.1259061284043381.38899815896118
Winsorized Mean ( 25 / 30 )0.1748361583333330.1251999797504471.39645516462401
Winsorized Mean ( 26 / 30 )0.1495092694444440.119247140266321.25377656110276
Winsorized Mean ( 27 / 30 )0.2008071694444440.1120509857445581.792105335889
Winsorized Mean ( 28 / 30 )0.1877703694444440.1033775544971121.81635530418443
Winsorized Mean ( 29 / 30 )0.2029393027777780.09806948894010972.06934190206407
Winsorized Mean ( 30 / 30 )0.1667016361111110.08953972522916561.8617617564099
Trimmed Mean ( 1 / 30 )0.012398343750.2369489661283570.0523249539872805
Trimmed Mean ( 2 / 30 )0.01326097965116280.2307988875690590.0574568612129679
Trimmed Mean ( 3 / 30 )0.02463362202380950.2263385511070240.10883529077714
Trimmed Mean ( 4 / 30 )0.03648041768292680.2216028022977240.16462074172652
Trimmed Mean ( 5 / 30 )0.0483816781250.2162807432376820.223698501312393
Trimmed Mean ( 6 / 30 )0.05954249038461540.2111108144344510.282043771865146
Trimmed Mean ( 7 / 30 )0.06709637171052630.2064152830784410.325055251286934
Trimmed Mean ( 8 / 30 )0.0730476250.2015733603699940.362387295949816
Trimmed Mean ( 9 / 30 )0.082486031250.1966431503804350.41947065580682
Trimmed Mean ( 10 / 30 )0.09235191785714280.1918305161316720.481424539324873
Trimmed Mean ( 11 / 30 )0.1018713860294120.1864890238949280.546259420001085
Trimmed Mean ( 12 / 30 )0.1128652159090910.1805220023138660.625215843290156
Trimmed Mean ( 13 / 30 )0.1128652159090910.1754807872752730.643177054659789
Trimmed Mean ( 14 / 30 )0.1284049072580650.171108336923250.750430455739046
Trimmed Mean ( 15 / 30 )0.1333619041666670.1673492631415970.79690762697788
Trimmed Mean ( 16 / 30 )0.1382074870689660.1629802891770270.848001238473975
Trimmed Mean ( 17 / 30 )0.144169718750.1579165531706430.912948743215105
Trimmed Mean ( 18 / 30 )0.1413641527777780.1551687823922570.911034749376444
Trimmed Mean ( 19 / 30 )0.1381120048076920.1517576774929740.910082488670709
Trimmed Mean ( 20 / 30 )0.1341068850.1480381476304470.90589410328732
Trimmed Mean ( 21 / 30 )0.1284563385416670.1438773519756630.892818339910751
Trimmed Mean ( 22 / 30 )0.1257829184782610.141699230189170.887675383347809
Trimmed Mean ( 23 / 30 )0.1238278238636360.1392361335404640.889336846082778
Trimmed Mean ( 24 / 30 )0.1220301011904760.1360177723064950.897162915707077
Trimmed Mean ( 25 / 30 )0.117075106250.1336942819870830.875692696126762
Trimmed Mean ( 26 / 30 )0.117075106250.130551976714190.896770077302665
Trimmed Mean ( 27 / 30 )0.1079581736111110.1275502302234910.846397324583018
Trimmed Mean ( 28 / 30 )0.09885533088235290.1248953595668040.791505234663877
Trimmed Mean ( 29 / 30 )0.08992413281250.1231385286851360.730268046668276
Trimmed Mean ( 30 / 30 )0.07823290833333330.1215809724712560.643463419835936
Median-0.065448625
Midrange-0.545525
Midmean - Weighted Average at Xnp0.0901172055555555
Midmean - Weighted Average at X(n+1)p0.125782918478261
Midmean - Empirical Distribution Function0.125782918478261
Midmean - Empirical Distribution Function - Averaging0.125782918478261
Midmean - Empirical Distribution Function - Interpolation0.123827823863636
Midmean - Closest Observation0.125782918478261
Midmean - True Basic - Statistics Graphics Toolkit0.125782918478261
Midmean - MS Excel (old versions)0.125782918478261
Number of observations90


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = Pearson Chi-Squared ;
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')