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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, 20 Oct 2008 16:25:49 -0600
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/Oct/21/t1224541610nogxqiw9g4i1t7q.htm/, Retrieved Sun, 19 May 2024 18:19:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18261, Retrieved Sun, 19 May 2024 18:19:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact216
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [Investigating Ass...] [2007-10-22 10:34:53] [b9964c45117f7aac638ab9056d451faa]
F    D    [Central Tendency] [Bouwvergunningen ...] [2008-10-20 22:25:49] [de3f0516a1536f7c4a656924d8bc8d07] [Current]
Feedback Forum
2008-10-25 13:17:26 [Davy De Nef] [reply
De student berekent de central tendency aan de hand van 2 verschillende methoden. Bij de winsorized mean zie je duidelijk een dalend verloop. Je ziet ook schommelingen.
Bij de trimmed mean daarentegen zie je wel een dalend verloop, maar stel je geen schommelingen vast. Hier is er eerder sprake van een vloeiende dalende lijn. Dit kan verklaart worden doordat bij deze methode de staarten weggelaten worden. Er wordt dus met een kleinere dataset gewerkt. De resultaten convergeren naar de mediaan.
2008-10-25 13:48:18 [Astrid Sniekers] [reply
De student zegt niet op welke tijdreeks hij een voorspelling maakt en kopieert gewoon de uitleg van de student van vorig jaar!!
2008-10-26 23:12:42 [Kristof Augustyns] [reply
De tendens van de bouwvergunningen in ... is jammer genoeg niet vermeld.
De winsorized mean is dus nauwkeuriger omdat de dataset uitgebreider is dan die van de trimmed mean.
Hier is er een rustig verloop dat lichtjes daalt naar onder, maar zonder teveel spanningen of outliers.
De midrange en mediaan lopen naar de mean toe.
Lichte daling = licht negatieve tendens naar de toekomst toe.

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Dataseries X:
2266
1878
2267
2069
1746
2299
2360
2214
2825
2355
2333
3016
2155
2172
2150
2533
2058
2160
2259
2498
2695
2799
2945
2930
2318
2540
2570
2669
2450
2842
3439
2677
2979
2257
2842
2546
2455
2293
2379
2478
2054
2272
2351
2271
2542
2304
2194
2722
2395
2146
1894
2548
2087
2063
2481
2476
2212
2834
2148
2598




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18261&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18261&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18261&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean2421.840.993163271797559.0781439320188
Geometric Mean2401.93432182843
Harmonic Mean2382.56244432215
Quadratic Mean2442.18368815015
Winsorized Mean ( 1 / 20 )2416.9537.973879105910263.6476982838403
Winsorized Mean ( 2 / 20 )2416.2537.525145053676164.3901574942291
Winsorized Mean ( 3 / 20 )2422.5535.441241457448968.3539825462529
Winsorized Mean ( 4 / 20 )2421.8166666666735.146878988560868.9055966378947
Winsorized Mean ( 5 / 20 )2414.933.376619070315972.3530443545655
Winsorized Mean ( 6 / 20 )2415.533.270051513089372.6028331831611
Winsorized Mean ( 7 / 20 )2416.6666666666732.702914283539573.8975935206807
Winsorized Mean ( 8 / 20 )2423.3333333333331.175144621710477.7328658050787
Winsorized Mean ( 9 / 20 )2419.7333333333330.289878851336279.8858703004217
Winsorized Mean ( 10 / 20 )2407.2333333333327.631977776787487.117663193677
Winsorized Mean ( 11 / 20 )2403.226.54775890399990.5236486699446
Winsorized Mean ( 12 / 20 )2400.625.726035966578193.3140264251643
Winsorized Mean ( 13 / 20 )2401.4666666666725.002683095191496.0483583911251
Winsorized Mean ( 14 / 20 )2390.0333333333321.3212841149132112.096125188896
Winsorized Mean ( 15 / 20 )2387.5333333333319.4919143988044122.488396187487
Winsorized Mean ( 16 / 20 )2382.218.4985844625648128.777421041097
Winsorized Mean ( 17 / 20 )2393.8166666666716.6180164239952144.049482536928
Winsorized Mean ( 18 / 20 )2393.2166666666716.3487260283341146.385514230220
Winsorized Mean ( 19 / 20 )2394.815.9450114402752150.191174774012
Winsorized Mean ( 20 / 20 )2392.815.5408483070164153.968429054139
Trimmed Mean ( 1 / 20 )2415.9137931034536.710409076899765.8100482629511
Trimmed Mean ( 2 / 20 )2414.8035714285735.151900612217368.69624485082
Trimmed Mean ( 3 / 20 )241433.522690668524572.0109260879401
Trimmed Mean ( 4 / 20 )2410.7115384615432.517014185922274.1369279687808
Trimmed Mean ( 5 / 20 )2407.3831.360235968576.765366256112
Trimmed Mean ( 6 / 20 )2405.530.523113553386278.8091292126107
Trimmed Mean ( 7 / 20 )2403.3260869565229.470726560564581.549604215475
Trimmed Mean ( 8 / 20 )2400.7272727272728.269362083297584.9232913587995
Trimmed Mean ( 9 / 20 )2396.6904761904827.118989495991088.3768355950277
Trimmed Mean ( 10 / 20 )2392.8525.846404054802392.5796097177163
Trimmed Mean ( 11 / 20 )2390.5789473684224.941257631888595.8483723095004
Trimmed Mean ( 12 / 20 )2388.6666666666724.009323585799399.4891279685814
Trimmed Mean ( 13 / 20 )2386.9117647058822.9467867585807104.019433736766
Trimmed Mean ( 14 / 20 )2384.812521.6481410538806110.162461250801
Trimmed Mean ( 15 / 20 )2384.0666666666720.9821453015639113.623589599724
Trimmed Mean ( 16 / 20 )2383.5714285714320.5362261265866116.066672322312
Trimmed Mean ( 17 / 20 )2383.7692307692320.1166068168189118.497580256737
Trimmed Mean ( 18 / 20 )2382.2916666666719.9908927785161119.168848188055
Trimmed Mean ( 19 / 20 )2380.6363636363619.7292875065856120.665095627083
Trimmed Mean ( 20 / 20 )2378.419.2758916784672123.387288104388
Median2357.5
Midrange2592.5
Midmean - Weighted Average at Xnp2377.93548387097
Midmean - Weighted Average at X(n+1)p2384.06666666667
Midmean - Empirical Distribution Function2377.93548387097
Midmean - Empirical Distribution Function - Averaging2384.06666666667
Midmean - Empirical Distribution Function - Interpolation2384.06666666667
Midmean - Closest Observation2377.93548387097
Midmean - True Basic - Statistics Graphics Toolkit2384.06666666667
Midmean - MS Excel (old versions)2384.8125
Number of observations60

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 2421.8 & 40.9931632717975 & 59.0781439320188 \tabularnewline
Geometric Mean & 2401.93432182843 &  &  \tabularnewline
Harmonic Mean & 2382.56244432215 &  &  \tabularnewline
Quadratic Mean & 2442.18368815015 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & 2416.95 & 37.9738791059102 & 63.6476982838403 \tabularnewline
Winsorized Mean ( 2 / 20 ) & 2416.25 & 37.5251450536761 & 64.3901574942291 \tabularnewline
Winsorized Mean ( 3 / 20 ) & 2422.55 & 35.4412414574489 & 68.3539825462529 \tabularnewline
Winsorized Mean ( 4 / 20 ) & 2421.81666666667 & 35.1468789885608 & 68.9055966378947 \tabularnewline
Winsorized Mean ( 5 / 20 ) & 2414.9 & 33.3766190703159 & 72.3530443545655 \tabularnewline
Winsorized Mean ( 6 / 20 ) & 2415.5 & 33.2700515130893 & 72.6028331831611 \tabularnewline
Winsorized Mean ( 7 / 20 ) & 2416.66666666667 & 32.7029142835395 & 73.8975935206807 \tabularnewline
Winsorized Mean ( 8 / 20 ) & 2423.33333333333 & 31.1751446217104 & 77.7328658050787 \tabularnewline
Winsorized Mean ( 9 / 20 ) & 2419.73333333333 & 30.2898788513362 & 79.8858703004217 \tabularnewline
Winsorized Mean ( 10 / 20 ) & 2407.23333333333 & 27.6319777767874 & 87.117663193677 \tabularnewline
Winsorized Mean ( 11 / 20 ) & 2403.2 & 26.547758903999 & 90.5236486699446 \tabularnewline
Winsorized Mean ( 12 / 20 ) & 2400.6 & 25.7260359665781 & 93.3140264251643 \tabularnewline
Winsorized Mean ( 13 / 20 ) & 2401.46666666667 & 25.0026830951914 & 96.0483583911251 \tabularnewline
Winsorized Mean ( 14 / 20 ) & 2390.03333333333 & 21.3212841149132 & 112.096125188896 \tabularnewline
Winsorized Mean ( 15 / 20 ) & 2387.53333333333 & 19.4919143988044 & 122.488396187487 \tabularnewline
Winsorized Mean ( 16 / 20 ) & 2382.2 & 18.4985844625648 & 128.777421041097 \tabularnewline
Winsorized Mean ( 17 / 20 ) & 2393.81666666667 & 16.6180164239952 & 144.049482536928 \tabularnewline
Winsorized Mean ( 18 / 20 ) & 2393.21666666667 & 16.3487260283341 & 146.385514230220 \tabularnewline
Winsorized Mean ( 19 / 20 ) & 2394.8 & 15.9450114402752 & 150.191174774012 \tabularnewline
Winsorized Mean ( 20 / 20 ) & 2392.8 & 15.5408483070164 & 153.968429054139 \tabularnewline
Trimmed Mean ( 1 / 20 ) & 2415.91379310345 & 36.7104090768997 & 65.8100482629511 \tabularnewline
Trimmed Mean ( 2 / 20 ) & 2414.80357142857 & 35.1519006122173 & 68.69624485082 \tabularnewline
Trimmed Mean ( 3 / 20 ) & 2414 & 33.5226906685245 & 72.0109260879401 \tabularnewline
Trimmed Mean ( 4 / 20 ) & 2410.71153846154 & 32.5170141859222 & 74.1369279687808 \tabularnewline
Trimmed Mean ( 5 / 20 ) & 2407.38 & 31.3602359685 & 76.765366256112 \tabularnewline
Trimmed Mean ( 6 / 20 ) & 2405.5 & 30.5231135533862 & 78.8091292126107 \tabularnewline
Trimmed Mean ( 7 / 20 ) & 2403.32608695652 & 29.4707265605645 & 81.549604215475 \tabularnewline
Trimmed Mean ( 8 / 20 ) & 2400.72727272727 & 28.2693620832975 & 84.9232913587995 \tabularnewline
Trimmed Mean ( 9 / 20 ) & 2396.69047619048 & 27.1189894959910 & 88.3768355950277 \tabularnewline
Trimmed Mean ( 10 / 20 ) & 2392.85 & 25.8464040548023 & 92.5796097177163 \tabularnewline
Trimmed Mean ( 11 / 20 ) & 2390.57894736842 & 24.9412576318885 & 95.8483723095004 \tabularnewline
Trimmed Mean ( 12 / 20 ) & 2388.66666666667 & 24.0093235857993 & 99.4891279685814 \tabularnewline
Trimmed Mean ( 13 / 20 ) & 2386.91176470588 & 22.9467867585807 & 104.019433736766 \tabularnewline
Trimmed Mean ( 14 / 20 ) & 2384.8125 & 21.6481410538806 & 110.162461250801 \tabularnewline
Trimmed Mean ( 15 / 20 ) & 2384.06666666667 & 20.9821453015639 & 113.623589599724 \tabularnewline
Trimmed Mean ( 16 / 20 ) & 2383.57142857143 & 20.5362261265866 & 116.066672322312 \tabularnewline
Trimmed Mean ( 17 / 20 ) & 2383.76923076923 & 20.1166068168189 & 118.497580256737 \tabularnewline
Trimmed Mean ( 18 / 20 ) & 2382.29166666667 & 19.9908927785161 & 119.168848188055 \tabularnewline
Trimmed Mean ( 19 / 20 ) & 2380.63636363636 & 19.7292875065856 & 120.665095627083 \tabularnewline
Trimmed Mean ( 20 / 20 ) & 2378.4 & 19.2758916784672 & 123.387288104388 \tabularnewline
Median & 2357.5 &  &  \tabularnewline
Midrange & 2592.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 2377.93548387097 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 2384.06666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 2377.93548387097 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 2384.06666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 2384.06666666667 &  &  \tabularnewline
Midmean - Closest Observation & 2377.93548387097 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 2384.06666666667 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 2384.8125 &  &  \tabularnewline
Number of observations & 60 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18261&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]2421.8[/C][C]40.9931632717975[/C][C]59.0781439320188[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]2401.93432182843[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]2382.56244432215[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]2442.18368815015[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]2416.95[/C][C]37.9738791059102[/C][C]63.6476982838403[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]2416.25[/C][C]37.5251450536761[/C][C]64.3901574942291[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]2422.55[/C][C]35.4412414574489[/C][C]68.3539825462529[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]2421.81666666667[/C][C]35.1468789885608[/C][C]68.9055966378947[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]2414.9[/C][C]33.3766190703159[/C][C]72.3530443545655[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]2415.5[/C][C]33.2700515130893[/C][C]72.6028331831611[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]2416.66666666667[/C][C]32.7029142835395[/C][C]73.8975935206807[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]2423.33333333333[/C][C]31.1751446217104[/C][C]77.7328658050787[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]2419.73333333333[/C][C]30.2898788513362[/C][C]79.8858703004217[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]2407.23333333333[/C][C]27.6319777767874[/C][C]87.117663193677[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]2403.2[/C][C]26.547758903999[/C][C]90.5236486699446[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]2400.6[/C][C]25.7260359665781[/C][C]93.3140264251643[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]2401.46666666667[/C][C]25.0026830951914[/C][C]96.0483583911251[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]2390.03333333333[/C][C]21.3212841149132[/C][C]112.096125188896[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]2387.53333333333[/C][C]19.4919143988044[/C][C]122.488396187487[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]2382.2[/C][C]18.4985844625648[/C][C]128.777421041097[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]2393.81666666667[/C][C]16.6180164239952[/C][C]144.049482536928[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]2393.21666666667[/C][C]16.3487260283341[/C][C]146.385514230220[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]2394.8[/C][C]15.9450114402752[/C][C]150.191174774012[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]2392.8[/C][C]15.5408483070164[/C][C]153.968429054139[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]2415.91379310345[/C][C]36.7104090768997[/C][C]65.8100482629511[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]2414.80357142857[/C][C]35.1519006122173[/C][C]68.69624485082[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]2414[/C][C]33.5226906685245[/C][C]72.0109260879401[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]2410.71153846154[/C][C]32.5170141859222[/C][C]74.1369279687808[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]2407.38[/C][C]31.3602359685[/C][C]76.765366256112[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]2405.5[/C][C]30.5231135533862[/C][C]78.8091292126107[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]2403.32608695652[/C][C]29.4707265605645[/C][C]81.549604215475[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]2400.72727272727[/C][C]28.2693620832975[/C][C]84.9232913587995[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]2396.69047619048[/C][C]27.1189894959910[/C][C]88.3768355950277[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]2392.85[/C][C]25.8464040548023[/C][C]92.5796097177163[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]2390.57894736842[/C][C]24.9412576318885[/C][C]95.8483723095004[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]2388.66666666667[/C][C]24.0093235857993[/C][C]99.4891279685814[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]2386.91176470588[/C][C]22.9467867585807[/C][C]104.019433736766[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]2384.8125[/C][C]21.6481410538806[/C][C]110.162461250801[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]2384.06666666667[/C][C]20.9821453015639[/C][C]113.623589599724[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]2383.57142857143[/C][C]20.5362261265866[/C][C]116.066672322312[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]2383.76923076923[/C][C]20.1166068168189[/C][C]118.497580256737[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]2382.29166666667[/C][C]19.9908927785161[/C][C]119.168848188055[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]2380.63636363636[/C][C]19.7292875065856[/C][C]120.665095627083[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]2378.4[/C][C]19.2758916784672[/C][C]123.387288104388[/C][/ROW]
[ROW][C]Median[/C][C]2357.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]2592.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]2377.93548387097[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]2384.06666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]2377.93548387097[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]2384.06666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]2384.06666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]2377.93548387097[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]2384.06666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]2384.8125[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]60[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18261&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18261&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 Mean2421.840.993163271797559.0781439320188
Geometric Mean2401.93432182843
Harmonic Mean2382.56244432215
Quadratic Mean2442.18368815015
Winsorized Mean ( 1 / 20 )2416.9537.973879105910263.6476982838403
Winsorized Mean ( 2 / 20 )2416.2537.525145053676164.3901574942291
Winsorized Mean ( 3 / 20 )2422.5535.441241457448968.3539825462529
Winsorized Mean ( 4 / 20 )2421.8166666666735.146878988560868.9055966378947
Winsorized Mean ( 5 / 20 )2414.933.376619070315972.3530443545655
Winsorized Mean ( 6 / 20 )2415.533.270051513089372.6028331831611
Winsorized Mean ( 7 / 20 )2416.6666666666732.702914283539573.8975935206807
Winsorized Mean ( 8 / 20 )2423.3333333333331.175144621710477.7328658050787
Winsorized Mean ( 9 / 20 )2419.7333333333330.289878851336279.8858703004217
Winsorized Mean ( 10 / 20 )2407.2333333333327.631977776787487.117663193677
Winsorized Mean ( 11 / 20 )2403.226.54775890399990.5236486699446
Winsorized Mean ( 12 / 20 )2400.625.726035966578193.3140264251643
Winsorized Mean ( 13 / 20 )2401.4666666666725.002683095191496.0483583911251
Winsorized Mean ( 14 / 20 )2390.0333333333321.3212841149132112.096125188896
Winsorized Mean ( 15 / 20 )2387.5333333333319.4919143988044122.488396187487
Winsorized Mean ( 16 / 20 )2382.218.4985844625648128.777421041097
Winsorized Mean ( 17 / 20 )2393.8166666666716.6180164239952144.049482536928
Winsorized Mean ( 18 / 20 )2393.2166666666716.3487260283341146.385514230220
Winsorized Mean ( 19 / 20 )2394.815.9450114402752150.191174774012
Winsorized Mean ( 20 / 20 )2392.815.5408483070164153.968429054139
Trimmed Mean ( 1 / 20 )2415.9137931034536.710409076899765.8100482629511
Trimmed Mean ( 2 / 20 )2414.8035714285735.151900612217368.69624485082
Trimmed Mean ( 3 / 20 )241433.522690668524572.0109260879401
Trimmed Mean ( 4 / 20 )2410.7115384615432.517014185922274.1369279687808
Trimmed Mean ( 5 / 20 )2407.3831.360235968576.765366256112
Trimmed Mean ( 6 / 20 )2405.530.523113553386278.8091292126107
Trimmed Mean ( 7 / 20 )2403.3260869565229.470726560564581.549604215475
Trimmed Mean ( 8 / 20 )2400.7272727272728.269362083297584.9232913587995
Trimmed Mean ( 9 / 20 )2396.6904761904827.118989495991088.3768355950277
Trimmed Mean ( 10 / 20 )2392.8525.846404054802392.5796097177163
Trimmed Mean ( 11 / 20 )2390.5789473684224.941257631888595.8483723095004
Trimmed Mean ( 12 / 20 )2388.6666666666724.009323585799399.4891279685814
Trimmed Mean ( 13 / 20 )2386.9117647058822.9467867585807104.019433736766
Trimmed Mean ( 14 / 20 )2384.812521.6481410538806110.162461250801
Trimmed Mean ( 15 / 20 )2384.0666666666720.9821453015639113.623589599724
Trimmed Mean ( 16 / 20 )2383.5714285714320.5362261265866116.066672322312
Trimmed Mean ( 17 / 20 )2383.7692307692320.1166068168189118.497580256737
Trimmed Mean ( 18 / 20 )2382.2916666666719.9908927785161119.168848188055
Trimmed Mean ( 19 / 20 )2380.6363636363619.7292875065856120.665095627083
Trimmed Mean ( 20 / 20 )2378.419.2758916784672123.387288104388
Median2357.5
Midrange2592.5
Midmean - Weighted Average at Xnp2377.93548387097
Midmean - Weighted Average at X(n+1)p2384.06666666667
Midmean - Empirical Distribution Function2377.93548387097
Midmean - Empirical Distribution Function - Averaging2384.06666666667
Midmean - Empirical Distribution Function - Interpolation2384.06666666667
Midmean - Closest Observation2377.93548387097
Midmean - True Basic - Statistics Graphics Toolkit2384.06666666667
Midmean - MS Excel (old versions)2384.8125
Number of observations60



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')