Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 20 Oct 2008 16:37:56 -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/t12245423145cgbmdu4fxt12og.htm/, Retrieved Sun, 19 May 2024 20:22:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18270, Retrieved Sun, 19 May 2024 20:22:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168
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 22:37:56] [7957bb37a64ed417bbed8444b0b0ea8a] [Current]
Feedback Forum
2008-10-27 18:13:37 [Evelyn Ongena] [reply
Je hebt enkel de link in het document vervat, zonder enige uitleg of conclusie wat het moeilijk maakt je hierop te beoordelen.

Post a new message
Dataseries X:
572
582
574
461
576
460
455
444
488
513
468
488
536
486
460
376
503
369
353
359
400
374
430
433
418
438
389
368
386
261
294
263
293
303
326
314
332
347
290
340
371
340
376
322
364
379
343
358
433
344
357
385
392
308
294
300
302
400
392
373
379
303
324
353
392
327
376
329
359
413
338
421
390
370
366
405
418
346
349
326
318
379
336
372
420
425
422
396
457
313
334
384
342
385
435
405
454




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18270&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18270&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18270&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'George Udny Yule' @ 72.249.76.132







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean386.7628865979387.0220072136386155.0786797607871
Geometric Mean381.010873303196
Harmonic Mean375.576427197663
Quadratic Mean392.834767604874
Winsorized Mean ( 1 / 32 )386.7216494845367.0005176273398655.2418649692747
Winsorized Mean ( 2 / 32 )387.2371134020626.8966937207233556.1482253791382
Winsorized Mean ( 3 / 32 )387.2680412371136.8658524814645756.40494640434
Winsorized Mean ( 4 / 32 )385.8247422680416.4715543696933159.6185584215876
Winsorized Mean ( 5 / 32 )384.6391752577326.2000960523371562.0376155483496
Winsorized Mean ( 6 / 32 )384.3917525773206.0144184699776663.9117072575011
Winsorized Mean ( 7 / 32 )383.4536082474235.7799351619628266.3421989178863
Winsorized Mean ( 8 / 32 )383.5360824742275.7678838472641366.4951120082192
Winsorized Mean ( 9 / 32 )383.3505154639185.7330738704934466.8664880522327
Winsorized Mean ( 10 / 32 )382.0103092783515.3285019228392171.6918779068023
Winsorized Mean ( 11 / 32 )381.7835051546395.1169784009913774.6111230566602
Winsorized Mean ( 12 / 32 )381.7835051546395.0798230261329775.1568515656092
Winsorized Mean ( 13 / 32 )382.3195876288665.0066868171303376.361794055255
Winsorized Mean ( 14 / 32 )382.4639175257734.8610650219571778.679037576787
Winsorized Mean ( 15 / 32 )382.4639175257734.7721058647947980.1457319602484
Winsorized Mean ( 16 / 32 )382.6288659793814.7042771260981181.3363787300403
Winsorized Mean ( 17 / 32 )380.8762886597944.4356378947673785.8673087605067
Winsorized Mean ( 18 / 32 )379.9484536082474.2498324995803089.4031596882394
Winsorized Mean ( 19 / 32 )379.7525773195884.1163551225337692.254571341706
Winsorized Mean ( 20 / 32 )379.9587628865983.9803511584887395.4586034642385
Winsorized Mean ( 21 / 32 )380.3917525773203.9265309548720696.8773089908606
Winsorized Mean ( 22 / 32 )380.1649484536083.77672835460968100.659860270225
Winsorized Mean ( 23 / 32 )379.4536082474233.5584835415763106.633515039200
Winsorized Mean ( 24 / 32 )379.206185567013.4005867363256111.511987480358
Winsorized Mean ( 25 / 32 )378.9484536082473.36692814602099112.550205164338
Winsorized Mean ( 26 / 32 )379.2164948453613.2679660305503116.040525299311
Winsorized Mean ( 27 / 32 )378.9381443298973.16298442200097119.803986922633
Winsorized Mean ( 28 / 32 )379.2268041237113.12897531186889121.198400858332
Winsorized Mean ( 29 / 32 )378.3298969072162.86811785159329131.908769612465
Winsorized Mean ( 30 / 32 )376.1649484536082.52809303311811148.793950035
Winsorized Mean ( 31 / 32 )376.804123711342.45192781188312153.676679176761
Winsorized Mean ( 32 / 32 )376.4742268041242.10200019206799179.102850810751
Trimmed Mean ( 1 / 32 )386.0315789473686.7359152147921857.3094474377642
Trimmed Mean ( 2 / 32 )385.3118279569896.431426655880759.9107862957081
Trimmed Mean ( 3 / 32 )384.2857142857146.1435868607099662.5507090561922
Trimmed Mean ( 4 / 32 )383.2022471910115.8217298328767765.8227465360848
Trimmed Mean ( 5 / 32 )382.4712643678165.5935541405387468.377145328029
Trimmed Mean ( 6 / 32 )381.9764705882355.4130503283553270.5658450259216
Trimmed Mean ( 7 / 32 )381.9764705882355.2532786033139772.7120146164092
Trimmed Mean ( 8 / 32 )381.1728395061735.1242822479467874.3856058395111
Trimmed Mean ( 9 / 32 )380.8101265822784.9767416188037576.5179621026444
Trimmed Mean ( 10 / 32 )380.4545454545454.8117517289238479.0677838109563
Trimmed Mean ( 11 / 32 )380.2533333333334.6995147663390880.9133181274267
Trimmed Mean ( 12 / 32 )380.0684931506854.6064414881594782.508047508608
Trimmed Mean ( 13 / 32 )379.8732394366204.5028910711874684.3620761486559
Trimmed Mean ( 14 / 32 )379.8732394366204.3922749258700186.4866716787714
Trimmed Mean ( 15 / 32 )379.3134328358214.2852923903449188.51518129555
Trimmed Mean ( 16 / 32 )3794.1720798170696690.8419820851361
Trimmed Mean ( 17 / 32 )378.6507936507944.0468428921610693.5669616392225
Trimmed Mean ( 18 / 32 )378.442622950823.943696955609795.9613852713772
Trimmed Mean ( 19 / 32 )378.3050847457633.8502244188570298.255333609376
Trimmed Mean ( 20 / 32 )378.1754385964913.75812593332272100.628729666366
Trimmed Mean ( 21 / 32 )378.0181818181823.66726266130437103.079112878085
Trimmed Mean ( 22 / 32 )377.8113207547173.56263228092186106.048362829339
Trimmed Mean ( 23 / 32 )377.6078431372553.45878573631035109.173528493866
Trimmed Mean ( 24 / 32 )377.4489795918373.36865569289698112.047360728409
Trimmed Mean ( 25 / 32 )377.4489795918373.28297191877150114.971735650142
Trimmed Mean ( 26 / 32 )377.1555555555563.17820156812495118.669488851227
Trimmed Mean ( 27 / 32 )376.9767441860473.06147576442121123.135629086816
Trimmed Mean ( 28 / 32 )376.9767441860472.93095745452539128.618975210301
Trimmed Mean ( 29 / 32 )376.5897435897442.76295084405982136.299834794162
Trimmed Mean ( 30 / 32 )376.4324324324322.60674239554420144.407223773197
Trimmed Mean ( 31 / 32 )376.4324324324322.48840769753424151.274420508118
Trimmed Mean ( 32 / 32 )376.4242424242422.34360441084392160.617654021522
Median376
Midrange421.5
Midmean - Weighted Average at Xnp376.520833333333
Midmean - Weighted Average at X(n+1)p377.448979591837
Midmean - Empirical Distribution Function377.448979591837
Midmean - Empirical Distribution Function - Averaging377.448979591837
Midmean - Empirical Distribution Function - Interpolation377.448979591837
Midmean - Closest Observation376.66
Midmean - True Basic - Statistics Graphics Toolkit377.448979591837
Midmean - MS Excel (old versions)377.448979591837
Number of observations97

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 386.762886597938 & 7.02200721363861 & 55.0786797607871 \tabularnewline
Geometric Mean & 381.010873303196 &  &  \tabularnewline
Harmonic Mean & 375.576427197663 &  &  \tabularnewline
Quadratic Mean & 392.834767604874 &  &  \tabularnewline
Winsorized Mean ( 1 / 32 ) & 386.721649484536 & 7.00051762733986 & 55.2418649692747 \tabularnewline
Winsorized Mean ( 2 / 32 ) & 387.237113402062 & 6.89669372072335 & 56.1482253791382 \tabularnewline
Winsorized Mean ( 3 / 32 ) & 387.268041237113 & 6.86585248146457 & 56.40494640434 \tabularnewline
Winsorized Mean ( 4 / 32 ) & 385.824742268041 & 6.47155436969331 & 59.6185584215876 \tabularnewline
Winsorized Mean ( 5 / 32 ) & 384.639175257732 & 6.20009605233715 & 62.0376155483496 \tabularnewline
Winsorized Mean ( 6 / 32 ) & 384.391752577320 & 6.01441846997766 & 63.9117072575011 \tabularnewline
Winsorized Mean ( 7 / 32 ) & 383.453608247423 & 5.77993516196282 & 66.3421989178863 \tabularnewline
Winsorized Mean ( 8 / 32 ) & 383.536082474227 & 5.76788384726413 & 66.4951120082192 \tabularnewline
Winsorized Mean ( 9 / 32 ) & 383.350515463918 & 5.73307387049344 & 66.8664880522327 \tabularnewline
Winsorized Mean ( 10 / 32 ) & 382.010309278351 & 5.32850192283921 & 71.6918779068023 \tabularnewline
Winsorized Mean ( 11 / 32 ) & 381.783505154639 & 5.11697840099137 & 74.6111230566602 \tabularnewline
Winsorized Mean ( 12 / 32 ) & 381.783505154639 & 5.07982302613297 & 75.1568515656092 \tabularnewline
Winsorized Mean ( 13 / 32 ) & 382.319587628866 & 5.00668681713033 & 76.361794055255 \tabularnewline
Winsorized Mean ( 14 / 32 ) & 382.463917525773 & 4.86106502195717 & 78.679037576787 \tabularnewline
Winsorized Mean ( 15 / 32 ) & 382.463917525773 & 4.77210586479479 & 80.1457319602484 \tabularnewline
Winsorized Mean ( 16 / 32 ) & 382.628865979381 & 4.70427712609811 & 81.3363787300403 \tabularnewline
Winsorized Mean ( 17 / 32 ) & 380.876288659794 & 4.43563789476737 & 85.8673087605067 \tabularnewline
Winsorized Mean ( 18 / 32 ) & 379.948453608247 & 4.24983249958030 & 89.4031596882394 \tabularnewline
Winsorized Mean ( 19 / 32 ) & 379.752577319588 & 4.11635512253376 & 92.254571341706 \tabularnewline
Winsorized Mean ( 20 / 32 ) & 379.958762886598 & 3.98035115848873 & 95.4586034642385 \tabularnewline
Winsorized Mean ( 21 / 32 ) & 380.391752577320 & 3.92653095487206 & 96.8773089908606 \tabularnewline
Winsorized Mean ( 22 / 32 ) & 380.164948453608 & 3.77672835460968 & 100.659860270225 \tabularnewline
Winsorized Mean ( 23 / 32 ) & 379.453608247423 & 3.5584835415763 & 106.633515039200 \tabularnewline
Winsorized Mean ( 24 / 32 ) & 379.20618556701 & 3.4005867363256 & 111.511987480358 \tabularnewline
Winsorized Mean ( 25 / 32 ) & 378.948453608247 & 3.36692814602099 & 112.550205164338 \tabularnewline
Winsorized Mean ( 26 / 32 ) & 379.216494845361 & 3.2679660305503 & 116.040525299311 \tabularnewline
Winsorized Mean ( 27 / 32 ) & 378.938144329897 & 3.16298442200097 & 119.803986922633 \tabularnewline
Winsorized Mean ( 28 / 32 ) & 379.226804123711 & 3.12897531186889 & 121.198400858332 \tabularnewline
Winsorized Mean ( 29 / 32 ) & 378.329896907216 & 2.86811785159329 & 131.908769612465 \tabularnewline
Winsorized Mean ( 30 / 32 ) & 376.164948453608 & 2.52809303311811 & 148.793950035 \tabularnewline
Winsorized Mean ( 31 / 32 ) & 376.80412371134 & 2.45192781188312 & 153.676679176761 \tabularnewline
Winsorized Mean ( 32 / 32 ) & 376.474226804124 & 2.10200019206799 & 179.102850810751 \tabularnewline
Trimmed Mean ( 1 / 32 ) & 386.031578947368 & 6.73591521479218 & 57.3094474377642 \tabularnewline
Trimmed Mean ( 2 / 32 ) & 385.311827956989 & 6.4314266558807 & 59.9107862957081 \tabularnewline
Trimmed Mean ( 3 / 32 ) & 384.285714285714 & 6.14358686070996 & 62.5507090561922 \tabularnewline
Trimmed Mean ( 4 / 32 ) & 383.202247191011 & 5.82172983287677 & 65.8227465360848 \tabularnewline
Trimmed Mean ( 5 / 32 ) & 382.471264367816 & 5.59355414053874 & 68.377145328029 \tabularnewline
Trimmed Mean ( 6 / 32 ) & 381.976470588235 & 5.41305032835532 & 70.5658450259216 \tabularnewline
Trimmed Mean ( 7 / 32 ) & 381.976470588235 & 5.25327860331397 & 72.7120146164092 \tabularnewline
Trimmed Mean ( 8 / 32 ) & 381.172839506173 & 5.12428224794678 & 74.3856058395111 \tabularnewline
Trimmed Mean ( 9 / 32 ) & 380.810126582278 & 4.97674161880375 & 76.5179621026444 \tabularnewline
Trimmed Mean ( 10 / 32 ) & 380.454545454545 & 4.81175172892384 & 79.0677838109563 \tabularnewline
Trimmed Mean ( 11 / 32 ) & 380.253333333333 & 4.69951476633908 & 80.9133181274267 \tabularnewline
Trimmed Mean ( 12 / 32 ) & 380.068493150685 & 4.60644148815947 & 82.508047508608 \tabularnewline
Trimmed Mean ( 13 / 32 ) & 379.873239436620 & 4.50289107118746 & 84.3620761486559 \tabularnewline
Trimmed Mean ( 14 / 32 ) & 379.873239436620 & 4.39227492587001 & 86.4866716787714 \tabularnewline
Trimmed Mean ( 15 / 32 ) & 379.313432835821 & 4.28529239034491 & 88.51518129555 \tabularnewline
Trimmed Mean ( 16 / 32 ) & 379 & 4.17207981706966 & 90.8419820851361 \tabularnewline
Trimmed Mean ( 17 / 32 ) & 378.650793650794 & 4.04684289216106 & 93.5669616392225 \tabularnewline
Trimmed Mean ( 18 / 32 ) & 378.44262295082 & 3.9436969556097 & 95.9613852713772 \tabularnewline
Trimmed Mean ( 19 / 32 ) & 378.305084745763 & 3.85022441885702 & 98.255333609376 \tabularnewline
Trimmed Mean ( 20 / 32 ) & 378.175438596491 & 3.75812593332272 & 100.628729666366 \tabularnewline
Trimmed Mean ( 21 / 32 ) & 378.018181818182 & 3.66726266130437 & 103.079112878085 \tabularnewline
Trimmed Mean ( 22 / 32 ) & 377.811320754717 & 3.56263228092186 & 106.048362829339 \tabularnewline
Trimmed Mean ( 23 / 32 ) & 377.607843137255 & 3.45878573631035 & 109.173528493866 \tabularnewline
Trimmed Mean ( 24 / 32 ) & 377.448979591837 & 3.36865569289698 & 112.047360728409 \tabularnewline
Trimmed Mean ( 25 / 32 ) & 377.448979591837 & 3.28297191877150 & 114.971735650142 \tabularnewline
Trimmed Mean ( 26 / 32 ) & 377.155555555556 & 3.17820156812495 & 118.669488851227 \tabularnewline
Trimmed Mean ( 27 / 32 ) & 376.976744186047 & 3.06147576442121 & 123.135629086816 \tabularnewline
Trimmed Mean ( 28 / 32 ) & 376.976744186047 & 2.93095745452539 & 128.618975210301 \tabularnewline
Trimmed Mean ( 29 / 32 ) & 376.589743589744 & 2.76295084405982 & 136.299834794162 \tabularnewline
Trimmed Mean ( 30 / 32 ) & 376.432432432432 & 2.60674239554420 & 144.407223773197 \tabularnewline
Trimmed Mean ( 31 / 32 ) & 376.432432432432 & 2.48840769753424 & 151.274420508118 \tabularnewline
Trimmed Mean ( 32 / 32 ) & 376.424242424242 & 2.34360441084392 & 160.617654021522 \tabularnewline
Median & 376 &  &  \tabularnewline
Midrange & 421.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 376.520833333333 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 377.448979591837 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 377.448979591837 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 377.448979591837 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 377.448979591837 &  &  \tabularnewline
Midmean - Closest Observation & 376.66 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 377.448979591837 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 377.448979591837 &  &  \tabularnewline
Number of observations & 97 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18270&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]386.762886597938[/C][C]7.02200721363861[/C][C]55.0786797607871[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]381.010873303196[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]375.576427197663[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]392.834767604874[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 32 )[/C][C]386.721649484536[/C][C]7.00051762733986[/C][C]55.2418649692747[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 32 )[/C][C]387.237113402062[/C][C]6.89669372072335[/C][C]56.1482253791382[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 32 )[/C][C]387.268041237113[/C][C]6.86585248146457[/C][C]56.40494640434[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 32 )[/C][C]385.824742268041[/C][C]6.47155436969331[/C][C]59.6185584215876[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 32 )[/C][C]384.639175257732[/C][C]6.20009605233715[/C][C]62.0376155483496[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 32 )[/C][C]384.391752577320[/C][C]6.01441846997766[/C][C]63.9117072575011[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 32 )[/C][C]383.453608247423[/C][C]5.77993516196282[/C][C]66.3421989178863[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 32 )[/C][C]383.536082474227[/C][C]5.76788384726413[/C][C]66.4951120082192[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 32 )[/C][C]383.350515463918[/C][C]5.73307387049344[/C][C]66.8664880522327[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 32 )[/C][C]382.010309278351[/C][C]5.32850192283921[/C][C]71.6918779068023[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 32 )[/C][C]381.783505154639[/C][C]5.11697840099137[/C][C]74.6111230566602[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 32 )[/C][C]381.783505154639[/C][C]5.07982302613297[/C][C]75.1568515656092[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 32 )[/C][C]382.319587628866[/C][C]5.00668681713033[/C][C]76.361794055255[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 32 )[/C][C]382.463917525773[/C][C]4.86106502195717[/C][C]78.679037576787[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 32 )[/C][C]382.463917525773[/C][C]4.77210586479479[/C][C]80.1457319602484[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 32 )[/C][C]382.628865979381[/C][C]4.70427712609811[/C][C]81.3363787300403[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 32 )[/C][C]380.876288659794[/C][C]4.43563789476737[/C][C]85.8673087605067[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 32 )[/C][C]379.948453608247[/C][C]4.24983249958030[/C][C]89.4031596882394[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 32 )[/C][C]379.752577319588[/C][C]4.11635512253376[/C][C]92.254571341706[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 32 )[/C][C]379.958762886598[/C][C]3.98035115848873[/C][C]95.4586034642385[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 32 )[/C][C]380.391752577320[/C][C]3.92653095487206[/C][C]96.8773089908606[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 32 )[/C][C]380.164948453608[/C][C]3.77672835460968[/C][C]100.659860270225[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 32 )[/C][C]379.453608247423[/C][C]3.5584835415763[/C][C]106.633515039200[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 32 )[/C][C]379.20618556701[/C][C]3.4005867363256[/C][C]111.511987480358[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 32 )[/C][C]378.948453608247[/C][C]3.36692814602099[/C][C]112.550205164338[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 32 )[/C][C]379.216494845361[/C][C]3.2679660305503[/C][C]116.040525299311[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 32 )[/C][C]378.938144329897[/C][C]3.16298442200097[/C][C]119.803986922633[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 32 )[/C][C]379.226804123711[/C][C]3.12897531186889[/C][C]121.198400858332[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 32 )[/C][C]378.329896907216[/C][C]2.86811785159329[/C][C]131.908769612465[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 32 )[/C][C]376.164948453608[/C][C]2.52809303311811[/C][C]148.793950035[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 32 )[/C][C]376.80412371134[/C][C]2.45192781188312[/C][C]153.676679176761[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 32 )[/C][C]376.474226804124[/C][C]2.10200019206799[/C][C]179.102850810751[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 32 )[/C][C]386.031578947368[/C][C]6.73591521479218[/C][C]57.3094474377642[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 32 )[/C][C]385.311827956989[/C][C]6.4314266558807[/C][C]59.9107862957081[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 32 )[/C][C]384.285714285714[/C][C]6.14358686070996[/C][C]62.5507090561922[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 32 )[/C][C]383.202247191011[/C][C]5.82172983287677[/C][C]65.8227465360848[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 32 )[/C][C]382.471264367816[/C][C]5.59355414053874[/C][C]68.377145328029[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 32 )[/C][C]381.976470588235[/C][C]5.41305032835532[/C][C]70.5658450259216[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 32 )[/C][C]381.976470588235[/C][C]5.25327860331397[/C][C]72.7120146164092[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 32 )[/C][C]381.172839506173[/C][C]5.12428224794678[/C][C]74.3856058395111[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 32 )[/C][C]380.810126582278[/C][C]4.97674161880375[/C][C]76.5179621026444[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 32 )[/C][C]380.454545454545[/C][C]4.81175172892384[/C][C]79.0677838109563[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 32 )[/C][C]380.253333333333[/C][C]4.69951476633908[/C][C]80.9133181274267[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 32 )[/C][C]380.068493150685[/C][C]4.60644148815947[/C][C]82.508047508608[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 32 )[/C][C]379.873239436620[/C][C]4.50289107118746[/C][C]84.3620761486559[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 32 )[/C][C]379.873239436620[/C][C]4.39227492587001[/C][C]86.4866716787714[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 32 )[/C][C]379.313432835821[/C][C]4.28529239034491[/C][C]88.51518129555[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 32 )[/C][C]379[/C][C]4.17207981706966[/C][C]90.8419820851361[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 32 )[/C][C]378.650793650794[/C][C]4.04684289216106[/C][C]93.5669616392225[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 32 )[/C][C]378.44262295082[/C][C]3.9436969556097[/C][C]95.9613852713772[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 32 )[/C][C]378.305084745763[/C][C]3.85022441885702[/C][C]98.255333609376[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 32 )[/C][C]378.175438596491[/C][C]3.75812593332272[/C][C]100.628729666366[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 32 )[/C][C]378.018181818182[/C][C]3.66726266130437[/C][C]103.079112878085[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 32 )[/C][C]377.811320754717[/C][C]3.56263228092186[/C][C]106.048362829339[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 32 )[/C][C]377.607843137255[/C][C]3.45878573631035[/C][C]109.173528493866[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 32 )[/C][C]377.448979591837[/C][C]3.36865569289698[/C][C]112.047360728409[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 32 )[/C][C]377.448979591837[/C][C]3.28297191877150[/C][C]114.971735650142[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 32 )[/C][C]377.155555555556[/C][C]3.17820156812495[/C][C]118.669488851227[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 32 )[/C][C]376.976744186047[/C][C]3.06147576442121[/C][C]123.135629086816[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 32 )[/C][C]376.976744186047[/C][C]2.93095745452539[/C][C]128.618975210301[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 32 )[/C][C]376.589743589744[/C][C]2.76295084405982[/C][C]136.299834794162[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 32 )[/C][C]376.432432432432[/C][C]2.60674239554420[/C][C]144.407223773197[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 32 )[/C][C]376.432432432432[/C][C]2.48840769753424[/C][C]151.274420508118[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 32 )[/C][C]376.424242424242[/C][C]2.34360441084392[/C][C]160.617654021522[/C][/ROW]
[ROW][C]Median[/C][C]376[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]421.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]376.520833333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]377.448979591837[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]377.448979591837[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]377.448979591837[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]377.448979591837[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]376.66[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]377.448979591837[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]377.448979591837[/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=18270&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18270&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 Mean386.7628865979387.0220072136386155.0786797607871
Geometric Mean381.010873303196
Harmonic Mean375.576427197663
Quadratic Mean392.834767604874
Winsorized Mean ( 1 / 32 )386.7216494845367.0005176273398655.2418649692747
Winsorized Mean ( 2 / 32 )387.2371134020626.8966937207233556.1482253791382
Winsorized Mean ( 3 / 32 )387.2680412371136.8658524814645756.40494640434
Winsorized Mean ( 4 / 32 )385.8247422680416.4715543696933159.6185584215876
Winsorized Mean ( 5 / 32 )384.6391752577326.2000960523371562.0376155483496
Winsorized Mean ( 6 / 32 )384.3917525773206.0144184699776663.9117072575011
Winsorized Mean ( 7 / 32 )383.4536082474235.7799351619628266.3421989178863
Winsorized Mean ( 8 / 32 )383.5360824742275.7678838472641366.4951120082192
Winsorized Mean ( 9 / 32 )383.3505154639185.7330738704934466.8664880522327
Winsorized Mean ( 10 / 32 )382.0103092783515.3285019228392171.6918779068023
Winsorized Mean ( 11 / 32 )381.7835051546395.1169784009913774.6111230566602
Winsorized Mean ( 12 / 32 )381.7835051546395.0798230261329775.1568515656092
Winsorized Mean ( 13 / 32 )382.3195876288665.0066868171303376.361794055255
Winsorized Mean ( 14 / 32 )382.4639175257734.8610650219571778.679037576787
Winsorized Mean ( 15 / 32 )382.4639175257734.7721058647947980.1457319602484
Winsorized Mean ( 16 / 32 )382.6288659793814.7042771260981181.3363787300403
Winsorized Mean ( 17 / 32 )380.8762886597944.4356378947673785.8673087605067
Winsorized Mean ( 18 / 32 )379.9484536082474.2498324995803089.4031596882394
Winsorized Mean ( 19 / 32 )379.7525773195884.1163551225337692.254571341706
Winsorized Mean ( 20 / 32 )379.9587628865983.9803511584887395.4586034642385
Winsorized Mean ( 21 / 32 )380.3917525773203.9265309548720696.8773089908606
Winsorized Mean ( 22 / 32 )380.1649484536083.77672835460968100.659860270225
Winsorized Mean ( 23 / 32 )379.4536082474233.5584835415763106.633515039200
Winsorized Mean ( 24 / 32 )379.206185567013.4005867363256111.511987480358
Winsorized Mean ( 25 / 32 )378.9484536082473.36692814602099112.550205164338
Winsorized Mean ( 26 / 32 )379.2164948453613.2679660305503116.040525299311
Winsorized Mean ( 27 / 32 )378.9381443298973.16298442200097119.803986922633
Winsorized Mean ( 28 / 32 )379.2268041237113.12897531186889121.198400858332
Winsorized Mean ( 29 / 32 )378.3298969072162.86811785159329131.908769612465
Winsorized Mean ( 30 / 32 )376.1649484536082.52809303311811148.793950035
Winsorized Mean ( 31 / 32 )376.804123711342.45192781188312153.676679176761
Winsorized Mean ( 32 / 32 )376.4742268041242.10200019206799179.102850810751
Trimmed Mean ( 1 / 32 )386.0315789473686.7359152147921857.3094474377642
Trimmed Mean ( 2 / 32 )385.3118279569896.431426655880759.9107862957081
Trimmed Mean ( 3 / 32 )384.2857142857146.1435868607099662.5507090561922
Trimmed Mean ( 4 / 32 )383.2022471910115.8217298328767765.8227465360848
Trimmed Mean ( 5 / 32 )382.4712643678165.5935541405387468.377145328029
Trimmed Mean ( 6 / 32 )381.9764705882355.4130503283553270.5658450259216
Trimmed Mean ( 7 / 32 )381.9764705882355.2532786033139772.7120146164092
Trimmed Mean ( 8 / 32 )381.1728395061735.1242822479467874.3856058395111
Trimmed Mean ( 9 / 32 )380.8101265822784.9767416188037576.5179621026444
Trimmed Mean ( 10 / 32 )380.4545454545454.8117517289238479.0677838109563
Trimmed Mean ( 11 / 32 )380.2533333333334.6995147663390880.9133181274267
Trimmed Mean ( 12 / 32 )380.0684931506854.6064414881594782.508047508608
Trimmed Mean ( 13 / 32 )379.8732394366204.5028910711874684.3620761486559
Trimmed Mean ( 14 / 32 )379.8732394366204.3922749258700186.4866716787714
Trimmed Mean ( 15 / 32 )379.3134328358214.2852923903449188.51518129555
Trimmed Mean ( 16 / 32 )3794.1720798170696690.8419820851361
Trimmed Mean ( 17 / 32 )378.6507936507944.0468428921610693.5669616392225
Trimmed Mean ( 18 / 32 )378.442622950823.943696955609795.9613852713772
Trimmed Mean ( 19 / 32 )378.3050847457633.8502244188570298.255333609376
Trimmed Mean ( 20 / 32 )378.1754385964913.75812593332272100.628729666366
Trimmed Mean ( 21 / 32 )378.0181818181823.66726266130437103.079112878085
Trimmed Mean ( 22 / 32 )377.8113207547173.56263228092186106.048362829339
Trimmed Mean ( 23 / 32 )377.6078431372553.45878573631035109.173528493866
Trimmed Mean ( 24 / 32 )377.4489795918373.36865569289698112.047360728409
Trimmed Mean ( 25 / 32 )377.4489795918373.28297191877150114.971735650142
Trimmed Mean ( 26 / 32 )377.1555555555563.17820156812495118.669488851227
Trimmed Mean ( 27 / 32 )376.9767441860473.06147576442121123.135629086816
Trimmed Mean ( 28 / 32 )376.9767441860472.93095745452539128.618975210301
Trimmed Mean ( 29 / 32 )376.5897435897442.76295084405982136.299834794162
Trimmed Mean ( 30 / 32 )376.4324324324322.60674239554420144.407223773197
Trimmed Mean ( 31 / 32 )376.4324324324322.48840769753424151.274420508118
Trimmed Mean ( 32 / 32 )376.4242424242422.34360441084392160.617654021522
Median376
Midrange421.5
Midmean - Weighted Average at Xnp376.520833333333
Midmean - Weighted Average at X(n+1)p377.448979591837
Midmean - Empirical Distribution Function377.448979591837
Midmean - Empirical Distribution Function - Averaging377.448979591837
Midmean - Empirical Distribution Function - Interpolation377.448979591837
Midmean - Closest Observation376.66
Midmean - True Basic - Statistics Graphics Toolkit377.448979591837
Midmean - MS Excel (old versions)377.448979591837
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')