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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 10:23:45 -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/20/t12245199632zf64ym7lcds1qf.htm/, Retrieved Sun, 19 May 2024 15:22:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17601, Retrieved Sun, 19 May 2024 15:22:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Central Tendency] [Central tendency ...] [2008-10-20 16:23:45] [b4fc5040f26b33db57f84cfb8d1d2b82] [Current]
Feedback Forum
2008-10-27 10:38:12 [Thomas Beyers] [reply
je reeks is onderhevig aan outliers. Let op de sterke daling vanaf periode 25 en 26 op de winsorized mean grafiek !

Post a new message
Dataseries X:
2319
2383
2513
2553
2341
2540
2371
2122
2301
2512
3145
2741
2548
1987
2281
2016
2434
2637
1831
1851
1839
2609
2417
2394
2372
2717
2998
2538
3007
2475
2175
2465
2279
2323
2746
2601
2486
2718
2646
2551
2712
2606
2365
3533
3509
2912
3599
2719
2869
4085
2686
2545
3071
3388
2652
3190
2884
3295
3818
3226
3953
3810
2877
3515
3708
3450
3360
4110
4384
3729
4263
3505
3674
3911
2951
3317
3417
3498
2768
2899
3171
3004
3481
3016
2595
3509
2833
3125
2556
3628
2876
2575
2903
3438
2926
3068
3015




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17601&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17601&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17601&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean2909.938144329957.751533753366250.3872010872834
Geometric Mean2856.07522932221
Harmonic Mean2803.32014609952
Quadratic Mean2964.44311976285
Winsorized Mean ( 1 / 32 )2908.7731958762957.416399529715350.6610170561266
Winsorized Mean ( 2 / 32 )2905.8659793814456.631238853688551.3120680070056
Winsorized Mean ( 3 / 32 )2909.2989690721755.68932902309252.2415877531188
Winsorized Mean ( 4 / 32 )2905.0515463917554.338329699727453.4622901080143
Winsorized Mean ( 5 / 32 )2908.3505154639253.019364940415454.854495498624
Winsorized Mean ( 6 / 32 )2905.8762886597951.424723656244656.5073778146969
Winsorized Mean ( 7 / 32 )2912.8041237113450.268603348817457.9447991323568
Winsorized Mean ( 8 / 32 )2906.2886597938149.041664204153959.2616239060592
Winsorized Mean ( 9 / 32 )2906.1958762886648.459548970464059.9715832695838
Winsorized Mean ( 10 / 32 )2904.5463917525847.622905787353460.9905326802612
Winsorized Mean ( 11 / 32 )2899.7835051546446.701904866161962.0913325369667
Winsorized Mean ( 12 / 32 )2898.4226804123745.840630085490663.2282469723246
Winsorized Mean ( 13 / 32 )2892.7938144329944.062050948564465.6527272824834
Winsorized Mean ( 14 / 32 )2891.061855670143.563768616702166.3639062338075
Winsorized Mean ( 15 / 32 )2890.2886597938143.406441828076266.5866294971065
Winsorized Mean ( 16 / 32 )2892.1030927835043.182185389288366.9744494566715
Winsorized Mean ( 17 / 32 )2893.3298969072242.842486824765667.5341258489853
Winsorized Mean ( 18 / 32 )2896.2989690721742.137299526335268.7348026956976
Winsorized Mean ( 19 / 32 )2896.2989690721741.252142933373370.2096609562806
Winsorized Mean ( 20 / 32 )2896.2989690721739.578367833647873.1788380270158
Winsorized Mean ( 21 / 32 )2895.8659793814438.956055151976874.3367357932927
Winsorized Mean ( 22 / 32 )2893.5979381443337.989199325856276.168963534193
Winsorized Mean ( 23 / 32 )2892.8865979381436.32616088769479.636452827531
Winsorized Mean ( 24 / 32 )2886.2061855670135.323155116752181.7086179314207
Winsorized Mean ( 25 / 32 )2881.5670103092833.085552135955187.0944211076893
Winsorized Mean ( 26 / 32 )2876.2061855670132.223996343146189.2566569006195
Winsorized Mean ( 27 / 32 )2858.3917525773229.523505243016496.8174926740265
Winsorized Mean ( 28 / 32 )2848.8659793814428.0958511755522101.398101861402
Winsorized Mean ( 29 / 32 )2844.0824742268027.2818340414415104.248214027935
Winsorized Mean ( 30 / 32 )2836.6597938144326.217767342799108.196085376948
Winsorized Mean ( 31 / 32 )2831.2268041237125.3318079712710111.765682391664
Winsorized Mean ( 32 / 32 )2819.6804123711322.5078525166733125.275408228412
Trimmed Mean ( 1 / 32 )2905.7789473684255.713977568620752.1552952091688
Trimmed Mean ( 2 / 32 )2902.6559139784953.771034012654153.9817760115121
Trimmed Mean ( 3 / 32 )2900.9450549450552.03342910316255.7515640415244
Trimmed Mean ( 4 / 32 )2897.9101123595550.452676682059557.4381837186057
Trimmed Mean ( 5 / 32 )2895.9195402298949.109711442068558.9683680720872
Trimmed Mean ( 6 / 32 )2893.0823529411847.947789683241160.3381797587299
Trimmed Mean ( 7 / 32 )2893.0823529411847.013609411765161.5371248695742
Trimmed Mean ( 8 / 32 )2886.7901234567946.185741867670562.5039245169624
Trimmed Mean ( 9 / 32 )2883.7974683544345.479929766902163.4081337226054
Trimmed Mean ( 10 / 32 )2880.6623376623444.763197897202964.3533633204151
Trimmed Mean ( 11 / 32 )2877.5733333333344.072717034314865.2914893150986
Trimmed Mean ( 12 / 32 )2874.8904109589043.420020254725766.2111715769181
Trimmed Mean ( 13 / 32 )2872.2112676056342.788243348027867.1261786618315
Trimmed Mean ( 14 / 32 )2872.2112676056342.324299534629367.861991791633
Trimmed Mean ( 15 / 32 )2867.8059701492541.836105447852868.5485883413281
Trimmed Mean ( 16 / 32 )2865.5692307692341.261274503687369.4493629980612
Trimmed Mean ( 17 / 32 )2863.0158730158740.589243440648570.5363202248968
Trimmed Mean ( 18 / 32 )2860.1803278688539.816769596378771.8335605038382
Trimmed Mean ( 19 / 32 )2856.8813559322038.976563000386173.2974160883274
Trimmed Mean ( 20 / 32 )2853.3508771929838.083575249403674.9233983024655
Trimmed Mean ( 21 / 32 )2849.5636363636437.254017148416676.4901037386447
Trimmed Mean ( 22 / 32 )2845.5283018867936.314878419330178.3570928981037
Trimmed Mean ( 23 / 32 )2841.3725490196135.301557603632780.4885886600997
Trimmed Mean ( 24 / 32 )2836.9387755102034.315208149491382.6729292490759
Trimmed Mean ( 25 / 32 )2836.9387755102033.249719729138385.3221861303107
Trimmed Mean ( 26 / 32 )2828.4888888888932.317812929523987.5210489972522
Trimmed Mean ( 27 / 32 )2824.348837209331.274140332094790.309399625954
Trimmed Mean ( 28 / 32 )2824.348837209330.510629017537692.5693415099984
Trimmed Mean ( 29 / 32 )2818.9230769230829.797118406616194.603882108854
Trimmed Mean ( 30 / 32 )2816.6486486486528.995811445892197.1398456602836
Trimmed Mean ( 31 / 32 )2816.6486486486528.1419511008868100.087184380044
Trimmed Mean ( 32 / 32 )2813.2424242424227.1632630665464103.567911460061
Median2833
Midrange3107.5
Midmean - Weighted Average at Xnp2826.04166666667
Midmean - Weighted Average at X(n+1)p2836.93877551020
Midmean - Empirical Distribution Function2836.93877551020
Midmean - Empirical Distribution Function - Averaging2836.93877551020
Midmean - Empirical Distribution Function - Interpolation2836.93877551020
Midmean - Closest Observation2830.44
Midmean - True Basic - Statistics Graphics Toolkit2836.93877551020
Midmean - MS Excel (old versions)2836.93877551020
Number of observations97

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 2909.9381443299 & 57.7515337533662 & 50.3872010872834 \tabularnewline
Geometric Mean & 2856.07522932221 &  &  \tabularnewline
Harmonic Mean & 2803.32014609952 &  &  \tabularnewline
Quadratic Mean & 2964.44311976285 &  &  \tabularnewline
Winsorized Mean ( 1 / 32 ) & 2908.77319587629 & 57.4163995297153 & 50.6610170561266 \tabularnewline
Winsorized Mean ( 2 / 32 ) & 2905.86597938144 & 56.6312388536885 & 51.3120680070056 \tabularnewline
Winsorized Mean ( 3 / 32 ) & 2909.29896907217 & 55.689329023092 & 52.2415877531188 \tabularnewline
Winsorized Mean ( 4 / 32 ) & 2905.05154639175 & 54.3383296997274 & 53.4622901080143 \tabularnewline
Winsorized Mean ( 5 / 32 ) & 2908.35051546392 & 53.0193649404154 & 54.854495498624 \tabularnewline
Winsorized Mean ( 6 / 32 ) & 2905.87628865979 & 51.4247236562446 & 56.5073778146969 \tabularnewline
Winsorized Mean ( 7 / 32 ) & 2912.80412371134 & 50.2686033488174 & 57.9447991323568 \tabularnewline
Winsorized Mean ( 8 / 32 ) & 2906.28865979381 & 49.0416642041539 & 59.2616239060592 \tabularnewline
Winsorized Mean ( 9 / 32 ) & 2906.19587628866 & 48.4595489704640 & 59.9715832695838 \tabularnewline
Winsorized Mean ( 10 / 32 ) & 2904.54639175258 & 47.6229057873534 & 60.9905326802612 \tabularnewline
Winsorized Mean ( 11 / 32 ) & 2899.78350515464 & 46.7019048661619 & 62.0913325369667 \tabularnewline
Winsorized Mean ( 12 / 32 ) & 2898.42268041237 & 45.8406300854906 & 63.2282469723246 \tabularnewline
Winsorized Mean ( 13 / 32 ) & 2892.79381443299 & 44.0620509485644 & 65.6527272824834 \tabularnewline
Winsorized Mean ( 14 / 32 ) & 2891.0618556701 & 43.5637686167021 & 66.3639062338075 \tabularnewline
Winsorized Mean ( 15 / 32 ) & 2890.28865979381 & 43.4064418280762 & 66.5866294971065 \tabularnewline
Winsorized Mean ( 16 / 32 ) & 2892.10309278350 & 43.1821853892883 & 66.9744494566715 \tabularnewline
Winsorized Mean ( 17 / 32 ) & 2893.32989690722 & 42.8424868247656 & 67.5341258489853 \tabularnewline
Winsorized Mean ( 18 / 32 ) & 2896.29896907217 & 42.1372995263352 & 68.7348026956976 \tabularnewline
Winsorized Mean ( 19 / 32 ) & 2896.29896907217 & 41.2521429333733 & 70.2096609562806 \tabularnewline
Winsorized Mean ( 20 / 32 ) & 2896.29896907217 & 39.5783678336478 & 73.1788380270158 \tabularnewline
Winsorized Mean ( 21 / 32 ) & 2895.86597938144 & 38.9560551519768 & 74.3367357932927 \tabularnewline
Winsorized Mean ( 22 / 32 ) & 2893.59793814433 & 37.9891993258562 & 76.168963534193 \tabularnewline
Winsorized Mean ( 23 / 32 ) & 2892.88659793814 & 36.326160887694 & 79.636452827531 \tabularnewline
Winsorized Mean ( 24 / 32 ) & 2886.20618556701 & 35.3231551167521 & 81.7086179314207 \tabularnewline
Winsorized Mean ( 25 / 32 ) & 2881.56701030928 & 33.0855521359551 & 87.0944211076893 \tabularnewline
Winsorized Mean ( 26 / 32 ) & 2876.20618556701 & 32.2239963431461 & 89.2566569006195 \tabularnewline
Winsorized Mean ( 27 / 32 ) & 2858.39175257732 & 29.5235052430164 & 96.8174926740265 \tabularnewline
Winsorized Mean ( 28 / 32 ) & 2848.86597938144 & 28.0958511755522 & 101.398101861402 \tabularnewline
Winsorized Mean ( 29 / 32 ) & 2844.08247422680 & 27.2818340414415 & 104.248214027935 \tabularnewline
Winsorized Mean ( 30 / 32 ) & 2836.65979381443 & 26.217767342799 & 108.196085376948 \tabularnewline
Winsorized Mean ( 31 / 32 ) & 2831.22680412371 & 25.3318079712710 & 111.765682391664 \tabularnewline
Winsorized Mean ( 32 / 32 ) & 2819.68041237113 & 22.5078525166733 & 125.275408228412 \tabularnewline
Trimmed Mean ( 1 / 32 ) & 2905.77894736842 & 55.7139775686207 & 52.1552952091688 \tabularnewline
Trimmed Mean ( 2 / 32 ) & 2902.65591397849 & 53.7710340126541 & 53.9817760115121 \tabularnewline
Trimmed Mean ( 3 / 32 ) & 2900.94505494505 & 52.033429103162 & 55.7515640415244 \tabularnewline
Trimmed Mean ( 4 / 32 ) & 2897.91011235955 & 50.4526766820595 & 57.4381837186057 \tabularnewline
Trimmed Mean ( 5 / 32 ) & 2895.91954022989 & 49.1097114420685 & 58.9683680720872 \tabularnewline
Trimmed Mean ( 6 / 32 ) & 2893.08235294118 & 47.9477896832411 & 60.3381797587299 \tabularnewline
Trimmed Mean ( 7 / 32 ) & 2893.08235294118 & 47.0136094117651 & 61.5371248695742 \tabularnewline
Trimmed Mean ( 8 / 32 ) & 2886.79012345679 & 46.1857418676705 & 62.5039245169624 \tabularnewline
Trimmed Mean ( 9 / 32 ) & 2883.79746835443 & 45.4799297669021 & 63.4081337226054 \tabularnewline
Trimmed Mean ( 10 / 32 ) & 2880.66233766234 & 44.7631978972029 & 64.3533633204151 \tabularnewline
Trimmed Mean ( 11 / 32 ) & 2877.57333333333 & 44.0727170343148 & 65.2914893150986 \tabularnewline
Trimmed Mean ( 12 / 32 ) & 2874.89041095890 & 43.4200202547257 & 66.2111715769181 \tabularnewline
Trimmed Mean ( 13 / 32 ) & 2872.21126760563 & 42.7882433480278 & 67.1261786618315 \tabularnewline
Trimmed Mean ( 14 / 32 ) & 2872.21126760563 & 42.3242995346293 & 67.861991791633 \tabularnewline
Trimmed Mean ( 15 / 32 ) & 2867.80597014925 & 41.8361054478528 & 68.5485883413281 \tabularnewline
Trimmed Mean ( 16 / 32 ) & 2865.56923076923 & 41.2612745036873 & 69.4493629980612 \tabularnewline
Trimmed Mean ( 17 / 32 ) & 2863.01587301587 & 40.5892434406485 & 70.5363202248968 \tabularnewline
Trimmed Mean ( 18 / 32 ) & 2860.18032786885 & 39.8167695963787 & 71.8335605038382 \tabularnewline
Trimmed Mean ( 19 / 32 ) & 2856.88135593220 & 38.9765630003861 & 73.2974160883274 \tabularnewline
Trimmed Mean ( 20 / 32 ) & 2853.35087719298 & 38.0835752494036 & 74.9233983024655 \tabularnewline
Trimmed Mean ( 21 / 32 ) & 2849.56363636364 & 37.2540171484166 & 76.4901037386447 \tabularnewline
Trimmed Mean ( 22 / 32 ) & 2845.52830188679 & 36.3148784193301 & 78.3570928981037 \tabularnewline
Trimmed Mean ( 23 / 32 ) & 2841.37254901961 & 35.3015576036327 & 80.4885886600997 \tabularnewline
Trimmed Mean ( 24 / 32 ) & 2836.93877551020 & 34.3152081494913 & 82.6729292490759 \tabularnewline
Trimmed Mean ( 25 / 32 ) & 2836.93877551020 & 33.2497197291383 & 85.3221861303107 \tabularnewline
Trimmed Mean ( 26 / 32 ) & 2828.48888888889 & 32.3178129295239 & 87.5210489972522 \tabularnewline
Trimmed Mean ( 27 / 32 ) & 2824.3488372093 & 31.2741403320947 & 90.309399625954 \tabularnewline
Trimmed Mean ( 28 / 32 ) & 2824.3488372093 & 30.5106290175376 & 92.5693415099984 \tabularnewline
Trimmed Mean ( 29 / 32 ) & 2818.92307692308 & 29.7971184066161 & 94.603882108854 \tabularnewline
Trimmed Mean ( 30 / 32 ) & 2816.64864864865 & 28.9958114458921 & 97.1398456602836 \tabularnewline
Trimmed Mean ( 31 / 32 ) & 2816.64864864865 & 28.1419511008868 & 100.087184380044 \tabularnewline
Trimmed Mean ( 32 / 32 ) & 2813.24242424242 & 27.1632630665464 & 103.567911460061 \tabularnewline
Median & 2833 &  &  \tabularnewline
Midrange & 3107.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 2826.04166666667 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 2836.93877551020 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 2836.93877551020 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 2836.93877551020 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 2836.93877551020 &  &  \tabularnewline
Midmean - Closest Observation & 2830.44 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 2836.93877551020 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 2836.93877551020 &  &  \tabularnewline
Number of observations & 97 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17601&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]2909.9381443299[/C][C]57.7515337533662[/C][C]50.3872010872834[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]2856.07522932221[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]2803.32014609952[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]2964.44311976285[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 32 )[/C][C]2908.77319587629[/C][C]57.4163995297153[/C][C]50.6610170561266[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 32 )[/C][C]2905.86597938144[/C][C]56.6312388536885[/C][C]51.3120680070056[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 32 )[/C][C]2909.29896907217[/C][C]55.689329023092[/C][C]52.2415877531188[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 32 )[/C][C]2905.05154639175[/C][C]54.3383296997274[/C][C]53.4622901080143[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 32 )[/C][C]2908.35051546392[/C][C]53.0193649404154[/C][C]54.854495498624[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 32 )[/C][C]2905.87628865979[/C][C]51.4247236562446[/C][C]56.5073778146969[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 32 )[/C][C]2912.80412371134[/C][C]50.2686033488174[/C][C]57.9447991323568[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 32 )[/C][C]2906.28865979381[/C][C]49.0416642041539[/C][C]59.2616239060592[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 32 )[/C][C]2906.19587628866[/C][C]48.4595489704640[/C][C]59.9715832695838[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 32 )[/C][C]2904.54639175258[/C][C]47.6229057873534[/C][C]60.9905326802612[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 32 )[/C][C]2899.78350515464[/C][C]46.7019048661619[/C][C]62.0913325369667[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 32 )[/C][C]2898.42268041237[/C][C]45.8406300854906[/C][C]63.2282469723246[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 32 )[/C][C]2892.79381443299[/C][C]44.0620509485644[/C][C]65.6527272824834[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 32 )[/C][C]2891.0618556701[/C][C]43.5637686167021[/C][C]66.3639062338075[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 32 )[/C][C]2890.28865979381[/C][C]43.4064418280762[/C][C]66.5866294971065[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 32 )[/C][C]2892.10309278350[/C][C]43.1821853892883[/C][C]66.9744494566715[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 32 )[/C][C]2893.32989690722[/C][C]42.8424868247656[/C][C]67.5341258489853[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 32 )[/C][C]2896.29896907217[/C][C]42.1372995263352[/C][C]68.7348026956976[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 32 )[/C][C]2896.29896907217[/C][C]41.2521429333733[/C][C]70.2096609562806[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 32 )[/C][C]2896.29896907217[/C][C]39.5783678336478[/C][C]73.1788380270158[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 32 )[/C][C]2895.86597938144[/C][C]38.9560551519768[/C][C]74.3367357932927[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 32 )[/C][C]2893.59793814433[/C][C]37.9891993258562[/C][C]76.168963534193[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 32 )[/C][C]2892.88659793814[/C][C]36.326160887694[/C][C]79.636452827531[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 32 )[/C][C]2886.20618556701[/C][C]35.3231551167521[/C][C]81.7086179314207[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 32 )[/C][C]2881.56701030928[/C][C]33.0855521359551[/C][C]87.0944211076893[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 32 )[/C][C]2876.20618556701[/C][C]32.2239963431461[/C][C]89.2566569006195[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 32 )[/C][C]2858.39175257732[/C][C]29.5235052430164[/C][C]96.8174926740265[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 32 )[/C][C]2848.86597938144[/C][C]28.0958511755522[/C][C]101.398101861402[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 32 )[/C][C]2844.08247422680[/C][C]27.2818340414415[/C][C]104.248214027935[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 32 )[/C][C]2836.65979381443[/C][C]26.217767342799[/C][C]108.196085376948[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 32 )[/C][C]2831.22680412371[/C][C]25.3318079712710[/C][C]111.765682391664[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 32 )[/C][C]2819.68041237113[/C][C]22.5078525166733[/C][C]125.275408228412[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 32 )[/C][C]2905.77894736842[/C][C]55.7139775686207[/C][C]52.1552952091688[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 32 )[/C][C]2902.65591397849[/C][C]53.7710340126541[/C][C]53.9817760115121[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 32 )[/C][C]2900.94505494505[/C][C]52.033429103162[/C][C]55.7515640415244[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 32 )[/C][C]2897.91011235955[/C][C]50.4526766820595[/C][C]57.4381837186057[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 32 )[/C][C]2895.91954022989[/C][C]49.1097114420685[/C][C]58.9683680720872[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 32 )[/C][C]2893.08235294118[/C][C]47.9477896832411[/C][C]60.3381797587299[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 32 )[/C][C]2893.08235294118[/C][C]47.0136094117651[/C][C]61.5371248695742[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 32 )[/C][C]2886.79012345679[/C][C]46.1857418676705[/C][C]62.5039245169624[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 32 )[/C][C]2883.79746835443[/C][C]45.4799297669021[/C][C]63.4081337226054[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 32 )[/C][C]2880.66233766234[/C][C]44.7631978972029[/C][C]64.3533633204151[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 32 )[/C][C]2877.57333333333[/C][C]44.0727170343148[/C][C]65.2914893150986[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 32 )[/C][C]2874.89041095890[/C][C]43.4200202547257[/C][C]66.2111715769181[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 32 )[/C][C]2872.21126760563[/C][C]42.7882433480278[/C][C]67.1261786618315[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 32 )[/C][C]2872.21126760563[/C][C]42.3242995346293[/C][C]67.861991791633[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 32 )[/C][C]2867.80597014925[/C][C]41.8361054478528[/C][C]68.5485883413281[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 32 )[/C][C]2865.56923076923[/C][C]41.2612745036873[/C][C]69.4493629980612[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 32 )[/C][C]2863.01587301587[/C][C]40.5892434406485[/C][C]70.5363202248968[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 32 )[/C][C]2860.18032786885[/C][C]39.8167695963787[/C][C]71.8335605038382[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 32 )[/C][C]2856.88135593220[/C][C]38.9765630003861[/C][C]73.2974160883274[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 32 )[/C][C]2853.35087719298[/C][C]38.0835752494036[/C][C]74.9233983024655[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 32 )[/C][C]2849.56363636364[/C][C]37.2540171484166[/C][C]76.4901037386447[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 32 )[/C][C]2845.52830188679[/C][C]36.3148784193301[/C][C]78.3570928981037[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 32 )[/C][C]2841.37254901961[/C][C]35.3015576036327[/C][C]80.4885886600997[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 32 )[/C][C]2836.93877551020[/C][C]34.3152081494913[/C][C]82.6729292490759[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 32 )[/C][C]2836.93877551020[/C][C]33.2497197291383[/C][C]85.3221861303107[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 32 )[/C][C]2828.48888888889[/C][C]32.3178129295239[/C][C]87.5210489972522[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 32 )[/C][C]2824.3488372093[/C][C]31.2741403320947[/C][C]90.309399625954[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 32 )[/C][C]2824.3488372093[/C][C]30.5106290175376[/C][C]92.5693415099984[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 32 )[/C][C]2818.92307692308[/C][C]29.7971184066161[/C][C]94.603882108854[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 32 )[/C][C]2816.64864864865[/C][C]28.9958114458921[/C][C]97.1398456602836[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 32 )[/C][C]2816.64864864865[/C][C]28.1419511008868[/C][C]100.087184380044[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 32 )[/C][C]2813.24242424242[/C][C]27.1632630665464[/C][C]103.567911460061[/C][/ROW]
[ROW][C]Median[/C][C]2833[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]3107.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]2826.04166666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]2836.93877551020[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]2836.93877551020[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]2836.93877551020[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]2836.93877551020[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]2830.44[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]2836.93877551020[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]2836.93877551020[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]97[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17601&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17601&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 Mean2909.938144329957.751533753366250.3872010872834
Geometric Mean2856.07522932221
Harmonic Mean2803.32014609952
Quadratic Mean2964.44311976285
Winsorized Mean ( 1 / 32 )2908.7731958762957.416399529715350.6610170561266
Winsorized Mean ( 2 / 32 )2905.8659793814456.631238853688551.3120680070056
Winsorized Mean ( 3 / 32 )2909.2989690721755.68932902309252.2415877531188
Winsorized Mean ( 4 / 32 )2905.0515463917554.338329699727453.4622901080143
Winsorized Mean ( 5 / 32 )2908.3505154639253.019364940415454.854495498624
Winsorized Mean ( 6 / 32 )2905.8762886597951.424723656244656.5073778146969
Winsorized Mean ( 7 / 32 )2912.8041237113450.268603348817457.9447991323568
Winsorized Mean ( 8 / 32 )2906.2886597938149.041664204153959.2616239060592
Winsorized Mean ( 9 / 32 )2906.1958762886648.459548970464059.9715832695838
Winsorized Mean ( 10 / 32 )2904.5463917525847.622905787353460.9905326802612
Winsorized Mean ( 11 / 32 )2899.7835051546446.701904866161962.0913325369667
Winsorized Mean ( 12 / 32 )2898.4226804123745.840630085490663.2282469723246
Winsorized Mean ( 13 / 32 )2892.7938144329944.062050948564465.6527272824834
Winsorized Mean ( 14 / 32 )2891.061855670143.563768616702166.3639062338075
Winsorized Mean ( 15 / 32 )2890.2886597938143.406441828076266.5866294971065
Winsorized Mean ( 16 / 32 )2892.1030927835043.182185389288366.9744494566715
Winsorized Mean ( 17 / 32 )2893.3298969072242.842486824765667.5341258489853
Winsorized Mean ( 18 / 32 )2896.2989690721742.137299526335268.7348026956976
Winsorized Mean ( 19 / 32 )2896.2989690721741.252142933373370.2096609562806
Winsorized Mean ( 20 / 32 )2896.2989690721739.578367833647873.1788380270158
Winsorized Mean ( 21 / 32 )2895.8659793814438.956055151976874.3367357932927
Winsorized Mean ( 22 / 32 )2893.5979381443337.989199325856276.168963534193
Winsorized Mean ( 23 / 32 )2892.8865979381436.32616088769479.636452827531
Winsorized Mean ( 24 / 32 )2886.2061855670135.323155116752181.7086179314207
Winsorized Mean ( 25 / 32 )2881.5670103092833.085552135955187.0944211076893
Winsorized Mean ( 26 / 32 )2876.2061855670132.223996343146189.2566569006195
Winsorized Mean ( 27 / 32 )2858.3917525773229.523505243016496.8174926740265
Winsorized Mean ( 28 / 32 )2848.8659793814428.0958511755522101.398101861402
Winsorized Mean ( 29 / 32 )2844.0824742268027.2818340414415104.248214027935
Winsorized Mean ( 30 / 32 )2836.6597938144326.217767342799108.196085376948
Winsorized Mean ( 31 / 32 )2831.2268041237125.3318079712710111.765682391664
Winsorized Mean ( 32 / 32 )2819.6804123711322.5078525166733125.275408228412
Trimmed Mean ( 1 / 32 )2905.7789473684255.713977568620752.1552952091688
Trimmed Mean ( 2 / 32 )2902.6559139784953.771034012654153.9817760115121
Trimmed Mean ( 3 / 32 )2900.9450549450552.03342910316255.7515640415244
Trimmed Mean ( 4 / 32 )2897.9101123595550.452676682059557.4381837186057
Trimmed Mean ( 5 / 32 )2895.9195402298949.109711442068558.9683680720872
Trimmed Mean ( 6 / 32 )2893.0823529411847.947789683241160.3381797587299
Trimmed Mean ( 7 / 32 )2893.0823529411847.013609411765161.5371248695742
Trimmed Mean ( 8 / 32 )2886.7901234567946.185741867670562.5039245169624
Trimmed Mean ( 9 / 32 )2883.7974683544345.479929766902163.4081337226054
Trimmed Mean ( 10 / 32 )2880.6623376623444.763197897202964.3533633204151
Trimmed Mean ( 11 / 32 )2877.5733333333344.072717034314865.2914893150986
Trimmed Mean ( 12 / 32 )2874.8904109589043.420020254725766.2111715769181
Trimmed Mean ( 13 / 32 )2872.2112676056342.788243348027867.1261786618315
Trimmed Mean ( 14 / 32 )2872.2112676056342.324299534629367.861991791633
Trimmed Mean ( 15 / 32 )2867.8059701492541.836105447852868.5485883413281
Trimmed Mean ( 16 / 32 )2865.5692307692341.261274503687369.4493629980612
Trimmed Mean ( 17 / 32 )2863.0158730158740.589243440648570.5363202248968
Trimmed Mean ( 18 / 32 )2860.1803278688539.816769596378771.8335605038382
Trimmed Mean ( 19 / 32 )2856.8813559322038.976563000386173.2974160883274
Trimmed Mean ( 20 / 32 )2853.3508771929838.083575249403674.9233983024655
Trimmed Mean ( 21 / 32 )2849.5636363636437.254017148416676.4901037386447
Trimmed Mean ( 22 / 32 )2845.5283018867936.314878419330178.3570928981037
Trimmed Mean ( 23 / 32 )2841.3725490196135.301557603632780.4885886600997
Trimmed Mean ( 24 / 32 )2836.9387755102034.315208149491382.6729292490759
Trimmed Mean ( 25 / 32 )2836.9387755102033.249719729138385.3221861303107
Trimmed Mean ( 26 / 32 )2828.4888888888932.317812929523987.5210489972522
Trimmed Mean ( 27 / 32 )2824.348837209331.274140332094790.309399625954
Trimmed Mean ( 28 / 32 )2824.348837209330.510629017537692.5693415099984
Trimmed Mean ( 29 / 32 )2818.9230769230829.797118406616194.603882108854
Trimmed Mean ( 30 / 32 )2816.6486486486528.995811445892197.1398456602836
Trimmed Mean ( 31 / 32 )2816.6486486486528.1419511008868100.087184380044
Trimmed Mean ( 32 / 32 )2813.2424242424227.1632630665464103.567911460061
Median2833
Midrange3107.5
Midmean - Weighted Average at Xnp2826.04166666667
Midmean - Weighted Average at X(n+1)p2836.93877551020
Midmean - Empirical Distribution Function2836.93877551020
Midmean - Empirical Distribution Function - Averaging2836.93877551020
Midmean - Empirical Distribution Function - Interpolation2836.93877551020
Midmean - Closest Observation2830.44
Midmean - True Basic - Statistics Graphics Toolkit2836.93877551020
Midmean - MS Excel (old versions)2836.93877551020
Number of observations97



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')