Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 05 Aug 2014 13:32:00 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Aug/05/t14072419795ck32hrpwkteqqb.htm/, Retrieved Thu, 16 May 2024 15:17:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=235406, Retrieved Thu, 16 May 2024 15:17:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsInes Van Dessel
Estimated Impact136
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [Tijdreeks 1 - Stap 3] [2014-08-03 19:11:32] [ae3d1feb555b13e324db089723206180]
- R P   [Histogram] [Tijdreeks 1 - Stap 5] [2014-08-04 09:44:37] [74be16979710d4c4e7c6647856088456]
-   P     [Histogram] [Tijdreeks 1 - Stap 5] [2014-08-04 09:47:49] [74be16979710d4c4e7c6647856088456]
- RMP       [(Partial) Autocorrelation Function] [Tijdreeks 1 - Sta...] [2014-08-04 16:49:46] [ae3d1feb555b13e324db089723206180]
- R P         [(Partial) Autocorrelation Function] [Tijdreeks 1 - Sta...] [2014-08-05 08:15:03] [74be16979710d4c4e7c6647856088456]
- RMPD          [Harrell-Davis Quantiles] [Tijdreeks 2 - Stap 6] [2014-08-05 08:50:48] [ae3d1feb555b13e324db089723206180]
- RMP               [Central Tendency] [Tijdreeks 2 - Stap 9] [2014-08-05 12:32:00] [188bf81caccb86647293be436f272d1b] [Current]
Feedback Forum

Post a new message
Dataseries X:
340
307
380
347
313
333
347
333
387
307
353
407
307
253
380
320
353
353
387
280
387
307
347
427
253
240
407
293
347
360
387
240
333
353
313
440
273
240
407
240
360
373
387
320
373
373
260
420
253
293
413
207
333
440
280
367
380
373
193
373
213
293
407
167
340
447
233
393
333
353
200
413
187
300
413
213
373
453
247
447
340
320
187
380
160
307
400
213
380
453
260
467
380
300
180
427
153
327
393
207
380
440
247
400
360
340
220
393




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=235406&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=235406&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235406&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean329.5462962962967.3776906404674944.6679472420132
Geometric Mean319.486628425179
Harmonic Mean308.113753756363
Quadratic Mean338.267358099412
Winsorized Mean ( 1 / 36 )329.4814814814817.3419717067695644.8764302888402
Winsorized Mean ( 2 / 36 )329.6111111111117.3145212466996445.0625680060515
Winsorized Mean ( 3 / 36 )329.8055555555567.2161703816045745.7036818859342
Winsorized Mean ( 4 / 36 )330.0648148148157.1668329709525146.054486849712
Winsorized Mean ( 5 / 36 )329.7407407407417.1186645011611446.3205901453785
Winsorized Mean ( 6 / 36 )330.0740740740747.0571727368456946.7714319008728
Winsorized Mean ( 7 / 36 )330.5277777777786.9763167863854747.378550587441
Winsorized Mean ( 8 / 36 )330.0833333333336.7514869585090148.8904644801726
Winsorized Mean ( 9 / 36 )330.0833333333336.7514869585090148.8904644801726
Winsorized Mean ( 10 / 36 )329.9907407407416.5729589560247350.2042904799023
Winsorized Mean ( 11 / 36 )329.2777777777786.4843026545742550.780753971361
Winsorized Mean ( 12 / 36 )329.2777777777786.4843026545742550.780753971361
Winsorized Mean ( 13 / 36 )330.120370370376.3453419190245952.025623612276
Winsorized Mean ( 14 / 36 )331.0277777777785.9858558671817855.3016619716288
Winsorized Mean ( 15 / 36 )3325.839849498053656.8507801631967
Winsorized Mean ( 16 / 36 )3325.839849498053656.8507801631967
Winsorized Mean ( 17 / 36 )3325.839849498053656.8507801631967
Winsorized Mean ( 18 / 36 )330.8333333333335.7036770126098958.0035181869372
Winsorized Mean ( 19 / 36 )332.0648148148155.5233585159107260.1200906763993
Winsorized Mean ( 20 / 36 )330.7685185185195.378710878711361.4958725198794
Winsorized Mean ( 21 / 36 )331.9351851851855.2111901514686963.6966173824293
Winsorized Mean ( 22 / 36 )331.9351851851855.2111901514686963.6966173824293
Winsorized Mean ( 23 / 36 )330.6574074074075.0748833814768365.1556661605855
Winsorized Mean ( 24 / 36 )332.2129629629634.8554753135235368.4202763914131
Winsorized Mean ( 25 / 36 )332.2129629629634.8554753135235368.4202763914131
Winsorized Mean ( 26 / 36 )335.3425925925934.4317086873365875.6689160437869
Winsorized Mean ( 27 / 36 )337.0925925925934.2055514136032880.1541960709915
Winsorized Mean ( 28 / 36 )335.2777777777784.0101945489909783.6063621557062
Winsorized Mean ( 29 / 36 )338.7685185185193.5756330478509194.7436479037274
Winsorized Mean ( 30 / 36 )338.7685185185193.5756330478509194.7436479037274
Winsorized Mean ( 31 / 36 )338.7685185185193.5756330478509194.7436479037274
Winsorized Mean ( 32 / 36 )340.8425925925933.33261056642409102.27495406351
Winsorized Mean ( 33 / 36 )340.8425925925933.33261056642409102.27495406351
Winsorized Mean ( 34 / 36 )343.0462962962963.08589350249933111.165954372196
Winsorized Mean ( 35 / 36 )340.7777777777782.83833268952813120.062661799675
Winsorized Mean ( 36 / 36 )340.7777777777782.83833268952813120.062661799675
Trimmed Mean ( 1 / 36 )329.9150943396237.2121007169850945.744659882889
Trimmed Mean ( 2 / 36 )330.3653846153857.0663009931627146.7522378306618
Trimmed Mean ( 3 / 36 )330.7647058823536.918657884380547.8076400668812
Trimmed Mean ( 4 / 36 )331.116.7933552650789448.7402744417125
Trimmed Mean ( 5 / 36 )331.3979591836736.6681386588746249.6987204581621
Trimmed Mean ( 6 / 36 )331.7708333333336.5394967207814350.733389356863
Trimmed Mean ( 7 / 36 )332.0957446808516.408607607269551.8202650298239
Trimmed Mean ( 8 / 36 )332.3586956521746.2777065100033152.9426941387865
Trimmed Mean ( 9 / 36 )332.76.1732670416514953.8936672843161
Trimmed Mean ( 10 / 36 )333.0568181818186.0534746525880555.0191150200697
Trimmed Mean ( 11 / 36 )333.4418604651165.9473891465967556.0652501872894
Trimmed Mean ( 12 / 36 )333.9285714285715.8390829556647157.1885301106426
Trimmed Mean ( 13 / 36 )334.4390243902445.713370888877658.5362005889215
Trimmed Mean ( 14 / 36 )334.88755.5905660180252559.9022529955369
Trimmed Mean ( 15 / 36 )335.2692307692315.5038409703479660.9155011155845
Trimmed Mean ( 16 / 36 )335.5789473684215.4242232254269661.8667288240163
Trimmed Mean ( 17 / 36 )335.9054054054055.3299558920108163.0221735810049
Trimmed Mean ( 18 / 36 )336.255.2182698641970364.4370660680159
Trimmed Mean ( 19 / 36 )336.7142857142865.1046661095427465.9620587299191
Trimmed Mean ( 20 / 36 )337.1029411764714.9976789918400667.4518995171306
Trimmed Mean ( 21 / 36 )337.6212121212124.8888229477274269.0598157738881
Trimmed Mean ( 22 / 36 )338.0781254.7843528388961470.6632926926857
Trimmed Mean ( 23 / 36 )338.5645161290324.6570157106583772.6998870444371
Trimmed Mean ( 24 / 36 )339.1833333333334.5202927050534875.0357013283989
Trimmed Mean ( 25 / 36 )339.7241379310344.3915852759801777.3579736204053
Trimmed Mean ( 26 / 36 )340.3035714285714.2315235998256380.4210501018107
Trimmed Mean ( 27 / 36 )340.6851851851854.1136734103081882.8177522142339
Trimmed Mean ( 28 / 36 )340.9615384615384.0079071110249685.0722157516127
Trimmed Mean ( 29 / 36 )341.43.9044715339189987.4382095077873
Trimmed Mean ( 30 / 36 )341.6041666666673.8543679265067888.6278043975587
Trimmed Mean ( 31 / 36 )341.8260869565223.7863605137293290.2782726887897
Trimmed Mean ( 32 / 36 )342.0681818181823.6950909848234392.5736830901141
Trimmed Mean ( 33 / 36 )342.1666666666673.624653720761794.3998221697056
Trimmed Mean ( 34 / 36 )342.2753.5277267140795997.0242390471854
Trimmed Mean ( 35 / 36 )342.2105263157893.4511749694287499.157686685597
Trimmed Mean ( 36 / 36 )342.3333333333333.39911286278762100.712552701938
Median343.5
Midrange310
Midmean - Weighted Average at Xnp342.677966101695
Midmean - Weighted Average at X(n+1)p343.879310344828
Midmean - Empirical Distribution Function342.677966101695
Midmean - Empirical Distribution Function - Averaging343.879310344828
Midmean - Empirical Distribution Function - Interpolation343.879310344828
Midmean - Closest Observation342.677966101695
Midmean - True Basic - Statistics Graphics Toolkit343.879310344828
Midmean - MS Excel (old versions)342.677966101695
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 329.546296296296 & 7.37769064046749 & 44.6679472420132 \tabularnewline
Geometric Mean & 319.486628425179 &  &  \tabularnewline
Harmonic Mean & 308.113753756363 &  &  \tabularnewline
Quadratic Mean & 338.267358099412 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 329.481481481481 & 7.34197170676956 & 44.8764302888402 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 329.611111111111 & 7.31452124669964 & 45.0625680060515 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 329.805555555556 & 7.21617038160457 & 45.7036818859342 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 330.064814814815 & 7.16683297095251 & 46.054486849712 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 329.740740740741 & 7.11866450116114 & 46.3205901453785 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 330.074074074074 & 7.05717273684569 & 46.7714319008728 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 330.527777777778 & 6.97631678638547 & 47.378550587441 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 330.083333333333 & 6.75148695850901 & 48.8904644801726 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 330.083333333333 & 6.75148695850901 & 48.8904644801726 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 329.990740740741 & 6.57295895602473 & 50.2042904799023 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 329.277777777778 & 6.48430265457425 & 50.780753971361 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 329.277777777778 & 6.48430265457425 & 50.780753971361 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 330.12037037037 & 6.34534191902459 & 52.025623612276 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 331.027777777778 & 5.98585586718178 & 55.3016619716288 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 332 & 5.8398494980536 & 56.8507801631967 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 332 & 5.8398494980536 & 56.8507801631967 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 332 & 5.8398494980536 & 56.8507801631967 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 330.833333333333 & 5.70367701260989 & 58.0035181869372 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 332.064814814815 & 5.52335851591072 & 60.1200906763993 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 330.768518518519 & 5.3787108787113 & 61.4958725198794 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 331.935185185185 & 5.21119015146869 & 63.6966173824293 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 331.935185185185 & 5.21119015146869 & 63.6966173824293 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 330.657407407407 & 5.07488338147683 & 65.1556661605855 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 332.212962962963 & 4.85547531352353 & 68.4202763914131 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 332.212962962963 & 4.85547531352353 & 68.4202763914131 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 335.342592592593 & 4.43170868733658 & 75.6689160437869 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 337.092592592593 & 4.20555141360328 & 80.1541960709915 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 335.277777777778 & 4.01019454899097 & 83.6063621557062 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 338.768518518519 & 3.57563304785091 & 94.7436479037274 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 338.768518518519 & 3.57563304785091 & 94.7436479037274 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 338.768518518519 & 3.57563304785091 & 94.7436479037274 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 340.842592592593 & 3.33261056642409 & 102.27495406351 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 340.842592592593 & 3.33261056642409 & 102.27495406351 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 343.046296296296 & 3.08589350249933 & 111.165954372196 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 340.777777777778 & 2.83833268952813 & 120.062661799675 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 340.777777777778 & 2.83833268952813 & 120.062661799675 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 329.915094339623 & 7.21210071698509 & 45.744659882889 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 330.365384615385 & 7.06630099316271 & 46.7522378306618 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 330.764705882353 & 6.9186578843805 & 47.8076400668812 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 331.11 & 6.79335526507894 & 48.7402744417125 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 331.397959183673 & 6.66813865887462 & 49.6987204581621 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 331.770833333333 & 6.53949672078143 & 50.733389356863 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 332.095744680851 & 6.4086076072695 & 51.8202650298239 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 332.358695652174 & 6.27770651000331 & 52.9426941387865 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 332.7 & 6.17326704165149 & 53.8936672843161 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 333.056818181818 & 6.05347465258805 & 55.0191150200697 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 333.441860465116 & 5.94738914659675 & 56.0652501872894 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 333.928571428571 & 5.83908295566471 & 57.1885301106426 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 334.439024390244 & 5.7133708888776 & 58.5362005889215 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 334.8875 & 5.59056601802525 & 59.9022529955369 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 335.269230769231 & 5.50384097034796 & 60.9155011155845 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 335.578947368421 & 5.42422322542696 & 61.8667288240163 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 335.905405405405 & 5.32995589201081 & 63.0221735810049 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 336.25 & 5.21826986419703 & 64.4370660680159 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 336.714285714286 & 5.10466610954274 & 65.9620587299191 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 337.102941176471 & 4.99767899184006 & 67.4518995171306 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 337.621212121212 & 4.88882294772742 & 69.0598157738881 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 338.078125 & 4.78435283889614 & 70.6632926926857 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 338.564516129032 & 4.65701571065837 & 72.6998870444371 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 339.183333333333 & 4.52029270505348 & 75.0357013283989 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 339.724137931034 & 4.39158527598017 & 77.3579736204053 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 340.303571428571 & 4.23152359982563 & 80.4210501018107 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 340.685185185185 & 4.11367341030818 & 82.8177522142339 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 340.961538461538 & 4.00790711102496 & 85.0722157516127 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 341.4 & 3.90447153391899 & 87.4382095077873 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 341.604166666667 & 3.85436792650678 & 88.6278043975587 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 341.826086956522 & 3.78636051372932 & 90.2782726887897 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 342.068181818182 & 3.69509098482343 & 92.5736830901141 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 342.166666666667 & 3.6246537207617 & 94.3998221697056 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 342.275 & 3.52772671407959 & 97.0242390471854 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 342.210526315789 & 3.45117496942874 & 99.157686685597 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 342.333333333333 & 3.39911286278762 & 100.712552701938 \tabularnewline
Median & 343.5 &  &  \tabularnewline
Midrange & 310 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 342.677966101695 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 343.879310344828 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 342.677966101695 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 343.879310344828 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 343.879310344828 &  &  \tabularnewline
Midmean - Closest Observation & 342.677966101695 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 343.879310344828 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 342.677966101695 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=235406&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]329.546296296296[/C][C]7.37769064046749[/C][C]44.6679472420132[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]319.486628425179[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]308.113753756363[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]338.267358099412[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]329.481481481481[/C][C]7.34197170676956[/C][C]44.8764302888402[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]329.611111111111[/C][C]7.31452124669964[/C][C]45.0625680060515[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]329.805555555556[/C][C]7.21617038160457[/C][C]45.7036818859342[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]330.064814814815[/C][C]7.16683297095251[/C][C]46.054486849712[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]329.740740740741[/C][C]7.11866450116114[/C][C]46.3205901453785[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]330.074074074074[/C][C]7.05717273684569[/C][C]46.7714319008728[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]330.527777777778[/C][C]6.97631678638547[/C][C]47.378550587441[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]330.083333333333[/C][C]6.75148695850901[/C][C]48.8904644801726[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]330.083333333333[/C][C]6.75148695850901[/C][C]48.8904644801726[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]329.990740740741[/C][C]6.57295895602473[/C][C]50.2042904799023[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]329.277777777778[/C][C]6.48430265457425[/C][C]50.780753971361[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]329.277777777778[/C][C]6.48430265457425[/C][C]50.780753971361[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]330.12037037037[/C][C]6.34534191902459[/C][C]52.025623612276[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]331.027777777778[/C][C]5.98585586718178[/C][C]55.3016619716288[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]332[/C][C]5.8398494980536[/C][C]56.8507801631967[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]332[/C][C]5.8398494980536[/C][C]56.8507801631967[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]332[/C][C]5.8398494980536[/C][C]56.8507801631967[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]330.833333333333[/C][C]5.70367701260989[/C][C]58.0035181869372[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]332.064814814815[/C][C]5.52335851591072[/C][C]60.1200906763993[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]330.768518518519[/C][C]5.3787108787113[/C][C]61.4958725198794[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]331.935185185185[/C][C]5.21119015146869[/C][C]63.6966173824293[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]331.935185185185[/C][C]5.21119015146869[/C][C]63.6966173824293[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]330.657407407407[/C][C]5.07488338147683[/C][C]65.1556661605855[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]332.212962962963[/C][C]4.85547531352353[/C][C]68.4202763914131[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]332.212962962963[/C][C]4.85547531352353[/C][C]68.4202763914131[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]335.342592592593[/C][C]4.43170868733658[/C][C]75.6689160437869[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]337.092592592593[/C][C]4.20555141360328[/C][C]80.1541960709915[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]335.277777777778[/C][C]4.01019454899097[/C][C]83.6063621557062[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]338.768518518519[/C][C]3.57563304785091[/C][C]94.7436479037274[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]338.768518518519[/C][C]3.57563304785091[/C][C]94.7436479037274[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]338.768518518519[/C][C]3.57563304785091[/C][C]94.7436479037274[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]340.842592592593[/C][C]3.33261056642409[/C][C]102.27495406351[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]340.842592592593[/C][C]3.33261056642409[/C][C]102.27495406351[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]343.046296296296[/C][C]3.08589350249933[/C][C]111.165954372196[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]340.777777777778[/C][C]2.83833268952813[/C][C]120.062661799675[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]340.777777777778[/C][C]2.83833268952813[/C][C]120.062661799675[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]329.915094339623[/C][C]7.21210071698509[/C][C]45.744659882889[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]330.365384615385[/C][C]7.06630099316271[/C][C]46.7522378306618[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]330.764705882353[/C][C]6.9186578843805[/C][C]47.8076400668812[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]331.11[/C][C]6.79335526507894[/C][C]48.7402744417125[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]331.397959183673[/C][C]6.66813865887462[/C][C]49.6987204581621[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]331.770833333333[/C][C]6.53949672078143[/C][C]50.733389356863[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]332.095744680851[/C][C]6.4086076072695[/C][C]51.8202650298239[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]332.358695652174[/C][C]6.27770651000331[/C][C]52.9426941387865[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]332.7[/C][C]6.17326704165149[/C][C]53.8936672843161[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]333.056818181818[/C][C]6.05347465258805[/C][C]55.0191150200697[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]333.441860465116[/C][C]5.94738914659675[/C][C]56.0652501872894[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]333.928571428571[/C][C]5.83908295566471[/C][C]57.1885301106426[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]334.439024390244[/C][C]5.7133708888776[/C][C]58.5362005889215[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]334.8875[/C][C]5.59056601802525[/C][C]59.9022529955369[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]335.269230769231[/C][C]5.50384097034796[/C][C]60.9155011155845[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]335.578947368421[/C][C]5.42422322542696[/C][C]61.8667288240163[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]335.905405405405[/C][C]5.32995589201081[/C][C]63.0221735810049[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]336.25[/C][C]5.21826986419703[/C][C]64.4370660680159[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]336.714285714286[/C][C]5.10466610954274[/C][C]65.9620587299191[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]337.102941176471[/C][C]4.99767899184006[/C][C]67.4518995171306[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]337.621212121212[/C][C]4.88882294772742[/C][C]69.0598157738881[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]338.078125[/C][C]4.78435283889614[/C][C]70.6632926926857[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]338.564516129032[/C][C]4.65701571065837[/C][C]72.6998870444371[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]339.183333333333[/C][C]4.52029270505348[/C][C]75.0357013283989[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]339.724137931034[/C][C]4.39158527598017[/C][C]77.3579736204053[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]340.303571428571[/C][C]4.23152359982563[/C][C]80.4210501018107[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]340.685185185185[/C][C]4.11367341030818[/C][C]82.8177522142339[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]340.961538461538[/C][C]4.00790711102496[/C][C]85.0722157516127[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]341.4[/C][C]3.90447153391899[/C][C]87.4382095077873[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]341.604166666667[/C][C]3.85436792650678[/C][C]88.6278043975587[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]341.826086956522[/C][C]3.78636051372932[/C][C]90.2782726887897[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]342.068181818182[/C][C]3.69509098482343[/C][C]92.5736830901141[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]342.166666666667[/C][C]3.6246537207617[/C][C]94.3998221697056[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]342.275[/C][C]3.52772671407959[/C][C]97.0242390471854[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]342.210526315789[/C][C]3.45117496942874[/C][C]99.157686685597[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]342.333333333333[/C][C]3.39911286278762[/C][C]100.712552701938[/C][/ROW]
[ROW][C]Median[/C][C]343.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]310[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]342.677966101695[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]343.879310344828[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]342.677966101695[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]343.879310344828[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]343.879310344828[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]342.677966101695[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]343.879310344828[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]342.677966101695[/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=235406&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235406&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 Mean329.5462962962967.3776906404674944.6679472420132
Geometric Mean319.486628425179
Harmonic Mean308.113753756363
Quadratic Mean338.267358099412
Winsorized Mean ( 1 / 36 )329.4814814814817.3419717067695644.8764302888402
Winsorized Mean ( 2 / 36 )329.6111111111117.3145212466996445.0625680060515
Winsorized Mean ( 3 / 36 )329.8055555555567.2161703816045745.7036818859342
Winsorized Mean ( 4 / 36 )330.0648148148157.1668329709525146.054486849712
Winsorized Mean ( 5 / 36 )329.7407407407417.1186645011611446.3205901453785
Winsorized Mean ( 6 / 36 )330.0740740740747.0571727368456946.7714319008728
Winsorized Mean ( 7 / 36 )330.5277777777786.9763167863854747.378550587441
Winsorized Mean ( 8 / 36 )330.0833333333336.7514869585090148.8904644801726
Winsorized Mean ( 9 / 36 )330.0833333333336.7514869585090148.8904644801726
Winsorized Mean ( 10 / 36 )329.9907407407416.5729589560247350.2042904799023
Winsorized Mean ( 11 / 36 )329.2777777777786.4843026545742550.780753971361
Winsorized Mean ( 12 / 36 )329.2777777777786.4843026545742550.780753971361
Winsorized Mean ( 13 / 36 )330.120370370376.3453419190245952.025623612276
Winsorized Mean ( 14 / 36 )331.0277777777785.9858558671817855.3016619716288
Winsorized Mean ( 15 / 36 )3325.839849498053656.8507801631967
Winsorized Mean ( 16 / 36 )3325.839849498053656.8507801631967
Winsorized Mean ( 17 / 36 )3325.839849498053656.8507801631967
Winsorized Mean ( 18 / 36 )330.8333333333335.7036770126098958.0035181869372
Winsorized Mean ( 19 / 36 )332.0648148148155.5233585159107260.1200906763993
Winsorized Mean ( 20 / 36 )330.7685185185195.378710878711361.4958725198794
Winsorized Mean ( 21 / 36 )331.9351851851855.2111901514686963.6966173824293
Winsorized Mean ( 22 / 36 )331.9351851851855.2111901514686963.6966173824293
Winsorized Mean ( 23 / 36 )330.6574074074075.0748833814768365.1556661605855
Winsorized Mean ( 24 / 36 )332.2129629629634.8554753135235368.4202763914131
Winsorized Mean ( 25 / 36 )332.2129629629634.8554753135235368.4202763914131
Winsorized Mean ( 26 / 36 )335.3425925925934.4317086873365875.6689160437869
Winsorized Mean ( 27 / 36 )337.0925925925934.2055514136032880.1541960709915
Winsorized Mean ( 28 / 36 )335.2777777777784.0101945489909783.6063621557062
Winsorized Mean ( 29 / 36 )338.7685185185193.5756330478509194.7436479037274
Winsorized Mean ( 30 / 36 )338.7685185185193.5756330478509194.7436479037274
Winsorized Mean ( 31 / 36 )338.7685185185193.5756330478509194.7436479037274
Winsorized Mean ( 32 / 36 )340.8425925925933.33261056642409102.27495406351
Winsorized Mean ( 33 / 36 )340.8425925925933.33261056642409102.27495406351
Winsorized Mean ( 34 / 36 )343.0462962962963.08589350249933111.165954372196
Winsorized Mean ( 35 / 36 )340.7777777777782.83833268952813120.062661799675
Winsorized Mean ( 36 / 36 )340.7777777777782.83833268952813120.062661799675
Trimmed Mean ( 1 / 36 )329.9150943396237.2121007169850945.744659882889
Trimmed Mean ( 2 / 36 )330.3653846153857.0663009931627146.7522378306618
Trimmed Mean ( 3 / 36 )330.7647058823536.918657884380547.8076400668812
Trimmed Mean ( 4 / 36 )331.116.7933552650789448.7402744417125
Trimmed Mean ( 5 / 36 )331.3979591836736.6681386588746249.6987204581621
Trimmed Mean ( 6 / 36 )331.7708333333336.5394967207814350.733389356863
Trimmed Mean ( 7 / 36 )332.0957446808516.408607607269551.8202650298239
Trimmed Mean ( 8 / 36 )332.3586956521746.2777065100033152.9426941387865
Trimmed Mean ( 9 / 36 )332.76.1732670416514953.8936672843161
Trimmed Mean ( 10 / 36 )333.0568181818186.0534746525880555.0191150200697
Trimmed Mean ( 11 / 36 )333.4418604651165.9473891465967556.0652501872894
Trimmed Mean ( 12 / 36 )333.9285714285715.8390829556647157.1885301106426
Trimmed Mean ( 13 / 36 )334.4390243902445.713370888877658.5362005889215
Trimmed Mean ( 14 / 36 )334.88755.5905660180252559.9022529955369
Trimmed Mean ( 15 / 36 )335.2692307692315.5038409703479660.9155011155845
Trimmed Mean ( 16 / 36 )335.5789473684215.4242232254269661.8667288240163
Trimmed Mean ( 17 / 36 )335.9054054054055.3299558920108163.0221735810049
Trimmed Mean ( 18 / 36 )336.255.2182698641970364.4370660680159
Trimmed Mean ( 19 / 36 )336.7142857142865.1046661095427465.9620587299191
Trimmed Mean ( 20 / 36 )337.1029411764714.9976789918400667.4518995171306
Trimmed Mean ( 21 / 36 )337.6212121212124.8888229477274269.0598157738881
Trimmed Mean ( 22 / 36 )338.0781254.7843528388961470.6632926926857
Trimmed Mean ( 23 / 36 )338.5645161290324.6570157106583772.6998870444371
Trimmed Mean ( 24 / 36 )339.1833333333334.5202927050534875.0357013283989
Trimmed Mean ( 25 / 36 )339.7241379310344.3915852759801777.3579736204053
Trimmed Mean ( 26 / 36 )340.3035714285714.2315235998256380.4210501018107
Trimmed Mean ( 27 / 36 )340.6851851851854.1136734103081882.8177522142339
Trimmed Mean ( 28 / 36 )340.9615384615384.0079071110249685.0722157516127
Trimmed Mean ( 29 / 36 )341.43.9044715339189987.4382095077873
Trimmed Mean ( 30 / 36 )341.6041666666673.8543679265067888.6278043975587
Trimmed Mean ( 31 / 36 )341.8260869565223.7863605137293290.2782726887897
Trimmed Mean ( 32 / 36 )342.0681818181823.6950909848234392.5736830901141
Trimmed Mean ( 33 / 36 )342.1666666666673.624653720761794.3998221697056
Trimmed Mean ( 34 / 36 )342.2753.5277267140795997.0242390471854
Trimmed Mean ( 35 / 36 )342.2105263157893.4511749694287499.157686685597
Trimmed Mean ( 36 / 36 )342.3333333333333.39911286278762100.712552701938
Median343.5
Midrange310
Midmean - Weighted Average at Xnp342.677966101695
Midmean - Weighted Average at X(n+1)p343.879310344828
Midmean - Empirical Distribution Function342.677966101695
Midmean - Empirical Distribution Function - Averaging343.879310344828
Midmean - Empirical Distribution Function - Interpolation343.879310344828
Midmean - Closest Observation342.677966101695
Midmean - True Basic - Statistics Graphics Toolkit343.879310344828
Midmean - MS Excel (old versions)342.677966101695
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')