Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationSun, 07 Dec 2008 13:13:33 -0700
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/Dec/07/t1228681030ad9tfnwfsw34lf0.htm/, Retrieved Sun, 19 May 2024 10:48:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30296, Retrieved Sun, 19 May 2024 10:48:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact189
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Percentiles] [Percentile Tijdre...] [2008-10-16 15:43:46] [819b576fab25b35cfda70f80599828ec]
-         [Percentiles] [paper 1.5 percent...] [2008-12-07 20:13:33] [c577d4c76516de948d1234ed72fcf120] [Current]
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Dataseries X:
493.000
481.000
462.000
457.000
442.000
439.000
488.000
521.000
501.000
485.000
464.000
460.000
467.000
460.000
448.000
443.000
436.000
431.000
484.000
510.000
513.000
503.000
471.000
471.000
476.000
475.000
470.000
461.000
455.000
456.000
517.000
525.000
523.000
519.000
509.000
512.000
519.000
517.000
510.000
509.000
501.000
507.000
569.000
580.000
578.000
565.000
547.000
555.000
562.000
561.000
555.000
544.000
537.000
543.000
594.000
611.000
613.000
611.000
594.000
595.000




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30296&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30296&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30296&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Percentiles - Ungrouped Data
pWeighted Average at XnpWeighted Average at X(n+1)pEmpirical Distribution FunctionEmpirical Distribution Function - AveragingEmpirical Distribution Function - InterpolationClosest ObservationTrue Basic - Statistics Graphics ToolkitMS Excel (old versions)
0.02432432.1436436436.54431434.9431
0.04437.2437.32439439440.08436437.68436
0.06440.8440.98442442442.54442440.02442
0.08442.8442.88443443446.6443442.12443
0.1448448.7448451.5454.3448454.3448
0.12455.2455.32456456456.08455455.68455
0.14456.4456.54457457457.78456456.46457
0.16458.8459.28460460460460457.72460
0.18460460460460460.62460460460
0.2461461.2461461.5461.8461461.8461
0.22462.4462.84464464463.96462463.16462
0.24465.2465.92467467467.48464465.08467
0.26468.8469.58470470470.34470467.42470
0.28470.8471471471471471471471
0.3471472.2471473473.8471473.8471
0.32475.2475.52476476475.88475475.48476
0.34478479.7481481481.18476477.3481
0.36482.8483.88484484484.24484481.12484
0.38484.8485.54485485486.26485487.46485
0.4488490488490.5491488491488
0.42494.6497.96501501499.24493496.04501
0.44501501501501501501501501
0.46502.2503.24503503503.56503506.76503
0.48506.2507.56507507507.64507508.44507
0.5509509509509509509509509
0.52509.2509.72510510509.68509509.28510
0.54510510510510510510510510
0.56511.2512.16512512512.04512512.84512
0.58512.8514.52513513513.88513515.48513
0.6517517517517517517517517
0.62517.4518.64519519518.16517517.36519
0.64519519.08519519519519520.92519
0.66520.2521.52521521520.88521522.48521
0.68522.6523.96523523523.24523524.04523
0.7525533.4525531528.6525528.6537
0.72538.2542.52543543539.88537537.48543
0.74543.4544.42544544543.66543546.58544
0.76545.8549.88547547546.52547552.12547
0.78553.4555555555555555555555
0.8555559.8555558556.2555556.2561
0.82561.2562.06562562561.38561564.94562
0.84563.2565.96565565563.68562568.04565
0.86567.4573.14569569567.96569573.86569
0.88576.2579.36578578577.28578578.64580
0.9580592.6580587581.4580581.4594
0.92594594.12594594594594594.88594
0.94594.4600.44595595594.46594605.56595
0.96604.6611611611605.24611611611
0.98611612.56611611611611611.44613

\begin{tabular}{lllllllll}
\hline
Percentiles - Ungrouped Data \tabularnewline
p & Weighted Average at Xnp & Weighted Average at X(n+1)p & Empirical Distribution Function & Empirical Distribution Function - Averaging & Empirical Distribution Function - Interpolation & Closest Observation & True Basic - Statistics Graphics Toolkit & MS Excel (old versions) \tabularnewline
0.02 & 432 & 432.1 & 436 & 436 & 436.54 & 431 & 434.9 & 431 \tabularnewline
0.04 & 437.2 & 437.32 & 439 & 439 & 440.08 & 436 & 437.68 & 436 \tabularnewline
0.06 & 440.8 & 440.98 & 442 & 442 & 442.54 & 442 & 440.02 & 442 \tabularnewline
0.08 & 442.8 & 442.88 & 443 & 443 & 446.6 & 443 & 442.12 & 443 \tabularnewline
0.1 & 448 & 448.7 & 448 & 451.5 & 454.3 & 448 & 454.3 & 448 \tabularnewline
0.12 & 455.2 & 455.32 & 456 & 456 & 456.08 & 455 & 455.68 & 455 \tabularnewline
0.14 & 456.4 & 456.54 & 457 & 457 & 457.78 & 456 & 456.46 & 457 \tabularnewline
0.16 & 458.8 & 459.28 & 460 & 460 & 460 & 460 & 457.72 & 460 \tabularnewline
0.18 & 460 & 460 & 460 & 460 & 460.62 & 460 & 460 & 460 \tabularnewline
0.2 & 461 & 461.2 & 461 & 461.5 & 461.8 & 461 & 461.8 & 461 \tabularnewline
0.22 & 462.4 & 462.84 & 464 & 464 & 463.96 & 462 & 463.16 & 462 \tabularnewline
0.24 & 465.2 & 465.92 & 467 & 467 & 467.48 & 464 & 465.08 & 467 \tabularnewline
0.26 & 468.8 & 469.58 & 470 & 470 & 470.34 & 470 & 467.42 & 470 \tabularnewline
0.28 & 470.8 & 471 & 471 & 471 & 471 & 471 & 471 & 471 \tabularnewline
0.3 & 471 & 472.2 & 471 & 473 & 473.8 & 471 & 473.8 & 471 \tabularnewline
0.32 & 475.2 & 475.52 & 476 & 476 & 475.88 & 475 & 475.48 & 476 \tabularnewline
0.34 & 478 & 479.7 & 481 & 481 & 481.18 & 476 & 477.3 & 481 \tabularnewline
0.36 & 482.8 & 483.88 & 484 & 484 & 484.24 & 484 & 481.12 & 484 \tabularnewline
0.38 & 484.8 & 485.54 & 485 & 485 & 486.26 & 485 & 487.46 & 485 \tabularnewline
0.4 & 488 & 490 & 488 & 490.5 & 491 & 488 & 491 & 488 \tabularnewline
0.42 & 494.6 & 497.96 & 501 & 501 & 499.24 & 493 & 496.04 & 501 \tabularnewline
0.44 & 501 & 501 & 501 & 501 & 501 & 501 & 501 & 501 \tabularnewline
0.46 & 502.2 & 503.24 & 503 & 503 & 503.56 & 503 & 506.76 & 503 \tabularnewline
0.48 & 506.2 & 507.56 & 507 & 507 & 507.64 & 507 & 508.44 & 507 \tabularnewline
0.5 & 509 & 509 & 509 & 509 & 509 & 509 & 509 & 509 \tabularnewline
0.52 & 509.2 & 509.72 & 510 & 510 & 509.68 & 509 & 509.28 & 510 \tabularnewline
0.54 & 510 & 510 & 510 & 510 & 510 & 510 & 510 & 510 \tabularnewline
0.56 & 511.2 & 512.16 & 512 & 512 & 512.04 & 512 & 512.84 & 512 \tabularnewline
0.58 & 512.8 & 514.52 & 513 & 513 & 513.88 & 513 & 515.48 & 513 \tabularnewline
0.6 & 517 & 517 & 517 & 517 & 517 & 517 & 517 & 517 \tabularnewline
0.62 & 517.4 & 518.64 & 519 & 519 & 518.16 & 517 & 517.36 & 519 \tabularnewline
0.64 & 519 & 519.08 & 519 & 519 & 519 & 519 & 520.92 & 519 \tabularnewline
0.66 & 520.2 & 521.52 & 521 & 521 & 520.88 & 521 & 522.48 & 521 \tabularnewline
0.68 & 522.6 & 523.96 & 523 & 523 & 523.24 & 523 & 524.04 & 523 \tabularnewline
0.7 & 525 & 533.4 & 525 & 531 & 528.6 & 525 & 528.6 & 537 \tabularnewline
0.72 & 538.2 & 542.52 & 543 & 543 & 539.88 & 537 & 537.48 & 543 \tabularnewline
0.74 & 543.4 & 544.42 & 544 & 544 & 543.66 & 543 & 546.58 & 544 \tabularnewline
0.76 & 545.8 & 549.88 & 547 & 547 & 546.52 & 547 & 552.12 & 547 \tabularnewline
0.78 & 553.4 & 555 & 555 & 555 & 555 & 555 & 555 & 555 \tabularnewline
0.8 & 555 & 559.8 & 555 & 558 & 556.2 & 555 & 556.2 & 561 \tabularnewline
0.82 & 561.2 & 562.06 & 562 & 562 & 561.38 & 561 & 564.94 & 562 \tabularnewline
0.84 & 563.2 & 565.96 & 565 & 565 & 563.68 & 562 & 568.04 & 565 \tabularnewline
0.86 & 567.4 & 573.14 & 569 & 569 & 567.96 & 569 & 573.86 & 569 \tabularnewline
0.88 & 576.2 & 579.36 & 578 & 578 & 577.28 & 578 & 578.64 & 580 \tabularnewline
0.9 & 580 & 592.6 & 580 & 587 & 581.4 & 580 & 581.4 & 594 \tabularnewline
0.92 & 594 & 594.12 & 594 & 594 & 594 & 594 & 594.88 & 594 \tabularnewline
0.94 & 594.4 & 600.44 & 595 & 595 & 594.46 & 594 & 605.56 & 595 \tabularnewline
0.96 & 604.6 & 611 & 611 & 611 & 605.24 & 611 & 611 & 611 \tabularnewline
0.98 & 611 & 612.56 & 611 & 611 & 611 & 611 & 611.44 & 613 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30296&T=1

[TABLE]
[ROW][C]Percentiles - Ungrouped Data[/C][/ROW]
[ROW][C]p[/C][C]Weighted Average at Xnp[/C][C]Weighted Average at X(n+1)p[/C][C]Empirical Distribution Function[/C][C]Empirical Distribution Function - Averaging[/C][C]Empirical Distribution Function - Interpolation[/C][C]Closest Observation[/C][C]True Basic - Statistics Graphics Toolkit[/C][C]MS Excel (old versions)[/C][/ROW]
[ROW][C]0.02[/C][C]432[/C][C]432.1[/C][C]436[/C][C]436[/C][C]436.54[/C][C]431[/C][C]434.9[/C][C]431[/C][/ROW]
[ROW][C]0.04[/C][C]437.2[/C][C]437.32[/C][C]439[/C][C]439[/C][C]440.08[/C][C]436[/C][C]437.68[/C][C]436[/C][/ROW]
[ROW][C]0.06[/C][C]440.8[/C][C]440.98[/C][C]442[/C][C]442[/C][C]442.54[/C][C]442[/C][C]440.02[/C][C]442[/C][/ROW]
[ROW][C]0.08[/C][C]442.8[/C][C]442.88[/C][C]443[/C][C]443[/C][C]446.6[/C][C]443[/C][C]442.12[/C][C]443[/C][/ROW]
[ROW][C]0.1[/C][C]448[/C][C]448.7[/C][C]448[/C][C]451.5[/C][C]454.3[/C][C]448[/C][C]454.3[/C][C]448[/C][/ROW]
[ROW][C]0.12[/C][C]455.2[/C][C]455.32[/C][C]456[/C][C]456[/C][C]456.08[/C][C]455[/C][C]455.68[/C][C]455[/C][/ROW]
[ROW][C]0.14[/C][C]456.4[/C][C]456.54[/C][C]457[/C][C]457[/C][C]457.78[/C][C]456[/C][C]456.46[/C][C]457[/C][/ROW]
[ROW][C]0.16[/C][C]458.8[/C][C]459.28[/C][C]460[/C][C]460[/C][C]460[/C][C]460[/C][C]457.72[/C][C]460[/C][/ROW]
[ROW][C]0.18[/C][C]460[/C][C]460[/C][C]460[/C][C]460[/C][C]460.62[/C][C]460[/C][C]460[/C][C]460[/C][/ROW]
[ROW][C]0.2[/C][C]461[/C][C]461.2[/C][C]461[/C][C]461.5[/C][C]461.8[/C][C]461[/C][C]461.8[/C][C]461[/C][/ROW]
[ROW][C]0.22[/C][C]462.4[/C][C]462.84[/C][C]464[/C][C]464[/C][C]463.96[/C][C]462[/C][C]463.16[/C][C]462[/C][/ROW]
[ROW][C]0.24[/C][C]465.2[/C][C]465.92[/C][C]467[/C][C]467[/C][C]467.48[/C][C]464[/C][C]465.08[/C][C]467[/C][/ROW]
[ROW][C]0.26[/C][C]468.8[/C][C]469.58[/C][C]470[/C][C]470[/C][C]470.34[/C][C]470[/C][C]467.42[/C][C]470[/C][/ROW]
[ROW][C]0.28[/C][C]470.8[/C][C]471[/C][C]471[/C][C]471[/C][C]471[/C][C]471[/C][C]471[/C][C]471[/C][/ROW]
[ROW][C]0.3[/C][C]471[/C][C]472.2[/C][C]471[/C][C]473[/C][C]473.8[/C][C]471[/C][C]473.8[/C][C]471[/C][/ROW]
[ROW][C]0.32[/C][C]475.2[/C][C]475.52[/C][C]476[/C][C]476[/C][C]475.88[/C][C]475[/C][C]475.48[/C][C]476[/C][/ROW]
[ROW][C]0.34[/C][C]478[/C][C]479.7[/C][C]481[/C][C]481[/C][C]481.18[/C][C]476[/C][C]477.3[/C][C]481[/C][/ROW]
[ROW][C]0.36[/C][C]482.8[/C][C]483.88[/C][C]484[/C][C]484[/C][C]484.24[/C][C]484[/C][C]481.12[/C][C]484[/C][/ROW]
[ROW][C]0.38[/C][C]484.8[/C][C]485.54[/C][C]485[/C][C]485[/C][C]486.26[/C][C]485[/C][C]487.46[/C][C]485[/C][/ROW]
[ROW][C]0.4[/C][C]488[/C][C]490[/C][C]488[/C][C]490.5[/C][C]491[/C][C]488[/C][C]491[/C][C]488[/C][/ROW]
[ROW][C]0.42[/C][C]494.6[/C][C]497.96[/C][C]501[/C][C]501[/C][C]499.24[/C][C]493[/C][C]496.04[/C][C]501[/C][/ROW]
[ROW][C]0.44[/C][C]501[/C][C]501[/C][C]501[/C][C]501[/C][C]501[/C][C]501[/C][C]501[/C][C]501[/C][/ROW]
[ROW][C]0.46[/C][C]502.2[/C][C]503.24[/C][C]503[/C][C]503[/C][C]503.56[/C][C]503[/C][C]506.76[/C][C]503[/C][/ROW]
[ROW][C]0.48[/C][C]506.2[/C][C]507.56[/C][C]507[/C][C]507[/C][C]507.64[/C][C]507[/C][C]508.44[/C][C]507[/C][/ROW]
[ROW][C]0.5[/C][C]509[/C][C]509[/C][C]509[/C][C]509[/C][C]509[/C][C]509[/C][C]509[/C][C]509[/C][/ROW]
[ROW][C]0.52[/C][C]509.2[/C][C]509.72[/C][C]510[/C][C]510[/C][C]509.68[/C][C]509[/C][C]509.28[/C][C]510[/C][/ROW]
[ROW][C]0.54[/C][C]510[/C][C]510[/C][C]510[/C][C]510[/C][C]510[/C][C]510[/C][C]510[/C][C]510[/C][/ROW]
[ROW][C]0.56[/C][C]511.2[/C][C]512.16[/C][C]512[/C][C]512[/C][C]512.04[/C][C]512[/C][C]512.84[/C][C]512[/C][/ROW]
[ROW][C]0.58[/C][C]512.8[/C][C]514.52[/C][C]513[/C][C]513[/C][C]513.88[/C][C]513[/C][C]515.48[/C][C]513[/C][/ROW]
[ROW][C]0.6[/C][C]517[/C][C]517[/C][C]517[/C][C]517[/C][C]517[/C][C]517[/C][C]517[/C][C]517[/C][/ROW]
[ROW][C]0.62[/C][C]517.4[/C][C]518.64[/C][C]519[/C][C]519[/C][C]518.16[/C][C]517[/C][C]517.36[/C][C]519[/C][/ROW]
[ROW][C]0.64[/C][C]519[/C][C]519.08[/C][C]519[/C][C]519[/C][C]519[/C][C]519[/C][C]520.92[/C][C]519[/C][/ROW]
[ROW][C]0.66[/C][C]520.2[/C][C]521.52[/C][C]521[/C][C]521[/C][C]520.88[/C][C]521[/C][C]522.48[/C][C]521[/C][/ROW]
[ROW][C]0.68[/C][C]522.6[/C][C]523.96[/C][C]523[/C][C]523[/C][C]523.24[/C][C]523[/C][C]524.04[/C][C]523[/C][/ROW]
[ROW][C]0.7[/C][C]525[/C][C]533.4[/C][C]525[/C][C]531[/C][C]528.6[/C][C]525[/C][C]528.6[/C][C]537[/C][/ROW]
[ROW][C]0.72[/C][C]538.2[/C][C]542.52[/C][C]543[/C][C]543[/C][C]539.88[/C][C]537[/C][C]537.48[/C][C]543[/C][/ROW]
[ROW][C]0.74[/C][C]543.4[/C][C]544.42[/C][C]544[/C][C]544[/C][C]543.66[/C][C]543[/C][C]546.58[/C][C]544[/C][/ROW]
[ROW][C]0.76[/C][C]545.8[/C][C]549.88[/C][C]547[/C][C]547[/C][C]546.52[/C][C]547[/C][C]552.12[/C][C]547[/C][/ROW]
[ROW][C]0.78[/C][C]553.4[/C][C]555[/C][C]555[/C][C]555[/C][C]555[/C][C]555[/C][C]555[/C][C]555[/C][/ROW]
[ROW][C]0.8[/C][C]555[/C][C]559.8[/C][C]555[/C][C]558[/C][C]556.2[/C][C]555[/C][C]556.2[/C][C]561[/C][/ROW]
[ROW][C]0.82[/C][C]561.2[/C][C]562.06[/C][C]562[/C][C]562[/C][C]561.38[/C][C]561[/C][C]564.94[/C][C]562[/C][/ROW]
[ROW][C]0.84[/C][C]563.2[/C][C]565.96[/C][C]565[/C][C]565[/C][C]563.68[/C][C]562[/C][C]568.04[/C][C]565[/C][/ROW]
[ROW][C]0.86[/C][C]567.4[/C][C]573.14[/C][C]569[/C][C]569[/C][C]567.96[/C][C]569[/C][C]573.86[/C][C]569[/C][/ROW]
[ROW][C]0.88[/C][C]576.2[/C][C]579.36[/C][C]578[/C][C]578[/C][C]577.28[/C][C]578[/C][C]578.64[/C][C]580[/C][/ROW]
[ROW][C]0.9[/C][C]580[/C][C]592.6[/C][C]580[/C][C]587[/C][C]581.4[/C][C]580[/C][C]581.4[/C][C]594[/C][/ROW]
[ROW][C]0.92[/C][C]594[/C][C]594.12[/C][C]594[/C][C]594[/C][C]594[/C][C]594[/C][C]594.88[/C][C]594[/C][/ROW]
[ROW][C]0.94[/C][C]594.4[/C][C]600.44[/C][C]595[/C][C]595[/C][C]594.46[/C][C]594[/C][C]605.56[/C][C]595[/C][/ROW]
[ROW][C]0.96[/C][C]604.6[/C][C]611[/C][C]611[/C][C]611[/C][C]605.24[/C][C]611[/C][C]611[/C][C]611[/C][/ROW]
[ROW][C]0.98[/C][C]611[/C][C]612.56[/C][C]611[/C][C]611[/C][C]611[/C][C]611[/C][C]611.44[/C][C]613[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30296&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30296&T=1

As an alternative you can also use a QR Code:  

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

Percentiles - Ungrouped Data
pWeighted Average at XnpWeighted Average at X(n+1)pEmpirical Distribution FunctionEmpirical Distribution Function - AveragingEmpirical Distribution Function - InterpolationClosest ObservationTrue Basic - Statistics Graphics ToolkitMS Excel (old versions)
0.02432432.1436436436.54431434.9431
0.04437.2437.32439439440.08436437.68436
0.06440.8440.98442442442.54442440.02442
0.08442.8442.88443443446.6443442.12443
0.1448448.7448451.5454.3448454.3448
0.12455.2455.32456456456.08455455.68455
0.14456.4456.54457457457.78456456.46457
0.16458.8459.28460460460460457.72460
0.18460460460460460.62460460460
0.2461461.2461461.5461.8461461.8461
0.22462.4462.84464464463.96462463.16462
0.24465.2465.92467467467.48464465.08467
0.26468.8469.58470470470.34470467.42470
0.28470.8471471471471471471471
0.3471472.2471473473.8471473.8471
0.32475.2475.52476476475.88475475.48476
0.34478479.7481481481.18476477.3481
0.36482.8483.88484484484.24484481.12484
0.38484.8485.54485485486.26485487.46485
0.4488490488490.5491488491488
0.42494.6497.96501501499.24493496.04501
0.44501501501501501501501501
0.46502.2503.24503503503.56503506.76503
0.48506.2507.56507507507.64507508.44507
0.5509509509509509509509509
0.52509.2509.72510510509.68509509.28510
0.54510510510510510510510510
0.56511.2512.16512512512.04512512.84512
0.58512.8514.52513513513.88513515.48513
0.6517517517517517517517517
0.62517.4518.64519519518.16517517.36519
0.64519519.08519519519519520.92519
0.66520.2521.52521521520.88521522.48521
0.68522.6523.96523523523.24523524.04523
0.7525533.4525531528.6525528.6537
0.72538.2542.52543543539.88537537.48543
0.74543.4544.42544544543.66543546.58544
0.76545.8549.88547547546.52547552.12547
0.78553.4555555555555555555555
0.8555559.8555558556.2555556.2561
0.82561.2562.06562562561.38561564.94562
0.84563.2565.96565565563.68562568.04565
0.86567.4573.14569569567.96569573.86569
0.88576.2579.36578578577.28578578.64580
0.9580592.6580587581.4580581.4594
0.92594594.12594594594594594.88594
0.94594.4600.44595595594.46594605.56595
0.96604.6611611611605.24611611611
0.98611612.56611611611611611.44613



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
x <-sort(x[!is.na(x)])
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]
}
}
}
}
lx <- length(x)
qval <- array(NA,dim=c(99,8))
mystep <- 25
mystart <- 25
if (lx>10){
mystep=10
mystart=10
}
if (lx>20){
mystep=5
mystart=5
}
if (lx>50){
mystep=2
mystart=2
}
if (lx>=100){
mystep=1
mystart=1
}
for (perc in seq(mystart,99,mystep)) {
qval[perc,1] <- q1(x,lx,perc/100,i,f)
qval[perc,2] <- q2(x,lx,perc/100,i,f)
qval[perc,3] <- q3(x,lx,perc/100,i,f)
qval[perc,4] <- q4(x,lx,perc/100,i,f)
qval[perc,5] <- q5(x,lx,perc/100,i,f)
qval[perc,6] <- q6(x,lx,perc/100,i,f)
qval[perc,7] <- q7(x,lx,perc/100,i,f)
qval[perc,8] <- q8(x,lx,perc/100,i,f)
}
bitmap(file='test1.png')
myqqnorm <- qqnorm(x,col=2)
qqline(x)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Percentiles - Ungrouped Data',9,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p',1,TRUE)
a<-table.element(a,hyperlink('method_1.htm', 'Weighted Average at Xnp',''),1,TRUE)
a<-table.element(a,hyperlink('method_2.htm','Weighted Average at X(n+1)p',''),1,TRUE)
a<-table.element(a,hyperlink('method_3.htm','Empirical Distribution Function',''),1,TRUE)
a<-table.element(a,hyperlink('method_4.htm','Empirical Distribution Function - Averaging',''),1,TRUE)
a<-table.element(a,hyperlink('method_5.htm','Empirical Distribution Function - Interpolation',''),1,TRUE)
a<-table.element(a,hyperlink('method_6.htm','Closest Observation',''),1,TRUE)
a<-table.element(a,hyperlink('method_7.htm','True Basic - Statistics Graphics Toolkit',''),1,TRUE)
a<-table.element(a,hyperlink('method_8.htm','MS Excel (old versions)',''),1,TRUE)
a<-table.row.end(a)
for (perc in seq(mystart,99,mystep)) {
a<-table.row.start(a)
a<-table.element(a,round(perc/100,2),1,TRUE)
for (j in 1:8) {
a<-table.element(a,round(qval[perc,j],6))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')